= 1, quiet = TRUE)
f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 86.5083 -3.1968 4.1673 1.7173 48.7028
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> RxODE 1.1.1 using 8 threads (see ?getRxThreads)
+#> no cache: create with `rxCreateCache()`
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.579 0.328 5.909
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.546 0.379 5.924
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 7.125 0.34 7.462
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.842 0.338 7.177
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.03 0.407 15.43
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.14 0.971 16.13
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.253 0.121 1.373
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.271 0.123 1.393
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.487 0.387 6.872
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.385 0.1 1.485
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.699 0.341 7.038
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.384 0.092 1.477
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.06 0.434 15.49
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.86 1.172 16.03
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.599 0.38 8.975
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.461 0.404 8.863
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.64 0.453 18.09
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 18.02 0.925 18.94
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.772 0.04 0.813
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.782 0.02 0.803
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.33 0.419 8.745
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.405 8.575
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.832 0.032 0.866
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.824 0.024 0.851
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 18.15 0.42 18.57
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.44 0.876 18.31
#>
+#> Attaching package: ‘nlmixr’
#> The following object is masked from ‘package:mkin’:
+#>
+#> saem
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> RxODE 1.1.1 using 8 threads (see ?getRxThreads)
-#> no cache: create with `rxCreateCache()`
#> 1: 86.5083 -3.1968 4.1673 1.7173 48.7028
-#> 2: 87.3628 -3.1468 3.9589 1.6315 45.1225
-#> 3: 86.8866 -3.2249 3.7610 1.8212 43.0034
-#> 4: 85.9210 -3.2427 3.5729 1.7302 39.4197
-#> 5: 85.8539 -3.2018 3.3943 1.7234 38.2933
-#> 6: 85.6934 -3.2262 3.2246 1.6843 39.0348
-#> 7: 85.7421 -3.2696 4.1298 1.7086 39.8152
-#> 8: 85.1605 -3.2190 3.9234 1.7588 41.7476
-#> 9: 84.7745 -3.2389 3.7361 1.6708 41.8512
-#> 10: 84.6549 -3.2078 3.5493 1.6489 41.6110
-#> 11: 84.4739 -3.2788 3.3718 1.5664 42.0076
-#> 12: 84.7871 -3.2674 3.4931 1.6097 40.9060
-#> 13: 84.5267 -3.2635 3.3185 1.6352 39.6914
-#> 14: 84.9806 -3.2353 3.1525 1.6470 39.2556
-#> 15: 84.9752 -3.2566 2.9949 1.6756 39.6152
-#> 16: 85.6293 -3.2232 2.8452 1.7076 39.4391
-#> 17: 85.9944 -3.2268 2.7029 1.6702 40.2731
-#> 18: 86.2811 -3.2260 2.5678 1.7100 41.4854
-#> 19: 86.2617 -3.2476 2.4489 1.7051 41.3066
-#> 20: 85.7552 -3.2032 3.3323 1.8885 42.2273
-#> 21: 85.6493 -3.2685 3.2317 1.7941 39.4198
-#> 22: 86.0133 -3.2457 4.0910 1.7044 39.0319
-#> 23: 86.1636 -3.2528 4.9399 1.6571 38.6728
-#> 24: 86.3086 -3.1708 7.0791 1.8182 39.6791
-#> 25: 85.7316 -3.2203 6.7252 1.7369 38.3546
-#> 26: 85.3476 -3.2341 6.3889 1.6864 38.0521
-#> 27: 85.6328 -3.2543 6.0695 1.6945 37.7990
-#> 28: 85.1715 -3.2191 5.7660 1.7898 38.5662
-#> 29: 85.4945 -3.2264 5.4777 1.7007 40.1659
-#> 30: 85.0864 -3.2463 5.2038 1.6156 39.0718
-#> 31: 85.8220 -3.2347 4.9436 1.6115 39.2011
-#> 32: 85.9869 -3.2400 4.6964 1.6818 41.2956
-#> 33: 85.9899 -3.2041 4.4616 1.6606 40.6657
-#> 34: 85.8353 -3.2065 4.2385 1.6868 41.5006
-#> 35: 85.8113 -3.2366 4.0266 1.8261 41.0403
-#> 36: 85.5233 -3.2389 3.8253 1.7348 39.5202
-#> 37: 85.1751 -3.2657 3.6340 1.6948 39.6097
-#> 38: 85.2768 -3.2380 3.4887 1.6820 38.7641
-#> 39: 84.8240 -3.2264 3.3143 1.5979 39.8074
-#> 40: 85.3754 -3.2147 3.1485 1.5810 39.1710
-#> 41: 85.0277 -3.2347 2.9911 1.7061 39.9948
-#> 42: 85.0113 -3.2651 3.1969 1.6208 39.7266
-#> 43: 85.0772 -3.2729 3.0371 1.6160 40.2919
-#> 44: 85.0769 -3.2272 3.3310 1.7321 38.5229
-#> 45: 85.1638 -3.2546 3.1644 1.6968 40.2382
-#> 46: 84.7966 -3.2597 5.0694 1.6816 38.7996
-#> 47: 85.0588 -3.2247 5.9549 1.7452 39.6569
-#> 48: 85.1769 -3.2557 5.6572 1.7441 37.9050
-#> 49: 84.9296 -3.2425 5.3743 1.6729 37.7885
-#> 50: 85.3414 -3.2421 5.1056 1.6646 38.2243
-#> 51: 84.9127 -3.2674 5.8827 1.7180 40.2859
-#> 52: 85.2014 -3.2471 5.5885 1.7318 39.1745
-#> 53: 85.9330 -3.2228 7.2369 1.8328 39.0461
-#> 54: 86.9718 -3.1447 6.9332 1.8404 39.3098
-#> 55: 87.2708 -3.1595 6.6308 1.8049 39.1338
-#> 56: 87.2006 -3.1746 6.2993 1.7541 38.2780
-#> 57: 87.8013 -3.2306 5.9843 1.6664 40.4876
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-#> 347: 84.8184 -3.2483 0.1126 1.6459 40.2120
-#> 348: 84.8189 -3.2483 0.1127 1.6455 40.2115
-#> 349: 84.8198 -3.2483 0.1127 1.6450 40.2087
-#> 350: 84.8202 -3.2482 0.1125 1.6454 40.2118
-#> 351: 84.8208 -3.2483 0.1120 1.6447 40.2094
-#> 352: 84.8213 -3.2483 0.1118 1.6444 40.2070
-#> 353: 84.8218 -3.2481 0.1115 1.6445 40.2077
-#> 354: 84.8226 -3.2482 0.1114 1.6439 40.2077
-#> 355: 84.8230 -3.2481 0.1113 1.6439 40.2072
-#> 356: 84.8232 -3.2479 0.1111 1.6439 40.2075
-#> 357: 84.8239 -3.2477 0.1109 1.6441 40.2021
-#> 358: 84.8245 -3.2476 0.1107 1.6445 40.2028
-#> 359: 84.8251 -3.2476 0.1107 1.6452 40.2032
-#> 360: 84.8252 -3.2474 0.1110 1.6462 40.2012
-#> 361: 84.8258 -3.2473 0.1108 1.6469 40.2043
-#> 362: 84.8260 -3.2475 0.1107 1.6467 40.2056
-#> 363: 84.8262 -3.2474 0.1106 1.6469 40.2028
-#> 364: 84.8266 -3.2472 0.1104 1.6473 40.1979
-#> 365: 84.8270 -3.2469 0.1102 1.6479 40.1923
-#> 366: 84.8273 -3.2469 0.1100 1.6482 40.1872
-#> 367: 84.8267 -3.2468 0.1099 1.6483 40.1836
-#> 368: 84.8263 -3.2470 0.1099 1.6483 40.1850
-#> 369: 84.8269 -3.2471 0.1098 1.6484 40.1864
-#> 370: 84.8274 -3.2472 0.1098 1.6484 40.1856
-#> 371: 84.8282 -3.2471 0.1101 1.6489 40.1839
-#> 372: 84.8288 -3.2469 0.1099 1.6492 40.1804
-#> 373: 84.8294 -3.2467 0.1098 1.6494 40.1806
-#> 374: 84.8301 -3.2466 0.1096 1.6491 40.1855
-#> 375: 84.8301 -3.2467 0.1093 1.6488 40.1951
-#> 376: 84.8302 -3.2467 0.1092 1.6484 40.1921
-#> 377: 84.8302 -3.2467 0.1092 1.6486 40.1842
-#> 378: 84.8300 -3.2467 0.1095 1.6485 40.1760
-#> 379: 84.8296 -3.2468 0.1094 1.6483 40.1701
-#> 380: 84.8297 -3.2469 0.1094 1.6483 40.1738
-#> 381: 84.8299 -3.2469 0.1093 1.6485 40.1801
-#> 382: 84.8302 -3.2470 0.1092 1.6488 40.1857
-#> 383: 84.8299 -3.2469 0.1090 1.6491 40.1859
-#> 384: 84.8297 -3.2470 0.1090 1.6488 40.1903
-#> 385: 84.8289 -3.2469 0.1095 1.6487 40.1978
-#> 386: 84.8282 -3.2470 0.1098 1.6487 40.1976
-#> 387: 84.8277 -3.2471 0.1101 1.6488 40.1910
-#> 388: 84.8270 -3.2471 0.1104 1.6486 40.1863
-#> 389: 84.8263 -3.2471 0.1108 1.6486 40.1837
-#> 390: 84.8259 -3.2472 0.1109 1.6491 40.1881
-#> 391: 84.8250 -3.2472 0.1111 1.6499 40.1919
-#> 392: 84.8248 -3.2471 0.1113 1.6501 40.1961
-#> 393: 84.8247 -3.2471 0.1113 1.6503 40.1941
-#> 394: 84.8241 -3.2470 0.1114 1.6508 40.1933
-#> 395: 84.8239 -3.2469 0.1115 1.6510 40.1916
-#> 396: 84.8239 -3.2468 0.1115 1.6515 40.1946
-#> 397: 84.8239 -3.2466 0.1113 1.6517 40.1979
-#> 398: 84.8241 -3.2467 0.1112 1.6519 40.1966
-#> 399: 84.8244 -3.2466 0.1112 1.6522 40.1975
-#> 400: 84.8248 -3.2466 0.1111 1.6523 40.1919
-#> 401: 84.8255 -3.2466 0.1109 1.6523 40.1889
-#> 402: 84.8259 -3.2468 0.1108 1.6523 40.1836
-#> 403: 84.8257 -3.2470 0.1109 1.6524 40.1787
-#> 404: 84.8251 -3.2470 0.1111 1.6528 40.1788
-#> 405: 84.8244 -3.2472 0.1113 1.6530 40.1761
-#> 406: 84.8235 -3.2472 0.1113 1.6529 40.1763
-#> 407: 84.8231 -3.2471 0.1112 1.6531 40.1742
-#> 408: 84.8229 -3.2471 0.1110 1.6530 40.1728
-#> 409: 84.8229 -3.2471 0.1109 1.6528 40.1698
-#> 410: 84.8233 -3.2473 0.1109 1.6524 40.1701
-#> 411: 84.8235 -3.2474 0.1109 1.6522 40.1714
-#> 412: 84.8236 -3.2474 0.1110 1.6517 40.1716
-#> 413: 84.8241 -3.2474 0.1111 1.6512 40.1741
-#> 414: 84.8238 -3.2476 0.1108 1.6508 40.1809
-#> 415: 84.8238 -3.2477 0.1108 1.6505 40.1803
-#> 416: 84.8234 -3.2475 0.1110 1.6504 40.1880
-#> 417: 84.8232 -3.2475 0.1112 1.6510 40.1938
-#> 418: 84.8232 -3.2475 0.1112 1.6511 40.1944
-#> 419: 84.8231 -3.2476 0.1114 1.6513 40.1921
-#> 420: 84.8226 -3.2477 0.1113 1.6511 40.1880
-#> 421: 84.8220 -3.2478 0.1111 1.6508 40.1859
-#> 422: 84.8213 -3.2478 0.1110 1.6503 40.1897
-#> 423: 84.8207 -3.2479 0.1110 1.6499 40.1876
-#> 424: 84.8203 -3.2479 0.1111 1.6498 40.1860
-#> 425: 84.8198 -3.2479 0.1111 1.6498 40.1817
-#> 426: 84.8191 -3.2479 0.1113 1.6498 40.1796
-#> 427: 84.8186 -3.2478 0.1112 1.6498 40.1781
-#> 428: 84.8183 -3.2478 0.1114 1.6496 40.1738
-#> 429: 84.8177 -3.2477 0.1116 1.6495 40.1695
-#> 430: 84.8172 -3.2477 0.1119 1.6496 40.1739
-#> 431: 84.8169 -3.2478 0.1120 1.6494 40.1741
-#> 432: 84.8169 -3.2479 0.1121 1.6490 40.1758
-#> 433: 84.8170 -3.2479 0.1121 1.6491 40.1793
-#> 434: 84.8171 -3.2480 0.1122 1.6488 40.1808
-#> 435: 84.8173 -3.2481 0.1123 1.6487 40.1845
-#> 436: 84.8176 -3.2481 0.1123 1.6489 40.1866
-#> 437: 84.8178 -3.2480 0.1122 1.6496 40.1872
-#> 438: 84.8183 -3.2480 0.1121 1.6502 40.1869
-#> 439: 84.8185 -3.2481 0.1119 1.6504 40.1834
-#> 440: 84.8185 -3.2480 0.1118 1.6506 40.1831
-#> 441: 84.8188 -3.2480 0.1120 1.6502 40.1893
-#> 442: 84.8192 -3.2480 0.1120 1.6501 40.1930
-#> 443: 84.8196 -3.2480 0.1120 1.6499 40.1917
-#> 444: 84.8202 -3.2478 0.1122 1.6498 40.1966
-#> 445: 84.8207 -3.2476 0.1124 1.6499 40.1977
-#> 446: 84.8210 -3.2473 0.1123 1.6496 40.2017
-#> 447: 84.8217 -3.2472 0.1123 1.6491 40.2030
-#> 448: 84.8221 -3.2473 0.1122 1.6488 40.2025
-#> 449: 84.8225 -3.2474 0.1121 1.6485 40.2069
-#> 450: 84.8224 -3.2473 0.1119 1.6484 40.2078
-#> 451: 84.8221 -3.2473 0.1118 1.6483 40.2032
-#> 452: 84.8220 -3.2472 0.1117 1.6484 40.1989
-#> 453: 84.8220 -3.2472 0.1117 1.6483 40.1953
-#> 454: 84.8220 -3.2473 0.1122 1.6483 40.1942
-#> 455: 84.8220 -3.2472 0.1124 1.6484 40.1932
-#> 456: 84.8220 -3.2470 0.1124 1.6478 40.1972
-#> 457: 84.8222 -3.2469 0.1125 1.6476 40.1989
-#> 458: 84.8226 -3.2468 0.1125 1.6479 40.1989
-#> 459: 84.8228 -3.2467 0.1126 1.6480 40.2035
-#> 460: 84.8231 -3.2467 0.1124 1.6479 40.2032
-#> 461: 84.8236 -3.2466 0.1126 1.6482 40.2030
-#> 462: 84.8238 -3.2466 0.1124 1.6481 40.2052
-#> 463: 84.8238 -3.2467 0.1123 1.6479 40.2023
-#> 464: 84.8233 -3.2467 0.1123 1.6479 40.2004
-#> 465: 84.8230 -3.2468 0.1123 1.6482 40.2043
-#> 466: 84.8233 -3.2469 0.1123 1.6480 40.2062
-#> 467: 84.8236 -3.2468 0.1121 1.6480 40.2026
-#> 468: 84.8238 -3.2468 0.1120 1.6477 40.2034
-#> 469: 84.8239 -3.2468 0.1119 1.6474 40.2035
-#> 470: 84.8241 -3.2469 0.1116 1.6473 40.2015
-#> 471: 84.8241 -3.2470 0.1116 1.6476 40.1993
-#> 472: 84.8240 -3.2469 0.1117 1.6478 40.1977
-#> 473: 84.8239 -3.2468 0.1119 1.6479 40.1949
-#> 474: 84.8239 -3.2466 0.1118 1.6480 40.1946
-#> 475: 84.8239 -3.2464 0.1119 1.6483 40.1941
-#> 476: 84.8237 -3.2462 0.1121 1.6488 40.1930
-#> 477: 84.8235 -3.2462 0.1122 1.6488 40.1901
-#> 478: 84.8235 -3.2462 0.1125 1.6488 40.1837
-#> 479: 84.8238 -3.2463 0.1128 1.6486 40.1814
-#> 480: 84.8238 -3.2464 0.1129 1.6484 40.1794
-#> 481: 84.8239 -3.2464 0.1129 1.6483 40.1783
-#> 482: 84.8237 -3.2465 0.1130 1.6482 40.1784
-#> 483: 84.8234 -3.2465 0.1130 1.6483 40.1764
-#> 484: 84.8227 -3.2465 0.1132 1.6482 40.1775
-#> 485: 84.8223 -3.2465 0.1133 1.6483 40.1764
-#> 486: 84.8219 -3.2465 0.1135 1.6484 40.1781
-#> 487: 84.8215 -3.2465 0.1136 1.6487 40.1770
-#> 488: 84.8214 -3.2466 0.1136 1.6486 40.1796
-#> 489: 84.8214 -3.2466 0.1134 1.6489 40.1801
-#> 490: 84.8214 -3.2466 0.1132 1.6490 40.1786
-#> 491: 84.8218 -3.2466 0.1131 1.6494 40.1805
-#> 492: 84.8220 -3.2465 0.1133 1.6495 40.1805
-#> 493: 84.8223 -3.2465 0.1137 1.6493 40.1791
-#> 494: 84.8223 -3.2465 0.1140 1.6494 40.1774
-#> 495: 84.8224 -3.2465 0.1142 1.6491 40.1764
-#> 496: 84.8225 -3.2465 0.1142 1.6491 40.1750
-#> 497: 84.8229 -3.2465 0.1142 1.6487 40.1742
-#> 498: 84.8230 -3.2466 0.1140 1.6485 40.1712
-#> 499: 84.8229 -3.2466 0.1137 1.6485 40.1688
-#> 500: 84.8228 -3.2468 0.1134 1.6488 40.1690
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> | #| Objective Fun | parent_0 |log_k_parent | sigma | o1 |
-#> |.....................| o2 |...........|...........|...........|
-#> | 1| 451.22394 | 1.000 | -1.000 | -0.7995 | -0.9125 |
-#> |.....................| -0.9081 |...........|...........|...........|
-#> | U| 451.22394 | 86.39 | -3.215 | 5.768 | 0.7049 |
-#> |.....................| 0.9021 |...........|...........|...........|
-#> | X| 451.22394 | 86.39 | 0.04015 | 5.768 | 0.7049 |
-#> |.....................| 0.9021 |...........|...........|...........|
-#> | G| Gill Diff. | 52.79 | 0.01520 | -15.05 | 0.6163 |
-#> |.....................| 2.488 |...........|...........|...........|
-#> | 2| 3099.6543 | 0.03939 | -1.000 | -0.5255 | -0.9237 |
-#> |.....................| -0.9534 |...........|...........|...........|
-#> | U| 3099.6543 | 3.403 | -3.215 | 6.558 | 0.6970 |
-#> |.....................| 0.8613 |...........|...........|...........|
-#> | X| 3099.6543 | 3.403 | 0.04014 | 6.558 | 0.6970 |
-#> |.....................| 0.8613 |...........|...........|...........|
-#> | 3| 473.10068 | 0.9039 | -1.000 | -0.7721 | -0.9136 |
-#> |.....................| -0.9126 |...........|...........|...........|
-#> | U| 473.10068 | 78.09 | -3.215 | 5.847 | 0.7041 |
-#> |.....................| 0.8980 |...........|...........|...........|
-#> | X| 473.10068 | 78.09 | 0.04015 | 5.847 | 0.7041 |
-#> |.....................| 0.8980 |...........|...........|...........|
-#> | 4| 450.95086 | 0.9904 | -1.000 | -0.7967 | -0.9126 |
-#> |.....................| -0.9086 |...........|...........|...........|
-#> | U| 450.95086 | 85.56 | -3.215 | 5.776 | 0.7048 |
-#> |.....................| 0.9017 |...........|...........|...........|
-#> | X| 450.95086 | 85.56 | 0.04015 | 5.776 | 0.7048 |
-#> |.....................| 0.9017 |...........|...........|...........|
-#> | F| Forward Diff. | -4.520 | 0.09729 | -14.85 | -0.2941 |
-#> |.....................| 2.449 |...........|...........|...........|
-#> | 5| 450.82239 | 0.9932 | -1.000 | -0.7873 | -0.9124 |
-#> |.....................| -0.9101 |...........|...........|...........|
-#> | U| 450.82239 | 85.81 | -3.215 | 5.804 | 0.7049 |
-#> |.....................| 0.9003 |...........|...........|...........|
-#> | X| 450.82239 | 85.81 | 0.04015 | 5.804 | 0.7049 |
-#> |.....................| 0.9003 |...........|...........|...........|
-#> | 6| 450.73959 | 0.9981 | -1.000 | -0.7712 | -0.9121 |
-#> |.....................| -0.9128 |...........|...........|...........|
-#> | U| 450.73959 | 86.23 | -3.215 | 5.850 | 0.7051 |
-#> |.....................| 0.8979 |...........|...........|...........|
-#> | X| 450.73959 | 86.23 | 0.04015 | 5.850 | 0.7051 |
-#> |.....................| 0.8979 |...........|...........|...........|
-#> | F| Forward Diff. | 41.55 | 0.02901 | -12.22 | 0.2553 |
-#> |.....................| 2.069 |...........|...........|...........|
-#> | 7| 450.34694 | 0.9875 | -1.000 | -0.7467 | -0.9114 |
-#> |.....................| -0.9169 |...........|...........|...........|
-#> | U| 450.34694 | 85.32 | -3.215 | 5.921 | 0.7056 |
-#> |.....................| 0.8942 |...........|...........|...........|
-#> | X| 450.34694 | 85.32 | 0.04014 | 5.921 | 0.7056 |
-#> |.....................| 0.8942 |...........|...........|...........|
-#> | F| Forward Diff. | -19.58 | 0.1161 | -10.02 | -0.6042 |
-#> |.....................| 1.700 |...........|...........|...........|
-#> | 8| 450.09191 | 0.9931 | -1.001 | -0.7208 | -0.9093 |
-#> |.....................| -0.9217 |...........|...........|...........|
-#> | U| 450.09191 | 85.80 | -3.216 | 5.995 | 0.7071 |
-#> |.....................| 0.8899 |...........|...........|...........|
-#> | X| 450.09191 | 85.80 | 0.04012 | 5.995 | 0.7071 |
-#> |.....................| 0.8899 |...........|...........|...........|
-#> | F| Forward Diff. | 13.00 | 0.06566 | -7.570 | -0.3896 |
-#> |.....................| 1.273 |...........|...........|...........|
-#> | 9| 449.93949 | 0.9873 | -1.002 | -0.6965 | -0.8998 |
-#> |.....................| -0.9259 |...........|...........|...........|
-#> | U| 449.93949 | 85.30 | -3.217 | 6.065 | 0.7138 |
-#> |.....................| 0.8861 |...........|...........|...........|
-#> | X| 449.93949 | 85.30 | 0.04009 | 6.065 | 0.7138 |
-#> |.....................| 0.8861 |...........|...........|...........|
-#> | F| Forward Diff. | -18.86 | 0.1073 | -5.670 | -0.6860 |
-#> |.....................| 0.8878 |...........|...........|...........|
-#> | 10| 449.82026 | 0.9918 | -1.004 | -0.6799 | -0.8791 |
-#> |.....................| -0.9254 |...........|...........|...........|
-#> | U| 449.82026 | 85.69 | -3.219 | 6.113 | 0.7284 |
-#> |.....................| 0.8865 |...........|...........|...........|
-#> | X| 449.82026 | 85.69 | 0.04000 | 6.113 | 0.7284 |
-#> |.....................| 0.8865 |...........|...........|...........|
-#> | F| Forward Diff. | 8.164 | 0.05669 | -4.296 | -0.3775 |
-#> |.....................| 0.8823 |...........|...........|...........|
-#> | 11| 449.76996 | 0.9897 | -1.006 | -0.6720 | -0.8560 |
-#> |.....................| -0.9364 |...........|...........|...........|
-#> | U| 449.76996 | 85.50 | -3.221 | 6.136 | 0.7447 |
-#> |.....................| 0.8766 |...........|...........|...........|
-#> | X| 449.76996 | 85.50 | 0.03990 | 6.136 | 0.7447 |
-#> |.....................| 0.8766 |...........|...........|...........|
-#> | F| Forward Diff. | -2.743 | 0.05613 | -3.782 | -0.3486 |
-#> |.....................| -0.07732 |...........|...........|...........|
-#> | 12| 449.73800 | 0.9901 | -1.008 | -0.6600 | -0.8416 |
-#> |.....................| -0.9169 |...........|...........|...........|
-#> | U| 449.738 | 85.54 | -3.223 | 6.170 | 0.7549 |
-#> |.....................| 0.8942 |...........|...........|...........|
-#> | X| 449.738 | 85.54 | 0.03983 | 6.170 | 0.7549 |
-#> |.....................| 0.8942 |...........|...........|...........|
-#> | F| Forward Diff. | 0.5907 | 0.04688 | -2.910 | -0.3174 |
-#> |.....................| 1.529 |...........|...........|...........|
-#> | 13| 449.73838 | 0.9854 | -1.008 | -0.6366 | -0.8390 |
-#> |.....................| -0.9292 |...........|...........|...........|
-#> | U| 449.73838 | 85.13 | -3.224 | 6.238 | 0.7567 |
-#> |.....................| 0.8831 |...........|...........|...........|
-#> | X| 449.73838 | 85.13 | 0.03981 | 6.238 | 0.7567 |
-#> |.....................| 0.8831 |...........|...........|...........|
-#> | 14| 449.71577 | 0.9877 | -1.008 | -0.6484 | -0.8403 |
-#> |.....................| -0.9231 |...........|...........|...........|
-#> | U| 449.71577 | 85.33 | -3.223 | 6.204 | 0.7558 |
-#> |.....................| 0.8886 |...........|...........|...........|
-#> | X| 449.71577 | 85.33 | 0.03982 | 6.204 | 0.7558 |
-#> |.....................| 0.8886 |...........|...........|...........|
-#> | F| Forward Diff. | -13.00 | 0.06593 | -2.084 | -0.4341 |
-#> |.....................| 1.007 |...........|...........|...........|
-#> | 15| 449.68436 | 0.9912 | -1.009 | -0.6401 | -0.8344 |
-#> |.....................| -0.9311 |...........|...........|...........|
-#> | U| 449.68436 | 85.64 | -3.224 | 6.228 | 0.7599 |
-#> |.....................| 0.8814 |...........|...........|...........|
-#> | X| 449.68436 | 85.64 | 0.03979 | 6.228 | 0.7599 |
-#> |.....................| 0.8814 |...........|...........|...........|
-#> | F| Forward Diff. | 7.939 | 0.02803 | -1.419 | -0.2659 |
-#> |.....................| 0.3125 |...........|...........|...........|
-#> | 16| 449.66988 | 0.9896 | -1.010 | -0.6363 | -0.8221 |
-#> |.....................| -0.9344 |...........|...........|...........|
-#> | U| 449.66988 | 85.50 | -3.226 | 6.239 | 0.7686 |
-#> |.....................| 0.8784 |...........|...........|...........|
-#> | X| 449.66988 | 85.50 | 0.03973 | 6.239 | 0.7686 |
-#> |.....................| 0.8784 |...........|...........|...........|
-#> | F| Forward Diff. | -0.8695 | 0.03361 | -1.202 | -0.2917 |
-#> |.....................| 0.02327 |...........|...........|...........|
-#> | 17| 449.66421 | 0.9900 | -1.012 | -0.6343 | -0.8088 |
-#> |.....................| -0.9351 |...........|...........|...........|
-#> | U| 449.66421 | 85.53 | -3.227 | 6.245 | 0.7779 |
-#> |.....................| 0.8778 |...........|...........|...........|
-#> | X| 449.66421 | 85.53 | 0.03969 | 6.245 | 0.7779 |
-#> |.....................| 0.8778 |...........|...........|...........|
-#> | 18| 449.65407 | 0.9895 | -1.015 | -0.6307 | -0.7728 |
-#> |.....................| -0.9370 |...........|...........|...........|
-#> | U| 449.65407 | 85.49 | -3.230 | 6.255 | 0.8033 |
-#> |.....................| 0.8761 |...........|...........|...........|
-#> | X| 449.65407 | 85.49 | 0.03957 | 6.255 | 0.8033 |
-#> |.....................| 0.8761 |...........|...........|...........|
-#> | F| Forward Diff. | 0.6836 | 0.009868 | -0.9456 | -0.1262 |
-#> |.....................| -0.2597 |...........|...........|...........|
-#> | 19| 449.64227 | 0.9890 | -1.006 | -0.6121 | -0.7274 |
-#> |.....................| -0.9339 |...........|...........|...........|
-#> | U| 449.64227 | 85.45 | -3.222 | 6.309 | 0.8353 |
-#> |.....................| 0.8789 |...........|...........|...........|
-#> | X| 449.64227 | 85.45 | 0.03989 | 6.309 | 0.8353 |
-#> |.....................| 0.8789 |...........|...........|...........|
-#> | F| Forward Diff. | -0.4372 | 0.06357 | 0.2445 | -0.08318 |
-#> |.....................| -0.05696 |...........|...........|...........|
-#> | 20| 449.64227 | 0.9890 | -1.006 | -0.6121 | -0.7274 |
-#> |.....................| -0.9339 |...........|...........|...........|
-#> | U| 449.64227 | 85.45 | -3.222 | 6.309 | 0.8353 |
-#> |.....................| 0.8789 |...........|...........|...........|
-#> | X| 449.64227 | 85.45 | 0.03989 | 6.309 | 0.8353 |
-#> |.....................| 0.8789 |...........|...........|...........|
-#> calculating covariance matrix
+#> no cache: create with `rxCreateCache()`
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.6754 -0.2977 2.0254 2.7655 0.7032 0.5111 15.3443
-#> 2: 93.8828 -0.2006 2.0786 2.6886 0.6681 0.4855 7.5256
-#> 3: 94.0494 -0.2006 2.0891 2.9975 0.6347 0.4612 7.0501
-#> 4: 94.1641 -0.2446 2.0103 3.6008 0.6029 0.4382 6.2482
-#> 5: 93.8983 -0.2562 1.9851 4.5637 0.5728 0.4163 6.1507
-#> 6: 93.9311 -0.2542 1.9733 5.7516 0.5441 0.3954 6.1445
-#> 7: 93.8631 -0.2535 1.9876 5.4640 0.5169 0.3757 5.9234
-#> 8: 94.2851 -0.2327 1.9851 5.7884 0.4943 0.3569 5.9887
-#> 9: 94.2114 -0.2348 2.0169 5.4990 0.4733 0.3390 5.9730
-#> 10: 94.0782 -0.1951 2.0678 5.2240 0.4969 0.3221 5.7694
-#> 11: 94.0527 -0.1898 2.0988 4.9628 0.4924 0.3060 5.6429
-#> 12: 93.9845 -0.1795 2.1168 4.7147 0.4748 0.2907 5.4764
-#> 13: 93.9424 -0.1958 2.0924 4.4790 0.4551 0.2762 5.5598
-#> 14: 94.2255 -0.2005 2.0963 4.2910 0.4552 0.2623 5.4520
-#> 15: 94.6065 -0.1964 2.0794 4.0765 0.4516 0.2492 5.5275
-#> 16: 94.8393 -0.1872 2.0825 4.7814 0.4714 0.2368 5.4708
-#> 17: 94.5489 -0.1873 2.0822 5.3772 0.4714 0.2249 5.5790
-#> 18: 94.5797 -0.1994 2.0702 5.1083 0.4563 0.2137 5.5962
-#> 19: 94.7205 -0.1987 2.0942 5.1405 0.4580 0.2030 5.8328
-#> 20: 94.2162 -0.1961 2.0955 7.2352 0.4578 0.2081 5.5730
-#> 21: 94.2688 -0.1935 2.0980 6.8735 0.4539 0.2199 5.6561
-#> 22: 94.4008 -0.2294 2.0430 6.5298 0.4312 0.2528 5.4970
-#> 23: 93.8617 -0.2126 2.0861 6.2033 0.4420 0.2401 5.3679
-#> 24: 93.9223 -0.2173 2.0786 5.8931 0.4419 0.2281 5.4475
-#> 25: 94.1259 -0.2199 2.0790 5.5985 0.4429 0.2167 5.2610
-#> 26: 93.5597 -0.1966 2.1115 5.3186 0.4521 0.2059 5.0971
-#> 27: 93.5468 -0.2077 2.1016 5.0526 0.4458 0.2090 5.2223
-#> 28: 93.6901 -0.2106 2.0884 4.8000 0.4439 0.2114 5.1693
-#> 29: 93.4521 -0.1991 2.1349 4.5600 0.4236 0.2248 5.1834
-#> 30: 93.7678 -0.1998 2.1267 5.5252 0.4212 0.2297 5.0549
-#> 31: 93.5695 -0.2039 2.1244 5.2489 0.4165 0.2334 5.0965
-#> 32: 93.8288 -0.1855 2.1392 5.1872 0.4401 0.2286 5.0321
-#> 33: 93.9053 -0.1827 2.1426 4.9278 0.4479 0.2171 5.0706
-#> 34: 94.0876 -0.1871 2.1151 4.6814 0.4613 0.2063 5.1438
-#> 35: 94.5298 -0.1845 2.1221 4.4474 0.4586 0.2006 5.1897
-#> 36: 94.3221 -0.1765 2.1144 5.3164 0.4401 0.2193 5.0921
-#> 37: 94.3600 -0.1842 2.1021 5.3586 0.4507 0.2210 5.0926
-#> 38: 94.3734 -0.1790 2.1261 5.0907 0.4494 0.2100 5.1494
-#> 39: 94.5052 -0.1806 2.1319 4.8362 0.4514 0.1995 5.0177
-#> 40: 94.1042 -0.1906 2.0983 4.5944 0.4360 0.1984 5.2507
-#> 41: 94.1815 -0.1914 2.1166 4.3646 0.4385 0.1977 5.1065
-#> 42: 93.9837 -0.2144 2.0673 4.1464 0.4378 0.1878 5.1603
-#> 43: 93.8806 -0.2107 2.0840 3.9642 0.4456 0.1848 5.0904
-#> 44: 94.1765 -0.2107 2.0722 3.7660 0.4456 0.1881 5.1562
-#> 45: 94.2089 -0.2018 2.0874 3.5777 0.4482 0.1787 5.1219
-#> 46: 93.8851 -0.2111 2.0869 3.9421 0.4462 0.1697 5.0752
-#> 47: 94.1372 -0.2192 2.0731 3.7450 0.4517 0.1733 5.1784
-#> 48: 94.0436 -0.2157 2.0730 3.5578 0.4577 0.1854 5.1957
-#> 49: 93.9915 -0.2122 2.0740 3.3799 0.4450 0.1829 5.1116
-#> 50: 94.0579 -0.2233 2.0633 3.2109 0.4453 0.1964 5.0295
-#> 51: 94.0044 -0.2283 2.0544 3.9314 0.4563 0.2118 5.0457
-#> 52: 94.1080 -0.2174 2.0551 4.8914 0.4548 0.2182 5.0504
-#> 53: 94.3715 -0.2134 2.0598 6.2569 0.4509 0.2162 4.9574
-#> 54: 94.7344 -0.2119 2.0459 5.9440 0.4563 0.2121 5.1069
-#> 55: 94.2730 -0.2055 2.0625 5.6468 0.4758 0.2125 5.2656
-#> 56: 94.0206 -0.2017 2.0715 5.3645 0.4719 0.2045 5.1400
-#> 57: 94.0409 -0.1986 2.0837 5.0963 0.4801 0.2068 5.0902
-#> 58: 94.2392 -0.2122 2.0652 4.8415 0.4560 0.2334 5.1883
-#> 59: 93.9996 -0.1962 2.0764 4.5994 0.4686 0.2417 5.1242
-#> 60: 94.1448 -0.1840 2.1016 4.3694 0.4916 0.2296 5.0867
-#> 61: 94.4861 -0.1840 2.1239 4.3846 0.4916 0.2181 5.3979
-#> 62: 93.9892 -0.1781 2.1083 5.1623 0.5216 0.2072 5.0944
-#> 63: 94.0641 -0.1822 2.1129 4.9628 0.5123 0.1969 5.4228
-#> 64: 94.1414 -0.1733 2.1343 6.7238 0.5220 0.1879 5.3546
-#> 65: 94.0908 -0.1754 2.1160 8.4197 0.5165 0.1852 5.0873
-#> 66: 94.1490 -0.1753 2.1054 7.9987 0.5183 0.1857 5.0777
-#> 67: 93.8958 -0.1613 2.1295 7.5988 0.5004 0.2102 5.0641
-#> 68: 94.0579 -0.1683 2.1511 7.2188 0.5083 0.2110 5.3362
-#> 69: 94.0001 -0.1581 2.1629 6.8579 0.5225 0.2272 5.4399
-#> 70: 93.9712 -0.1733 2.1393 6.5150 0.5153 0.2403 5.5011
-#> 71: 94.3143 -0.1758 2.0989 6.1893 0.5043 0.2713 5.5366
-#> 72: 94.2138 -0.1842 2.1003 5.8798 0.5130 0.2578 5.2964
-#> 73: 94.1742 -0.1951 2.0773 5.5858 0.5165 0.2449 5.1986
-#> 74: 94.1287 -0.2003 2.0606 5.3065 0.5115 0.2326 4.8815
-#> 75: 94.4113 -0.1918 2.0811 5.6717 0.5153 0.2210 4.8370
-#> 76: 94.5175 -0.1940 2.0773 5.3881 0.5127 0.2127 4.9333
-#> 77: 94.4157 -0.1882 2.0714 5.1187 0.5189 0.2021 5.0162
-#> 78: 94.6190 -0.2000 2.0529 4.8628 0.5057 0.2064 4.9436
-#> 79: 94.8081 -0.2006 2.0458 4.6196 0.5053 0.2177 5.0159
-#> 80: 94.7817 -0.1943 2.0547 4.3886 0.5076 0.2099 5.1427
-#> 81: 94.5410 -0.1990 2.0686 4.8770 0.5032 0.2092 5.1192
-#> 82: 94.9536 -0.1936 2.0879 6.9870 0.4781 0.2068 5.1053
-#> 83: 94.7923 -0.1936 2.0777 6.6377 0.4734 0.2120 5.1233
-#> 84: 94.9314 -0.1881 2.0981 6.3058 0.4701 0.2088 5.2821
-#> 85: 94.8024 -0.1866 2.0975 5.9905 0.4684 0.2150 5.2088
-#> 86: 94.6506 -0.2019 2.0677 5.6910 0.4510 0.2043 5.2488
-#> 87: 94.9460 -0.1868 2.0823 5.4064 0.4625 0.2089 5.2663
-#> 88: 94.6365 -0.1901 2.0791 5.3471 0.4509 0.2203 5.2214
-#> 89: 94.5943 -0.2135 2.0521 5.0798 0.4585 0.2093 5.0161
-#> 90: 94.7957 -0.2131 2.0545 4.8258 0.4502 0.2026 5.1344
-#> 91: 94.6308 -0.2096 2.0565 4.5845 0.4566 0.2108 5.0403
-#> 92: 94.3521 -0.2059 2.0557 4.3553 0.4925 0.2072 5.3715
-#> 93: 94.5188 -0.2130 2.0646 4.1375 0.4980 0.1996 5.5624
-#> 94: 94.5995 -0.2056 2.0593 3.9306 0.4995 0.2167 5.3581
-#> 95: 94.7276 -0.1868 2.0922 3.7341 0.4863 0.2059 5.3610
-#> 96: 94.5986 -0.1900 2.0771 3.5474 0.4998 0.1956 5.2070
-#> 97: 94.2586 -0.1881 2.1051 3.9558 0.4757 0.1858 5.1561
-#> 98: 94.0716 -0.2098 2.0698 5.6441 0.4539 0.2044 5.1802
-#> 99: 94.2657 -0.2065 2.0679 5.6964 0.4679 0.2190 5.3608
-#> 100: 94.2331 -0.2203 2.0679 5.4116 0.4445 0.2256 5.4031
-#> 101: 93.8634 -0.2222 2.0720 5.1410 0.4279 0.2341 5.3774
-#> 102: 93.7675 -0.2496 2.0232 4.8839 0.4103 0.2224 5.1238
-#> 103: 93.9534 -0.2416 2.0249 4.6397 0.4144 0.2113 5.0031
-#> 104: 94.0631 -0.2442 2.0216 4.8203 0.4119 0.2007 5.1163
-#> 105: 94.0324 -0.2464 2.0092 4.5793 0.4135 0.2047 5.1666
-#> 106: 93.9954 -0.2482 2.0256 4.9167 0.4083 0.2052 5.2515
-#> 107: 94.2189 -0.2507 2.0121 4.6709 0.4072 0.2087 5.3430
-#> 108: 94.3707 -0.2448 2.0215 4.4373 0.4119 0.1996 5.1549
-#> 109: 94.1518 -0.2428 2.0197 4.2155 0.4155 0.1958 5.5480
-#> 110: 93.9287 -0.2571 2.0275 4.0047 0.4152 0.1931 5.8482
-#> 111: 93.9743 -0.2488 2.0202 3.8045 0.4171 0.2084 5.9798
-#> 112: 93.6245 -0.2350 2.0346 3.6142 0.4397 0.1980 6.0270
-#> 113: 94.5370 -0.2330 2.0593 3.9090 0.4422 0.1881 5.4431
-#> 114: 94.5052 -0.2289 2.0555 3.7135 0.4391 0.1787 5.5970
-#> 115: 94.5963 -0.2216 2.0579 3.5279 0.4446 0.1727 5.3901
-#> 116: 94.5059 -0.2293 2.0459 3.3515 0.4407 0.1705 5.2788
-#> 117: 94.6315 -0.2211 2.0564 3.1839 0.4279 0.1689 5.3258
-#> 118: 94.4868 -0.2194 2.0508 4.6523 0.4275 0.1604 5.1421
-#> 119: 94.1809 -0.2232 2.0444 7.0101 0.4302 0.1612 5.3468
-#> 120: 94.0950 -0.2231 2.0482 7.2110 0.4304 0.1625 5.1691
-#> 121: 94.1525 -0.2059 2.0682 6.8504 0.4474 0.1875 5.2811
-#> 122: 94.7122 -0.2154 2.0692 6.6747 0.4366 0.1906 5.3851
-#> 123: 94.2915 -0.2311 2.0431 6.9655 0.4351 0.2021 5.2103
-#> 124: 93.9984 -0.2310 2.0401 6.6173 0.4396 0.2091 5.0920
-#> 125: 94.3668 -0.2068 2.0505 6.2864 0.4983 0.1987 5.3263
-#> 126: 94.3570 -0.2043 2.0525 5.9721 0.5006 0.1887 5.3281
-#> 127: 94.7086 -0.2177 2.0377 5.6735 0.4762 0.1958 5.4003
-#> 128: 94.3565 -0.2173 2.0432 5.3898 0.4754 0.2055 5.5196
-#> 129: 94.4862 -0.2066 2.0639 5.1203 0.4807 0.1952 5.4783
-#> 130: 94.6107 -0.2026 2.0908 4.8643 0.4579 0.1855 5.6186
-#> 131: 94.6831 -0.1907 2.0920 4.6211 0.4710 0.1762 5.4859
-#> 132: 94.7035 -0.2052 2.0733 4.6333 0.4492 0.1723 5.2721
-#> 133: 94.1511 -0.2192 2.0615 5.7533 0.4362 0.1905 5.5019
-#> 134: 94.2758 -0.2101 2.0624 5.4656 0.4356 0.1810 5.3233
-#> 135: 94.6546 -0.1960 2.0826 5.1923 0.4281 0.1980 5.2515
-#> 136: 94.0322 -0.2100 2.0770 4.9327 0.4156 0.2103 5.3514
-#> 137: 94.0915 -0.2096 2.0859 5.6044 0.4159 0.2008 5.2755
-#> 138: 94.2452 -0.1983 2.1055 6.0837 0.4213 0.2185 5.0580
-#> 139: 94.5460 -0.1876 2.1093 6.8410 0.4301 0.2288 5.0840
-#> 140: 94.6905 -0.1863 2.1167 7.4689 0.4313 0.2173 5.0868
-#> 141: 94.6425 -0.1703 2.1240 7.0955 0.4522 0.2065 4.9715
-#> 142: 94.2538 -0.1632 2.1514 6.7407 0.4499 0.2059 5.0853
-#> 143: 94.3098 -0.1625 2.1567 6.4037 0.4499 0.2115 5.5860
-#> 144: 94.2802 -0.1716 2.1510 6.0835 0.4535 0.2081 5.1989
-#> 145: 94.1169 -0.1707 2.1523 5.7793 0.4531 0.2109 5.1407
-#> 146: 94.2558 -0.1579 2.1623 5.4903 0.4654 0.2427 5.2652
-#> 147: 93.9440 -0.1587 2.1673 5.2158 0.4611 0.2537 5.2699
-#> 148: 94.4271 -0.1587 2.1586 4.9550 0.4611 0.2595 5.1280
-#> 149: 94.2734 -0.1768 2.1160 4.7073 0.4809 0.2802 4.9251
-#> 150: 94.2406 -0.1928 2.0941 5.4176 0.4626 0.2662 5.0837
-#> 151: 94.4217 -0.1884 2.0965 5.1467 0.4677 0.2538 5.1728
-#> 152: 94.4856 -0.1826 2.1127 5.6736 0.4646 0.2373 5.1522
-#> 153: 94.3458 -0.1686 2.1381 6.3603 0.4760 0.2028 5.2197
-#> 154: 94.3945 -0.1633 2.1370 5.1586 0.4402 0.1955 5.3770
-#> 155: 94.6367 -0.1520 2.1596 6.4738 0.4533 0.1882 5.3345
-#> 156: 94.9050 -0.1521 2.1417 6.8382 0.4532 0.1729 5.2770
-#> 157: 94.5823 -0.1540 2.1326 5.5745 0.4487 0.1813 5.2760
-#> 158: 94.8355 -0.1691 2.1357 5.2979 0.4296 0.1990 5.3177
-#> 159: 94.7330 -0.1740 2.1148 4.0960 0.4476 0.1820 5.3001
-#> 160: 94.4926 -0.1731 2.1123 4.3550 0.4666 0.1817 5.1849
-#> 161: 94.4953 -0.1758 2.1063 4.0311 0.4698 0.1929 5.1371
-#> 162: 94.5639 -0.1753 2.1064 4.3044 0.4692 0.1911 5.1437
-#> 163: 94.5477 -0.1798 2.1041 4.1393 0.4804 0.2002 5.3561
-#> 164: 94.3812 -0.1934 2.1019 3.5760 0.4689 0.1908 5.3231
-#> 165: 94.0978 -0.1924 2.0973 2.2052 0.4743 0.1962 5.2813
-#> 166: 94.1374 -0.2043 2.0834 2.5477 0.4639 0.1904 5.3277
-#> 167: 94.1587 -0.2036 2.0797 2.7035 0.4561 0.1951 5.3106
-#> 168: 94.1518 -0.2166 2.0654 2.4969 0.4405 0.2090 5.3148
-#> 169: 94.3328 -0.2164 2.0652 2.3067 0.4455 0.1993 5.2385
-#> 170: 94.6029 -0.2176 2.0456 1.7913 0.4478 0.2085 5.4589
-#> 171: 94.2690 -0.2189 2.0635 1.8133 0.4496 0.1999 5.4918
-#> 172: 94.3227 -0.2120 2.0643 1.7763 0.4337 0.2063 5.4992
-#> 173: 94.3099 -0.2039 2.0892 1.1103 0.4350 0.2201 5.5148
-#> 174: 94.3192 -0.1895 2.1140 0.9817 0.4454 0.2078 5.5249
-#> 175: 94.2327 -0.1967 2.0939 0.9890 0.4361 0.1876 5.6321
-#> 176: 94.2707 -0.1989 2.0958 1.3001 0.4405 0.1790 5.6494
-#> 177: 94.0762 -0.2024 2.0908 0.9179 0.4426 0.1778 5.7085
-#> 178: 94.1807 -0.2074 2.0761 1.2663 0.4237 0.2064 5.5157
-#> 179: 94.2221 -0.2029 2.1083 2.0148 0.4270 0.2023 5.6770
-#> 180: 94.5889 -0.1975 2.0974 1.5302 0.4223 0.1778 5.7495
-#> 181: 94.4280 -0.2163 2.0648 1.8829 0.3908 0.1994 5.3948
-#> 182: 94.7076 -0.2247 2.0340 2.1148 0.4238 0.2062 5.4167
-#> 183: 94.5127 -0.2292 2.0317 3.0950 0.4302 0.2160 5.5009
-#> 184: 94.2522 -0.2335 2.0515 2.8900 0.4265 0.2038 5.2995
-#> 185: 94.2331 -0.2330 2.0431 3.3282 0.4276 0.2044 5.2220
-#> 186: 94.2207 -0.2259 2.0512 4.0568 0.4253 0.2008 5.2307
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-#> 191: 94.3882 -0.2475 1.9949 4.5490 0.4366 0.1972 5.2470
-#> 192: 94.4267 -0.2478 1.9943 4.3327 0.4281 0.1995 5.2792
-#> 193: 94.6313 -0.2522 1.9703 3.5911 0.4321 0.1944 5.6218
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-#> 208: 94.4802 -0.1789 2.0950 1.3488 0.5137 0.1450 5.7072
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-#> 233: 94.2692 -0.1682 2.1279 1.4649 0.5076 0.1570 5.6027
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-#> 235: 94.2623 -0.1673 2.1302 1.4424 0.5064 0.1593 5.5919
-#> 236: 94.2610 -0.1667 2.1313 1.4255 0.5055 0.1599 5.5953
-#> 237: 94.2660 -0.1663 2.1322 1.4242 0.5053 0.1605 5.5922
-#> 238: 94.2753 -0.1666 2.1320 1.4370 0.5044 0.1611 5.5891
-#> 239: 94.2821 -0.1662 2.1326 1.4395 0.5036 0.1629 5.5864
-#> 240: 94.2886 -0.1661 2.1330 1.4375 0.5028 0.1644 5.5815
-#> 241: 94.2934 -0.1664 2.1329 1.4276 0.5020 0.1661 5.5777
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-#> 245: 94.2959 -0.1675 2.1316 1.4289 0.4993 0.1705 5.5524
-#> 246: 94.2992 -0.1683 2.1305 1.4378 0.4986 0.1706 5.5436
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-#> 255: 94.3111 -0.1731 2.1236 1.4755 0.4878 0.1775 5.5175
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-#> 265: 94.3098 -0.1769 2.1184 1.7115 0.4847 0.1903 5.4832
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-#> 270: 94.3025 -0.1764 2.1200 1.7440 0.4832 0.1949 5.4720
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-#> 273: 94.3046 -0.1773 2.1192 1.7820 0.4826 0.1976 5.4754
-#> 274: 94.3051 -0.1774 2.1193 1.7895 0.4823 0.1988 5.4735
-#> 275: 94.3026 -0.1773 2.1193 1.7891 0.4819 0.1998 5.4749
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-#> 278: 94.3067 -0.1771 2.1197 1.7747 0.4799 0.2039 5.4888
-#> 279: 94.3066 -0.1768 2.1202 1.7772 0.4795 0.2049 5.4889
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-#> 282: 94.2893 -0.1772 2.1203 1.7797 0.4777 0.2072 5.4865
-#> 283: 94.2880 -0.1776 2.1198 1.7743 0.4772 0.2074 5.4856
-#> 284: 94.2897 -0.1779 2.1195 1.7717 0.4768 0.2076 5.4836
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-#> 287: 94.2991 -0.1787 2.1181 1.7884 0.4761 0.2075 5.4769
-#> 288: 94.2980 -0.1793 2.1171 1.7901 0.4756 0.2077 5.4772
-#> 289: 94.2948 -0.1797 2.1166 1.7957 0.4752 0.2077 5.4763
-#> 290: 94.2922 -0.1801 2.1161 1.8012 0.4749 0.2074 5.4752
-#> 291: 94.2891 -0.1803 2.1157 1.8016 0.4747 0.2073 5.4743
-#> 292: 94.2890 -0.1805 2.1155 1.8012 0.4746 0.2072 5.4743
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-#> 294: 94.2841 -0.1811 2.1148 1.8003 0.4740 0.2075 5.4758
-#> 295: 94.2834 -0.1813 2.1143 1.7982 0.4743 0.2075 5.4766
-#> 296: 94.2817 -0.1816 2.1138 1.7997 0.4745 0.2074 5.4756
-#> 297: 94.2772 -0.1820 2.1131 1.8025 0.4747 0.2074 5.4778
-#> 298: 94.2759 -0.1822 2.1125 1.8097 0.4747 0.2073 5.4781
-#> 299: 94.2752 -0.1825 2.1120 1.8176 0.4748 0.2071 5.4784
-#> 300: 94.2758 -0.1828 2.1115 1.8353 0.4750 0.2069 5.4771
-#> 301: 94.2789 -0.1829 2.1113 1.8511 0.4749 0.2066 5.4767
-#> 302: 94.2808 -0.1833 2.1107 1.8541 0.4747 0.2065 5.4785
-#> 303: 94.2832 -0.1836 2.1103 1.8571 0.4745 0.2064 5.4789
-#> 304: 94.2838 -0.1840 2.1097 1.8584 0.4743 0.2064 5.4792
-#> 305: 94.2835 -0.1843 2.1090 1.8633 0.4741 0.2066 5.4790
-#> 306: 94.2868 -0.1847 2.1083 1.8633 0.4738 0.2069 5.4802
-#> 307: 94.2909 -0.1851 2.1076 1.8702 0.4737 0.2072 5.4787
-#> 308: 94.2916 -0.1857 2.1067 1.8754 0.4735 0.2075 5.4773
-#> 309: 94.2889 -0.1860 2.1062 1.8785 0.4732 0.2078 5.4774
-#> 310: 94.2875 -0.1863 2.1059 1.8854 0.4727 0.2082 5.4763
-#> 311: 94.2889 -0.1867 2.1053 1.8873 0.4722 0.2087 5.4746
-#> 312: 94.2889 -0.1870 2.1047 1.8956 0.4717 0.2090 5.4748
-#> 313: 94.2836 -0.1873 2.1044 1.8980 0.4711 0.2093 5.4721
-#> 314: 94.2801 -0.1876 2.1041 1.8924 0.4706 0.2096 5.4718
-#> 315: 94.2768 -0.1880 2.1038 1.8875 0.4701 0.2096 5.4727
-#> 316: 94.2766 -0.1883 2.1035 1.8854 0.4697 0.2097 5.4730
-#> 317: 94.2779 -0.1886 2.1030 1.8808 0.4693 0.2099 5.4725
-#> 318: 94.2806 -0.1889 2.1024 1.8789 0.4688 0.2101 5.4713
-#> 319: 94.2853 -0.1891 2.1018 1.8852 0.4684 0.2104 5.4690
-#> 320: 94.2867 -0.1894 2.1016 1.8898 0.4680 0.2106 5.4677
-#> 321: 94.2883 -0.1897 2.1013 1.8975 0.4676 0.2108 5.4656
-#> 322: 94.2864 -0.1899 2.1011 1.9078 0.4672 0.2109 5.4622
-#> 323: 94.2831 -0.1902 2.1009 1.9181 0.4668 0.2109 5.4593
-#> 324: 94.2799 -0.1904 2.1008 1.9355 0.4665 0.2109 5.4599
-#> 325: 94.2802 -0.1905 2.1007 1.9474 0.4660 0.2112 5.4608
-#> 326: 94.2808 -0.1907 2.1006 1.9656 0.4654 0.2114 5.4606
-#> 327: 94.2815 -0.1907 2.1006 1.9851 0.4649 0.2118 5.4596
-#> 328: 94.2805 -0.1908 2.1007 2.0051 0.4644 0.2120 5.4584
-#> 329: 94.2810 -0.1909 2.1004 2.0162 0.4638 0.2124 5.4566
-#> 330: 94.2812 -0.1912 2.0999 2.0210 0.4632 0.2131 5.4548
-#> 331: 94.2830 -0.1915 2.0994 2.0253 0.4625 0.2136 5.4520
-#> 332: 94.2835 -0.1920 2.0987 2.0288 0.4619 0.2142 5.4493
-#> 333: 94.2832 -0.1924 2.0981 2.0365 0.4615 0.2148 5.4463
-#> 334: 94.2845 -0.1928 2.0976 2.0433 0.4611 0.2153 5.4436
-#> 335: 94.2856 -0.1931 2.0971 2.0423 0.4607 0.2158 5.4405
-#> 336: 94.2886 -0.1936 2.0963 2.0400 0.4606 0.2165 5.4386
-#> 337: 94.2888 -0.1939 2.0957 2.0352 0.4604 0.2171 5.4376
-#> 338: 94.2879 -0.1944 2.0950 2.0360 0.4600 0.2179 5.4361
-#> 339: 94.2860 -0.1947 2.0946 2.0418 0.4599 0.2186 5.4342
-#> 340: 94.2842 -0.1951 2.0940 2.0455 0.4597 0.2192 5.4324
-#> 341: 94.2804 -0.1954 2.0934 2.0535 0.4596 0.2199 5.4310
-#> 342: 94.2772 -0.1958 2.0928 2.0586 0.4594 0.2204 5.4310
-#> 343: 94.2753 -0.1962 2.0921 2.0604 0.4592 0.2209 5.4304
-#> 344: 94.2749 -0.1965 2.0916 2.0591 0.4589 0.2214 5.4305
-#> 345: 94.2757 -0.1969 2.0911 2.0582 0.4586 0.2220 5.4302
-#> 346: 94.2774 -0.1972 2.0906 2.0554 0.4584 0.2225 5.4301
-#> 347: 94.2772 -0.1974 2.0901 2.0533 0.4583 0.2230 5.4298
-#> 348: 94.2769 -0.1977 2.0895 2.0497 0.4581 0.2235 5.4302
-#> 349: 94.2792 -0.1980 2.0890 2.0439 0.4579 0.2241 5.4327
-#> 350: 94.2825 -0.1983 2.0884 2.0391 0.4577 0.2245 5.4358
-#> 351: 94.2849 -0.1985 2.0879 2.0352 0.4576 0.2251 5.4399
-#> 352: 94.2871 -0.1988 2.0874 2.0396 0.4576 0.2257 5.4414
-#> 353: 94.2888 -0.1991 2.0869 2.0407 0.4573 0.2262 5.4417
-#> 354: 94.2914 -0.1994 2.0863 2.0383 0.4571 0.2268 5.4417
-#> 355: 94.2933 -0.1996 2.0859 2.0385 0.4570 0.2275 5.4418
-#> 356: 94.2932 -0.1999 2.0853 2.0377 0.4569 0.2284 5.4426
-#> 357: 94.2944 -0.2001 2.0850 2.0362 0.4566 0.2292 5.4423
-#> 358: 94.2948 -0.2003 2.0847 2.0415 0.4562 0.2299 5.4409
-#> 359: 94.2950 -0.2005 2.0843 2.0452 0.4558 0.2304 5.4393
-#> 360: 94.2967 -0.2008 2.0840 2.0514 0.4554 0.2307 5.4385
-#> 361: 94.2983 -0.2009 2.0839 2.0676 0.4551 0.2308 5.4386
-#> 362: 94.2992 -0.2009 2.0840 2.0770 0.4549 0.2307 5.4370
-#> 363: 94.2991 -0.2008 2.0841 2.0831 0.4550 0.2306 5.4348
-#> 364: 94.2982 -0.2007 2.0843 2.0892 0.4549 0.2304 5.4348
-#> 365: 94.2951 -0.2005 2.0847 2.1002 0.4551 0.2302 5.4347
-#> 366: 94.2938 -0.2004 2.0850 2.1176 0.4553 0.2300 5.4343
-#> 367: 94.2945 -0.2003 2.0850 2.1310 0.4553 0.2298 5.4346
-#> 368: 94.2956 -0.2003 2.0851 2.1436 0.4554 0.2295 5.4323
-#> 369: 94.2960 -0.2003 2.0850 2.1526 0.4555 0.2293 5.4309
-#> 370: 94.2964 -0.2003 2.0848 2.1577 0.4555 0.2292 5.4295
-#> 371: 94.2965 -0.2004 2.0847 2.1621 0.4555 0.2290 5.4278
-#> 372: 94.2972 -0.2004 2.0847 2.1635 0.4556 0.2285 5.4275
-#> 373: 94.2975 -0.2003 2.0848 2.1643 0.4556 0.2282 5.4275
-#> 374: 94.2985 -0.2004 2.0847 2.1648 0.4556 0.2277 5.4270
-#> 375: 94.3001 -0.2004 2.0846 2.1682 0.4555 0.2273 5.4255
-#> 376: 94.3024 -0.2005 2.0845 2.1692 0.4555 0.2268 5.4246
-#> 377: 94.3050 -0.2005 2.0843 2.1700 0.4555 0.2264 5.4239
-#> 378: 94.3041 -0.2005 2.0843 2.1680 0.4555 0.2258 5.4242
-#> 379: 94.3034 -0.2006 2.0842 2.1688 0.4554 0.2255 5.4233
-#> 380: 94.3027 -0.2007 2.0840 2.1754 0.4554 0.2250 5.4222
-#> 381: 94.3015 -0.2008 2.0839 2.1806 0.4553 0.2246 5.4205
-#> 382: 94.3006 -0.2009 2.0837 2.1812 0.4552 0.2242 5.4194
-#> 383: 94.3004 -0.2010 2.0835 2.1835 0.4551 0.2236 5.4178
-#> 384: 94.3001 -0.2011 2.0834 2.1895 0.4550 0.2232 5.4159
-#> 385: 94.3005 -0.2012 2.0834 2.1910 0.4547 0.2228 5.4148
-#> 386: 94.2993 -0.2013 2.0834 2.1926 0.4545 0.2224 5.4139
-#> 387: 94.2974 -0.2014 2.0834 2.1956 0.4543 0.2221 5.4135
-#> 388: 94.2964 -0.2014 2.0835 2.1979 0.4541 0.2218 5.4124
-#> 389: 94.2956 -0.2013 2.0837 2.1974 0.4540 0.2215 5.4117
-#> 390: 94.2962 -0.2013 2.0838 2.1995 0.4538 0.2213 5.4115
-#> 391: 94.2962 -0.2013 2.0838 2.1987 0.4537 0.2211 5.4116
-#> 392: 94.2956 -0.2013 2.0839 2.2007 0.4536 0.2209 5.4111
-#> 393: 94.2954 -0.2012 2.0839 2.2041 0.4535 0.2207 5.4106
-#> 394: 94.2953 -0.2012 2.0840 2.2033 0.4535 0.2205 5.4103
-#> 395: 94.2964 -0.2012 2.0841 2.2052 0.4533 0.2203 5.4098
-#> 396: 94.2950 -0.2012 2.0841 2.2123 0.4532 0.2202 5.4081
-#> 397: 94.2940 -0.2011 2.0843 2.2227 0.4533 0.2201 5.4070
-#> 398: 94.2938 -0.2011 2.0842 2.2283 0.4534 0.2201 5.4065
-#> 399: 94.2930 -0.2012 2.0842 2.2296 0.4535 0.2201 5.4066
-#> 400: 94.2931 -0.2011 2.0844 2.2345 0.4537 0.2199 5.4071
-#> 401: 94.2926 -0.2009 2.0846 2.2414 0.4539 0.2198 5.4067
-#> 402: 94.2916 -0.2008 2.0848 2.2478 0.4541 0.2196 5.4070
-#> 403: 94.2902 -0.2007 2.0849 2.2543 0.4544 0.2194 5.4071
-#> 404: 94.2895 -0.2007 2.0851 2.2578 0.4546 0.2192 5.4079
-#> 405: 94.2896 -0.2006 2.0853 2.2600 0.4548 0.2190 5.4082
-#> 406: 94.2897 -0.2004 2.0855 2.2636 0.4550 0.2188 5.4086
-#> 407: 94.2880 -0.2002 2.0859 2.2670 0.4554 0.2188 5.4079
-#> 408: 94.2883 -0.1999 2.0861 2.2735 0.4556 0.2189 5.4076
-#> 409: 94.2874 -0.1997 2.0865 2.2822 0.4559 0.2190 5.4073
-#> 410: 94.2861 -0.1995 2.0867 2.2861 0.4563 0.2190 5.4062
-#> 411: 94.2861 -0.1993 2.0869 2.2883 0.4566 0.2190 5.4049
-#> 412: 94.2869 -0.1991 2.0872 2.2926 0.4570 0.2190 5.4039
-#> 413: 94.2874 -0.1990 2.0873 2.2936 0.4574 0.2190 5.4031
-#> 414: 94.2881 -0.1988 2.0874 2.2972 0.4577 0.2189 5.4019
-#> 415: 94.2895 -0.1987 2.0876 2.2999 0.4580 0.2188 5.4004
-#> 416: 94.2900 -0.1985 2.0878 2.3003 0.4582 0.2186 5.3997
-#> 417: 94.2917 -0.1984 2.0880 2.2986 0.4583 0.2185 5.3993
-#> 418: 94.2937 -0.1982 2.0882 2.2986 0.4584 0.2183 5.3995
-#> 419: 94.2947 -0.1981 2.0885 2.2993 0.4584 0.2182 5.3995
-#> 420: 94.2954 -0.1979 2.0886 2.2993 0.4585 0.2180 5.3996
-#> 421: 94.2963 -0.1978 2.0888 2.3029 0.4587 0.2180 5.3992
-#> 422: 94.2982 -0.1976 2.0890 2.3074 0.4588 0.2178 5.4000
-#> 423: 94.3001 -0.1975 2.0891 2.3099 0.4589 0.2178 5.3999
-#> 424: 94.3007 -0.1974 2.0891 2.3106 0.4589 0.2177 5.4001
-#> 425: 94.3016 -0.1973 2.0893 2.3107 0.4589 0.2176 5.3997
-#> 426: 94.3021 -0.1972 2.0894 2.3119 0.4590 0.2175 5.3990
-#> 427: 94.3009 -0.1972 2.0894 2.3100 0.4590 0.2175 5.3971
-#> 428: 94.2998 -0.1972 2.0895 2.3070 0.4590 0.2175 5.3966
-#> 429: 94.2988 -0.1973 2.0895 2.3033 0.4590 0.2175 5.3958
-#> 430: 94.2968 -0.1973 2.0895 2.3028 0.4590 0.2174 5.3955
-#> 431: 94.2950 -0.1973 2.0895 2.3004 0.4589 0.2174 5.3954
-#> 432: 94.2944 -0.1973 2.0896 2.2966 0.4589 0.2174 5.3956
-#> 433: 94.2950 -0.1972 2.0897 2.2942 0.4589 0.2176 5.3959
-#> 434: 94.2949 -0.1972 2.0898 2.2911 0.4589 0.2177 5.3955
-#> 435: 94.2943 -0.1971 2.0900 2.2914 0.4588 0.2179 5.3943
-#> 436: 94.2943 -0.1970 2.0902 2.2895 0.4586 0.2180 5.3948
-#> 437: 94.2955 -0.1970 2.0903 2.2890 0.4585 0.2181 5.3954
-#> 438: 94.2961 -0.1969 2.0905 2.2918 0.4584 0.2183 5.3958
-#> 439: 94.2954 -0.1968 2.0906 2.2943 0.4583 0.2185 5.3953
-#> 440: 94.2944 -0.1968 2.0906 2.2977 0.4581 0.2187 5.3949
-#> 441: 94.2931 -0.1968 2.0907 2.2991 0.4578 0.2188 5.3952
-#> 442: 94.2926 -0.1968 2.0908 2.2990 0.4575 0.2188 5.3951
-#> 443: 94.2922 -0.1968 2.0909 2.2990 0.4573 0.2188 5.3938
-#> 444: 94.2917 -0.1969 2.0909 2.2995 0.4571 0.2188 5.3927
-#> 445: 94.2901 -0.1969 2.0910 2.3067 0.4568 0.2187 5.3911
-#> 446: 94.2898 -0.1969 2.0910 2.3082 0.4566 0.2187 5.3891
-#> 447: 94.2897 -0.1969 2.0910 2.3121 0.4564 0.2187 5.3871
-#> 448: 94.2883 -0.1970 2.0911 2.3180 0.4562 0.2188 5.3858
-#> 449: 94.2879 -0.1970 2.0912 2.3210 0.4561 0.2188 5.3851
-#> 450: 94.2874 -0.1970 2.0914 2.3243 0.4559 0.2188 5.3841
-#> 451: 94.2873 -0.1969 2.0915 2.3247 0.4557 0.2188 5.3834
-#> 452: 94.2873 -0.1969 2.0917 2.3249 0.4555 0.2187 5.3839
-#> 453: 94.2868 -0.1968 2.0920 2.3257 0.4554 0.2187 5.3831
-#> 454: 94.2857 -0.1967 2.0922 2.3240 0.4552 0.2187 5.3824
-#> 455: 94.2848 -0.1965 2.0925 2.3214 0.4551 0.2186 5.3822
-#> 456: 94.2838 -0.1964 2.0929 2.3204 0.4550 0.2185 5.3822
-#> 457: 94.2831 -0.1962 2.0932 2.3202 0.4549 0.2184 5.3819
-#> 458: 94.2831 -0.1961 2.0935 2.3174 0.4548 0.2183 5.3810
-#> 459: 94.2829 -0.1960 2.0938 2.3183 0.4546 0.2183 5.3807
-#> 460: 94.2818 -0.1958 2.0941 2.3213 0.4545 0.2183 5.3802
-#> 461: 94.2812 -0.1956 2.0945 2.3292 0.4544 0.2182 5.3785
-#> 462: 94.2813 -0.1955 2.0948 2.3328 0.4544 0.2182 5.3778
-#> 463: 94.2816 -0.1953 2.0951 2.3364 0.4543 0.2181 5.3770
-#> 464: 94.2810 -0.1952 2.0954 2.3365 0.4542 0.2180 5.3764
-#> 465: 94.2797 -0.1950 2.0957 2.3341 0.4541 0.2179 5.3756
-#> 466: 94.2777 -0.1949 2.0960 2.3368 0.4541 0.2178 5.3750
-#> 467: 94.2755 -0.1949 2.0962 2.3417 0.4539 0.2178 5.3738
-#> 468: 94.2741 -0.1948 2.0965 2.3426 0.4537 0.2177 5.3731
-#> 469: 94.2735 -0.1947 2.0967 2.3410 0.4535 0.2175 5.3729
-#> 470: 94.2731 -0.1946 2.0970 2.3440 0.4534 0.2173 5.3733
-#> 471: 94.2727 -0.1945 2.0972 2.3505 0.4533 0.2171 5.3724
-#> 472: 94.2734 -0.1944 2.0973 2.3550 0.4533 0.2169 5.3719
-#> 473: 94.2745 -0.1944 2.0974 2.3593 0.4533 0.2167 5.3715
-#> 474: 94.2746 -0.1944 2.0975 2.3622 0.4533 0.2166 5.3708
-#> 475: 94.2753 -0.1943 2.0975 2.3673 0.4533 0.2165 5.3701
-#> 476: 94.2760 -0.1943 2.0976 2.3745 0.4534 0.2166 5.3698
-#> 477: 94.2771 -0.1942 2.0978 2.3812 0.4535 0.2166 5.3695
-#> 478: 94.2767 -0.1941 2.0981 2.3891 0.4535 0.2166 5.3691
-#> 479: 94.2762 -0.1940 2.0984 2.3931 0.4534 0.2166 5.3691
-#> 480: 94.2754 -0.1939 2.0986 2.3958 0.4533 0.2166 5.3685
-#> 481: 94.2743 -0.1938 2.0987 2.3990 0.4532 0.2165 5.3677
-#> 482: 94.2733 -0.1937 2.0988 2.3996 0.4531 0.2164 5.3670
-#> 483: 94.2724 -0.1937 2.0989 2.4031 0.4531 0.2163 5.3659
-#> 484: 94.2726 -0.1937 2.0989 2.4035 0.4530 0.2162 5.3651
-#> 485: 94.2722 -0.1937 2.0989 2.4033 0.4530 0.2162 5.3649
-#> 486: 94.2716 -0.1936 2.0991 2.4046 0.4529 0.2163 5.3645
-#> 487: 94.2710 -0.1936 2.0992 2.4078 0.4527 0.2165 5.3643
-#> 488: 94.2693 -0.1936 2.0992 2.4088 0.4525 0.2167 5.3653
-#> 489: 94.2689 -0.1936 2.0993 2.4116 0.4523 0.2170 5.3645
-#> 490: 94.2686 -0.1936 2.0993 2.4105 0.4520 0.2172 5.3644
-#> 491: 94.2685 -0.1935 2.0994 2.4097 0.4518 0.2174 5.3651
-#> 492: 94.2677 -0.1935 2.0995 2.4103 0.4517 0.2175 5.3657
-#> 493: 94.2670 -0.1935 2.0996 2.4112 0.4515 0.2177 5.3661
-#> 494: 94.2668 -0.1935 2.0996 2.4140 0.4514 0.2178 5.3662
-#> 495: 94.2667 -0.1936 2.0996 2.4157 0.4513 0.2179 5.3660
-#> 496: 94.2670 -0.1936 2.0996 2.4163 0.4511 0.2180 5.3668
-#> 497: 94.2664 -0.1936 2.0996 2.4170 0.4510 0.2181 5.3676
-#> 498: 94.2654 -0.1937 2.0996 2.4128 0.4509 0.2181 5.3683
-#> 499: 94.2643 -0.1937 2.0996 2.4109 0.4508 0.2181 5.3679
-#> 500: 94.2635 -0.1938 2.0995 2.4122 0.4508 0.2181 5.3682
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#>
Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> | #| Objective Fun | parent_0 | log_alpha | log_beta | sigma |
-#>
|.....................| o1 | o2 | o3 |...........|
-#> |
1| 296.31831 | 1.000 | -1.000 | -0.9520 | -0.9547 |
-#> |.....................| -0.9791 | -0.9725 | -0.9706 |...........|
-#> | U| 296.31831 | 94.44 | -0.2226 | 2.048 | 1.920 |
-#> |.....................| 0.7656 | 1.078 | 1.168 |...........|
-#> | X|
296.31831 | 94.44 | 0.8004 | 7.754 | 1.920 |
-#>
|.....................| 0.7656 | 1.078 | 1.168 |...........|
-#> | G| Gill Diff. | 9.126 | 0.009097 | -0.01177 | -32.33 |
-#>
|.....................| 6.099 | -8.436 | -11.35 |...........|
-#> |
2| 594.25462 | 0.7531 | -1.000 | -0.9517 | -0.07988 |
-#> |.....................| -1.144 | -0.7442 | -0.6636 |...........|
-#> | U| 594.25462 | 71.12 | -0.2229 | 2.049 | 2.760 |
-#> |.....................| 0.6392 | 1.324 | 1.526 |...........|
-#> | X|
594.25462 | 71.12 | 0.8002 | 7.756 | 2.760 |
-#>
|.....................| 0.6392 | 1.324 | 1.526 |...........|
-#> |
3| 298.71818 | 0.9753 | -1.000 | -0.9520 | -0.8672 |
-#> |.....................| -0.9956 | -0.9497 | -0.9399 |...........|
-#> | U| 298.71818 | 92.11 | -0.2226 | 2.048 | 2.004 |
-#> |.....................| 0.7529 | 1.103 | 1.204 |...........|
-#> | X|
298.71818 | 92.11 | 0.8004 | 7.754 | 2.004 |
-#>
|.....................| 0.7529 | 1.103 | 1.204 |...........|
-#> |
4| 295.79061 | 0.9925 | -1.000 | -0.9520 | -0.9282 |
-#> |.....................| -0.9841 | -0.9656 | -0.9613 |...........|
-#> | U| 295.79061 | 93.73 | -0.2226 | 2.048 | 1.945 |
-#> |.....................| 0.7617 | 1.086 | 1.179 |...........|
-#> | X|
295.79061 | 93.73 | 0.8004 | 7.754 | 1.945 |
-#>
|.....................| 0.7617 | 1.086 | 1.179 |...........|
-#> | F| Forward Diff. | -134.6 | -0.07715 | -0.3541 | -29.37 |
-#>
|.....................| 6.863 | -7.752 | -10.79 |...........|
-#> |
5| 294.44078 | 1.001 | -1.000 | -0.9520 | -0.9020 |
-#> |.....................| -0.9892 | -0.9588 | -0.9521 |...........|
-#> | U| 294.44078 | 94.55 | -0.2226 | 2.048 | 1.970 |
-#> |.....................| 0.7578 | 1.093 | 1.189 |...........|
-#> | X|
294.44078 | 94.55 | 0.8004 | 7.754 | 1.970 |
-#>
|.....................| 0.7578 | 1.093 | 1.189 |...........|
-#> | F| Forward Diff. | 30.39 | 0.01643 | 0.02646 | -26.06 |
-#>
|.....................| 5.336 | -7.397 | -10.44 |...........|
-#> |
6| 293.62741 | 0.9971 | -1.000 | -0.9519 | -0.8750 |
-#> |.....................| -0.9945 | -0.9516 | -0.9423 |...........|
-#> | U| 293.62741 | 94.17 | -0.2226 | 2.048 | 1.996 |
-#> |.....................| 0.7538 | 1.101 | 1.201 |...........|
-#> | X|
293.62741 | 94.17 | 0.8004 | 7.754 | 1.996 |
-#>
|.....................| 0.7538 | 1.101 | 1.201 |...........|
-#> |
7| 292.50099 | 0.9961 | -1.000 | -0.9519 | -0.8316 |
-#> |.....................| -1.003 | -0.9401 | -0.9267 |...........|
-#> | U| 292.50099 | 94.07 | -0.2226 | 2.048 | 2.038 |
-#> |.....................| 0.7474 | 1.113 | 1.219 |...........|
-#> | X|
292.50099 | 94.07 | 0.8004 | 7.755 | 2.038 |
-#>
|.....................| 0.7474 | 1.113 | 1.219 |...........|
-#> |
8| 290.76125 | 0.9939 | -1.000 | -0.9518 | -0.7361 |
-#> |.....................| -1.021 | -0.9149 | -0.8925 |...........|
-#> | U| 290.76125 | 93.87 | -0.2226 | 2.048 | 2.130 |
-#> |.....................| 0.7332 | 1.140 | 1.259 |...........|
-#> | X|
290.76125 | 93.87 | 0.8004 | 7.756 | 2.130 |
-#>
|.....................| 0.7332 | 1.140 | 1.259 |...........|
-#> | F| Forward Diff. | -91.20 | -0.08176 | -0.4010 | -10.74 |
-#>
|.....................| 3.658 | -4.872 | -7.770 |...........|
-#> |
9| 293.40175 | 1.024 | -0.9990 | -0.9455 | -0.7012 |
-#> |.....................| -1.060 | -0.8302 | -0.7398 |...........|
-#> | U| 293.40175 | 96.67 | -0.2216 | 2.055 | 2.163 |
-#> |.....................| 0.7035 | 1.231 | 1.437 |...........|
-#> | X|
293.40175 | 96.67 | 0.8012 | 7.804 | 2.163 |
-#>
|.....................| 0.7035 | 1.231 | 1.437 |...........|
-#> |
10| 292.85583 | 1.019 | -0.9997 | -0.9499 | -0.7242 |
-#> |.....................| -1.033 | -0.8898 | -0.8474 |...........|
-#> | U| 292.85583 | 96.21 | -0.2223 | 2.050 | 2.141 |
-#> |.....................| 0.7242 | 1.167 | 1.312 |...........|
-#> | X|
292.85583 | 96.21 | 0.8007 | 7.770 | 2.141 |
-#>
|.....................| 0.7242 | 1.167 | 1.312 |...........|
-#> |
11| 291.55187 | 1.011 | -1.000 | -0.9517 | -0.7341 |
-#> |.....................| -1.022 | -0.9140 | -0.8910 |...........|
-#> | U| 291.55187 | 95.48 | -0.2226 | 2.048 | 2.132 |
-#> |.....................| 0.7326 | 1.141 | 1.261 |...........|
-#> | X|
291.55187 | 95.48 | 0.8004 | 7.756 | 2.132 |
-#>
|.....................| 0.7326 | 1.141 | 1.261 |...........|
-#> |
12| 290.49268 | 0.9997 | -1.000 | -0.9518 | -0.7354 |
-#> |.....................| -1.022 | -0.9146 | -0.8920 |...........|
-#> | U| 290.49268 | 94.41 | -0.2226 | 2.048 | 2.130 |
-#> |.....................| 0.7330 | 1.141 | 1.259 |...........|
-#> | X|
290.49268 | 94.41 | 0.8004 | 7.756 | 2.130 |
-#>
|.....................| 0.7330 | 1.141 | 1.259 |...........|
-#> | F| Forward Diff. | 2.619 | -0.007793 | -0.07320 | -10.57 |
-#>
|.....................| 3.077 | -4.876 | -7.795 |...........|
-#> |
13| 290.41825 | 0.9986 | -1.000 | -0.9517 | -0.7312 |
-#> |.....................| -1.023 | -0.9126 | -0.8889 |...........|
-#> | U| 290.41825 | 94.31 | -0.2226 | 2.048 | 2.134 |
-#> |.....................| 0.7321 | 1.143 | 1.263 |...........|
-#> | X|
290.41825 | 94.31 | 0.8004 | 7.756 | 2.134 |
-#>
|.....................| 0.7321 | 1.143 | 1.263 |...........|
-#> |
14| 290.31205 | 0.9955 | -1.000 | -0.9517 | -0.7186 |
-#> |.....................| -1.027 | -0.9068 | -0.8796 |...........|
-#> | U| 290.31205 | 94.01 | -0.2226 | 2.049 | 2.146 |
-#> |.....................| 0.7292 | 1.149 | 1.274 |...........|
-#> | X|
290.31205 | 94.01 | 0.8004 | 7.757 | 2.146 |
-#>
|.....................| 0.7292 | 1.149 | 1.274 |...........|
-#> | F| Forward Diff. | -64.45 | -0.06351 | -0.3251 | -9.485 |
-#>
|.....................| 2.861 | -4.414 | -7.225 |...........|
-#> |
15| 290.00198 | 1.000 | -0.9999 | -0.9510 | -0.7191 |
-#> |.....................| -1.030 | -0.8965 | -0.8595 |...........|
-#> | U| 290.00198 | 94.46 | -0.2225 | 2.049 | 2.146 |
-#> |.....................| 0.7268 | 1.160 | 1.297 |...........|
-#> | X|
290.00198 | 94.46 | 0.8005 | 7.762 | 2.146 |
-#>
|.....................| 0.7268 | 1.160 | 1.297 |...........|
-#> | F| Forward Diff. | 11.27 | -0.003123 | -0.03408 | -9.156 |
-#>
|.....................| 2.235 | -3.823 | -6.423 |...........|
-#> |
16| 289.83558 | 0.9983 | -0.9998 | -0.9502 | -0.7180 |
-#> |.....................| -1.031 | -0.8872 | -0.8384 |...........|
-#> | U| 289.83558 | 94.28 | -0.2224 | 2.050 | 2.147 |
-#> |.....................| 0.7259 | 1.170 | 1.322 |...........|
-#> | X|
289.83558 | 94.28 | 0.8006 | 7.768 | 2.147 |
-#>
|.....................| 0.7259 | 1.170 | 1.322 |...........|
-#> |
17| 289.63307 | 0.9979 | -0.9995 | -0.9489 | -0.7184 |
-#> |.....................| -1.032 | -0.8720 | -0.8037 |...........|
-#> | U| 289.63307 | 94.24 | -0.2221 | 2.051 | 2.147 |
-#> |.....................| 0.7248 | 1.186 | 1.363 |...........|
-#> | X|
289.63307 | 94.24 | 0.8008 | 7.778 | 2.147 |
-#>
|.....................| 0.7248 | 1.186 | 1.363 |...........|
-#> |
18| 289.44450 | 0.9972 | -0.9991 | -0.9468 | -0.7190 |
-#> |.....................| -1.035 | -0.8473 | -0.7469 |...........|
-#> | U| 289.4445 | 94.18 | -0.2217 | 2.053 | 2.146 |
-#> |.....................| 0.7231 | 1.213 | 1.429 |...........|
-#> | X|
289.4445 | 94.18 | 0.8011 | 7.794 | 2.146 |
-#>
|.....................| 0.7231 | 1.213 | 1.429 |...........|
-#> | F| Forward Diff. | -36.76 | -0.05208 | -0.1861 | -9.057 |
-#>
|.....................| 2.429 | -0.6853 | -1.924 |...........|
-#> |
19| 288.93351 | 0.9984 | -0.9961 | -0.9370 | -0.6306 |
-#> |.....................| -1.080 | -0.9120 | -0.7149 |...........|
-#> | U| 288.93351 | 94.29 | -0.2187 | 2.063 | 2.231 |
-#> |.....................| 0.6885 | 1.143 | 1.466 |...........|
-#> | X|
288.93351 | 94.29 | 0.8035 | 7.871 | 2.231 |
-#>
|.....................| 0.6885 | 1.143 | 1.466 |...........|
-#> | F| Forward Diff. | -14.48 | -0.02726 | 0.2181 | -3.062 |
-#>
|.....................| -0.1976 | -4.306 | -0.8806 |...........|
-#> |
20| 288.85238 | 1.002 | -0.9934 | -0.9444 | -0.5654 |
-#> |.....................| -1.062 | -0.8288 | -0.7747 |...........|
-#> | U| 288.85238 | 94.67 | -0.2160 | 2.056 | 2.293 |
-#> |.....................| 0.7024 | 1.233 | 1.396 |...........|
-#> | X|
288.85238 | 94.67 | 0.8057 | 7.813 | 2.293 |
-#>
|.....................| 0.7024 | 1.233 | 1.396 |...........|
-#> | F| Forward Diff. | 40.49 | 0.1537 | 0.2940 | 0.6524 |
-#>
|.....................| 0.4942 | 0.3489 | -3.099 |...........|
-#> |
21| 289.09335 | 0.9960 | -1.025 | -1.050 | -0.5645 |
-#> |.....................| -1.111 | -0.8117 | -0.7552 |...........|
-#> | U| 289.09335 | 94.07 | -0.2476 | 1.951 | 2.294 |
-#> |.....................| 0.6648 | 1.251 | 1.419 |...........|
-#> | X|
289.09335 | 94.07 | 0.7806 | 7.034 | 2.294 |
-#>
|.....................| 0.6648 | 1.251 | 1.419 |...........|
-#> |
22| 288.97418 | 0.9945 | -1.003 | -0.9755 | -0.5652 |
-#> |.....................| -1.076 | -0.8238 | -0.7685 |...........|
-#> | U| 288.97418 | 93.92 | -0.2254 | 2.025 | 2.294 |
-#> |.....................| 0.6912 | 1.238 | 1.404 |...........|
-#> | X|
288.97418 | 93.92 | 0.7982 | 7.574 | 2.294 |
-#>
|.....................| 0.6912 | 1.238 | 1.404 |...........|
-#> |
23| 288.99640 | 0.9941 | -0.9963 | -0.9538 | -0.5655 |
-#> |.....................| -1.066 | -0.8273 | -0.7723 |...........|
-#> | U| 288.9964 | 93.88 | -0.2189 | 2.046 | 2.293 |
-#> |.....................| 0.6990 | 1.235 | 1.399 |...........|
-#> | X|
288.9964 | 93.88 | 0.8034 | 7.740 | 2.293 |
-#>
|.....................| 0.6990 | 1.235 | 1.399 |...........|
-#> |
24| 288.82158 | 0.9975 | -0.9934 | -0.9445 | -0.5655 |
-#> |.....................| -1.062 | -0.8288 | -0.7743 |...........|
-#> | U| 288.82158 | 94.20 | -0.2160 | 2.056 | 2.293 |
-#> |.....................| 0.7023 | 1.233 | 1.397 |...........|
-#> | X|
288.82158 | 94.20 | 0.8057 | 7.813 | 2.293 |
-#>
|.....................| 0.7023 | 1.233 | 1.397 |...........|
-#> | F| Forward Diff. | -27.98 | 0.07663 | -0.09902 | 0.6250 |
-#>
|.....................| 0.3387 | 0.3777 | -3.049 |...........|
-#> |
25| 288.78525 | 0.9995 | -0.9943 | -0.9465 | -0.5657 |
-#> |.....................| -1.059 | -0.8303 | -0.7716 |...........|
-#> | U| 288.78525 | 94.39 | -0.2169 | 2.054 | 2.293 |
-#> |.....................| 0.7042 | 1.231 | 1.400 |...........|
-#> | X|
288.78525 | 94.39 | 0.8050 | 7.797 | 2.293 |
-#>
|.....................| 0.7042 | 1.231 | 1.400 |...........|
-#> | F| Forward Diff. | -0.7037 | 0.08814 | -0.009566 | 0.5597 |
-#>
|.....................| 0.2999 | 0.2778 | -2.968 |...........|
-#> |
26| 288.77680 | 1.000 | -0.9946 | -0.9467 | -0.5664 |
-#> |.....................| -1.059 | -0.8311 | -0.7670 |...........|
-#> | U| 288.7768 | 94.48 | -0.2172 | 2.053 | 2.292 |
-#> |.....................| 0.7047 | 1.231 | 1.405 |...........|
-#> | X|
288.7768 | 94.48 | 0.8048 | 7.795 | 2.292 |
-#>
|.....................| 0.7047 | 1.231 | 1.405 |...........|
-#> | F| Forward Diff. | 12.46 | 0.09472 | 0.05753 | 0.4960 |
-#>
|.....................| 0.3156 | 0.2411 | -2.796 |...........|
-#> |
27| 288.76499 | 0.9995 | -0.9954 | -0.9482 | -0.5665 |
-#> |.....................| -1.055 | -0.8326 | -0.7642 |...........|
-#> | U| 288.76499 | 94.39 | -0.2180 | 2.052 | 2.292 |
-#> |.....................| 0.7071 | 1.229 | 1.409 |...........|
-#> | X|
288.76499 | 94.39 | 0.8042 | 7.783 | 2.292 |
-#>
|.....................| 0.7071 | 1.229 | 1.409 |...........|
-#> | F| Forward Diff. | -0.8358 | 0.06465 | -0.06858 | 0.5747 |
-#>
|.....................| 0.6430 | 0.1630 | -2.683 |...........|
-#> |
28| 288.75697 | 1.000 | -0.9957 | -0.9484 | -0.5681 |
-#> |.....................| -1.059 | -0.8325 | -0.7609 |...........|
-#> | U| 288.75697 | 94.45 | -0.2183 | 2.052 | 2.291 |
-#> |.....................| 0.7046 | 1.229 | 1.413 |...........|
-#> | X|
288.75697 | 94.45 | 0.8039 | 7.782 | 2.291 |
-#>
|.....................| 0.7046 | 1.229 | 1.413 |...........|
-#> | F| Forward Diff. | 8.673 | 0.06496 | -0.02049 | 0.4885 |
-#>
|.....................| 0.5066 | 0.1747 | -2.560 |...........|
-#> |
29| 288.75050 | 0.9994 | -0.9958 | -0.9480 | -0.5696 |
-#> |.....................| -1.063 | -0.8317 | -0.7600 |...........|
-#> | U| 288.7505 | 94.38 | -0.2184 | 2.052 | 2.289 |
-#> |.....................| 0.7012 | 1.230 | 1.414 |...........|
-#> | X|
288.7505 | 94.38 | 0.8038 | 7.785 | 2.289 |
-#>
|.....................| 0.7012 | 1.230 | 1.414 |...........|
-#> | F| Forward Diff. | -2.463 | 0.04955 | -0.07455 | 0.3979 |
-#>
|.....................| 0.1788 | 0.2263 | -2.511 |...........|
-#> |
30| 288.74110 | 0.9997 | -0.9954 | -0.9459 | -0.5705 |
-#> |.....................| -1.061 | -0.8331 | -0.7562 |...........|
-#> | U| 288.7411 | 94.41 | -0.2180 | 2.054 | 2.289 |
-#> |.....................| 0.7025 | 1.228 | 1.418 |...........|
-#> | X|
288.7411 | 94.41 | 0.8041 | 7.801 | 2.289 |
-#>
|.....................| 0.7025 | 1.228 | 1.418 |...........|
-#> |
31| 288.72064 | 0.9993 | -0.9939 | -0.9392 | -0.5730 |
-#> |.....................| -1.056 | -0.8374 | -0.7455 |...........|
-#> | U| 288.72064 | 94.37 | -0.2166 | 2.061 | 2.286 |
-#> |.....................| 0.7068 | 1.224 | 1.431 |...........|
-#> | X|
288.72064 | 94.37 | 0.8053 | 7.854 | 2.286 |
-#>
|.....................| 0.7068 | 1.224 | 1.431 |...........|
-#> |
32| 288.70690 | 0.9989 | -0.9915 | -0.9277 | -0.5774 |
-#> |.....................| -1.046 | -0.8449 | -0.7267 |...........|
-#> | U| 288.7069 | 94.33 | -0.2141 | 2.072 | 2.282 |
-#> |.....................| 0.7141 | 1.216 | 1.453 |...........|
-#> | X|
288.7069 | 94.33 | 0.8073 | 7.944 | 2.282 |
-#>
|.....................| 0.7141 | 1.216 | 1.453 |...........|
-#> | F| Forward Diff. | -8.246 | 0.08782 | 0.6230 | -0.2261 |
-#>
|.....................| 0.9054 | -0.5290 | -1.268 |...........|
-#> |
33| 288.68146 | 1.000 | -0.9932 | -0.9567 | -0.5899 |
-#> |.....................| -1.067 | -0.8479 | -0.7019 |...........|
-#> | U| 288.68146 | 94.46 | -0.2158 | 2.043 | 2.270 |
-#> |.....................| 0.6982 | 1.212 | 1.481 |...........|
-#> | X|
288.68146 | 94.46 | 0.8059 | 7.717 | 2.270 |
-#>
|.....................| 0.6982 | 1.212 | 1.481 |...........|
-#> | F| Forward Diff. | 8.603 | 0.1068 | -0.4021 | -0.6499 |
-#>
|.....................| 0.1745 | -0.5873 | -0.4459 |...........|
-#> |
34| 288.70236 | 1.001 | -1.018 | -0.9264 | -0.5930 |
-#> |.....................| -1.088 | -0.8392 | -0.6985 |...........|
-#> | U| 288.70236 | 94.50 | -0.2403 | 2.074 | 2.267 |
-#> |.....................| 0.6822 | 1.222 | 1.485 |...........|
-#> | X|
288.70236 | 94.50 | 0.7864 | 7.955 | 2.267 |
-#>
|.....................| 0.6822 | 1.222 | 1.485 |...........|
-#> |
35| 288.67546 | 0.9997 | -0.9992 | -0.9493 | -0.5906 |
-#> |.....................| -1.072 | -0.8457 | -0.7010 |...........|
-#> | U| 288.67546 | 94.41 | -0.2218 | 2.051 | 2.269 |
-#> |.....................| 0.6943 | 1.215 | 1.482 |...........|
-#> | X|
288.67546 | 94.41 | 0.8011 | 7.775 | 2.269 |
-#>
|.....................| 0.6943 | 1.215 | 1.482 |...........|
-#> | F| Forward Diff. | 1.309 | -0.03968 | -0.1448 | -0.6596 |
-#>
|.....................| 0.05856 | -0.4617 | -0.3123 |...........|
-#> |
36| 288.67323 | 0.9995 | -0.9891 | -0.9462 | -0.5890 |
-#> |.....................| -1.074 | -0.8436 | -0.6999 |...........|
-#> | U| 288.67323 | 94.40 | -0.2117 | 2.054 | 2.271 |
-#> |.....................| 0.6929 | 1.217 | 1.484 |...........|
-#> | X|
288.67323 | 94.40 | 0.8092 | 7.800 | 2.271 |
-#>
|.....................| 0.6929 | 1.217 | 1.484 |...........|
-#> | F| Forward Diff. | -0.3529 | 0.1695 | -0.04594 | -0.6688 |
-#>
|.....................| -0.2932 | -0.3576 | -0.2566 |...........|
-#> |
37| 288.67323 | 0.9995 | -0.9891 | -0.9462 | -0.5890 |
-#> |.....................| -1.074 | -0.8436 | -0.6999 |...........|
-#> | U| 288.67323 | 94.40 | -0.2117 | 2.054 | 2.271 |
-#> |.....................| 0.6929 | 1.217 | 1.484 |...........|
-#> | X|
288.67323 | 94.40 | 0.8092 | 7.800 | 2.271 |
-#>
|.....................| 0.6929 | 1.217 | 1.484 |...........|
-#> calculating covariance matrix
+
f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC",
], est
= "saem",
+ control
= saemControl(print
= 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.2375 -1.6690 -4.0126 0.0336 3.3441 0.9789 2.1220 0.5342 18.1447
-#> 2: 92.9778 -1.6369 -3.9297 0.0067 3.1769 1.2515 2.0460 0.5166 11.1022
-#> 3: 92.9382 -1.6747 -3.9496 -0.0050 3.0181 1.1889 1.9437 0.4908 9.5980
-#> 4: 93.4481 -1.8083 -3.9734 -0.0250 2.8672 1.1295 1.8797 0.4662 8.6240
-#> 5: 93.4584 -1.8288 -4.0221 0.0414 2.7238 1.0730 1.8467 0.5161 8.1404
-#> 6: 93.7533 -1.8675 -4.0215 0.0158 2.5876 1.0194 1.8017 0.4911 7.5848
-#> 7: 93.6006 -1.8542 -4.0241 -0.0026 2.4582 0.9684 1.7860 0.4916 7.0796
-#> 8: 93.6918 -1.8416 -3.9940 0.0121 2.3353 0.9200 1.7061 0.4681 6.9985
-#> 9: 93.4789 -1.8738 -3.9845 0.0318 3.1307 0.8740 1.7845 0.4553 6.8335
-#> 10: 93.6048 -1.8723 -4.0154 0.0112 3.1962 0.8303 1.7434 0.4325 7.0681
-#> 11: 93.5135 -1.8675 -3.9905 0.0295 3.2177 0.7888 1.6910 0.4619 6.9572
-#> 12: 93.4407 -1.8790 -3.9877 0.0509 3.4194 0.7493 1.6324 0.5060 6.5755
-#> 13: 93.5033 -1.9250 -4.0416 0.0734 3.2485 0.7295 1.7369 0.4807 6.3881
-#> 14: 93.4276 -1.9082 -4.0516 0.0558 3.0860 0.7281 1.7241 0.4567 5.9840
-#> 15: 93.3041 -1.9256 -4.0718 0.0854 3.4389 0.7293 1.7446 0.4524 5.8195
-#> 16: 93.2979 -1.9297 -4.0624 0.0730 3.2670 0.7239 1.7476 0.4298 5.7629
-#> 17: 93.3522 -1.9570 -4.0876 0.1304 3.3053 0.7020 1.7402 0.4083 5.6926
-#> 18: 93.3500 -1.9652 -4.0816 0.1350 3.1400 0.7130 1.7217 0.3879 5.5714
-#> 19: 93.3822 -1.9519 -4.0961 0.1322 2.9830 0.7087 1.7228 0.3745 5.4176
-#> 20: 93.2823 -1.9490 -4.0841 0.1238 2.8339 0.6988 1.7659 0.3753 5.5279
-#> 21: 93.5951 -1.9298 -4.0874 0.1345 2.6922 0.6665 1.7724 0.3645 5.4414
-#> 22: 93.5052 -1.9469 -4.0739 0.1260 3.1244 0.6776 1.7629 0.3618 5.5395
-#> 23: 93.4734 -1.9952 -4.0909 0.1472 3.0340 0.7225 1.8104 0.3437 5.5072
-#> 24: 93.8816 -1.9639 -4.0914 0.1511 2.8824 0.7215 1.8586 0.3324 5.6009
-#> 25: 93.5874 -1.9750 -4.1026 0.1296 2.7383 0.7178 1.8209 0.3680 5.6274
-#> 26: 93.4057 -1.9316 -4.0922 0.1224 3.8103 0.7331 1.7796 0.3639 5.6861
-#> 27: 93.5013 -1.9188 -4.0698 0.0758 3.7127 0.7670 1.8750 0.3457 5.6624
-#> 28: 93.5703 -1.9523 -4.0758 0.0731 4.6390 0.7489 1.8583 0.3445 5.8077
-#> 29: 93.4694 -1.9559 -4.0566 0.0444 5.1290 0.8062 1.9344 0.3273 5.8688
-#> 30: 93.2290 -1.9824 -4.0475 0.0674 4.8726 0.8702 2.0343 0.3109 5.7579
-#> 31: 93.8652 -1.9771 -4.0510 0.0679 4.6289 0.8565 2.0529 0.2954 5.5526
-#> 32: 93.5854 -1.9573 -4.0510 0.0643 5.1320 0.8417 2.0138 0.2806 5.4199
-#> 33: 93.9870 -1.9503 -4.0513 0.0542 4.8754 0.8412 2.0433 0.2666 5.6945
-#> 34: 93.6884 -1.9172 -4.0633 0.0556 4.6317 0.8847 2.0861 0.2702 5.2687
-#> 35: 94.0375 -1.9365 -4.0576 0.0753 5.2320 0.8404 2.0791 0.2582 5.2760
-#> 36: 94.1588 -1.9423 -4.0499 0.0792 4.9704 0.8221 2.1145 0.2669 5.2050
-#> 37: 93.8626 -1.9356 -4.0538 0.0591 5.2723 0.8360 2.1407 0.2536 5.3218
-#> 38: 93.7237 -1.9357 -4.0611 0.0543 5.0087 0.8361 2.0788 0.2710 5.2866
-#> 39: 93.6513 -1.9327 -4.0408 0.0712 4.7582 0.8408 2.0051 0.2899 5.4693
-#> 40: 93.4619 -1.9634 -4.0360 0.1232 4.5203 0.8317 2.0367 0.3288 5.4324
-#> 41: 93.4809 -1.9601 -4.0351 0.1261 4.2943 0.8424 2.0081 0.3306 5.4573
-#> 42: 93.5851 -1.9745 -4.0428 0.1250 4.9744 0.8003 1.9818 0.3141 5.5168
-#> 43: 93.7820 -1.9597 -4.0401 0.1305 5.9118 0.7603 2.1332 0.2984 5.4899
-#> 44: 93.7419 -1.9509 -4.0495 0.1345 5.6162 0.7743 2.0459 0.2998 5.5344
-#> 45: 93.6967 -1.9366 -4.0522 0.1215 5.3354 0.7968 2.0566 0.2848 5.7738
-#> 46: 93.3665 -1.9553 -4.0018 0.0951 5.0686 0.7583 2.1124 0.2706 5.3850
-#> 47: 93.2974 -1.9332 -4.0091 0.0869 5.2792 0.8149 2.1009 0.2597 5.6743
-#> 48: 93.3967 -1.9540 -4.0218 0.0623 5.0152 0.8006 2.1538 0.2467 5.5889
-#> 49: 93.1652 -1.9724 -4.0350 0.0506 4.7645 0.8055 2.1445 0.2344 5.3586
-#> 50: 93.1464 -1.9377 -4.0185 0.0591 5.3658 0.8149 2.1523 0.2226 5.2483
-#> 51: 93.5217 -1.9246 -4.0272 0.0423 5.8579 0.8368 2.1596 0.2115 5.2746
-#> 52: 93.5512 -1.9257 -4.0204 0.0307 7.2345 0.8463 2.1903 0.2065 5.2405
-#> 53: 93.5400 -1.9428 -4.0300 0.0572 6.8728 0.8268 2.0807 0.2139 5.4127
-#> 54: 93.9868 -1.9502 -4.0129 0.0282 9.6651 0.8468 2.0823 0.2032 5.0396
-#> 55: 94.0505 -1.9393 -4.0073 0.0390 10.0994 0.8375 2.1018 0.2016 4.9147
-#> 56: 93.8010 -1.9493 -4.0026 0.0415 10.1741 0.8816 2.1117 0.2207 5.0723
-#> 57: 93.7596 -1.9762 -4.0154 0.0651 9.6654 0.8952 2.1662 0.2096 5.2311
-#> 58: 94.3399 -1.9353 -4.0095 0.0446 9.1821 0.9498 2.2103 0.1991 5.1009
-#> 59: 94.4036 -1.9283 -4.0279 0.0475 8.7230 0.9480 2.3209 0.1892 4.9930
-#> 60: 94.6395 -1.9260 -4.0348 0.0457 8.8651 0.9006 2.2565 0.1797 5.1751
-#> 61: 94.6499 -1.9291 -4.0216 0.0297 8.4218 0.9206 2.2220 0.1843 5.1124
-#> 62: 94.3847 -1.9010 -4.0300 0.0257 9.0591 0.9331 2.2795 0.1816 5.0834
-#> 63: 94.5510 -1.9120 -4.0116 0.0179 8.6061 0.9256 2.1791 0.1736 5.1513
-#> 64: 94.2510 -1.9213 -4.0184 0.0204 8.1758 0.9124 2.2131 0.1682 5.0698
-#> 65: 94.1173 -1.9044 -4.0279 0.0286 8.6773 0.9211 2.2202 0.1598 5.1120
-#> 66: 94.2093 -1.9098 -4.0206 0.0160 8.2435 0.9230 2.2475 0.1750 5.0175
-#> 67: 94.2814 -1.9339 -4.0041 0.0146 7.8313 0.9377 2.2350 0.1709 5.1478
-#> 68: 94.3001 -1.9079 -4.0127 -0.0103 7.4397 0.9163 2.2245 0.1640 5.2529
-#> 69: 94.3820 -1.9167 -4.0176 0.0296 7.0678 0.8704 2.2236 0.1888 5.2574
-#> 70: 94.2691 -1.9037 -4.0156 0.0388 6.7144 0.8601 2.1833 0.2128 5.0230
-#> 71: 94.3827 -1.9183 -4.0056 0.0485 6.3786 0.8491 2.2147 0.2345 5.1212
-#> 72: 94.3104 -1.9291 -4.0099 0.0330 6.0597 0.9007 2.2316 0.2255 5.3748
-#> 73: 94.1778 -1.9238 -4.0054 0.0222 5.7567 0.9479 2.2969 0.2142 5.2827
-#> 74: 94.1022 -1.9149 -4.0017 0.0497 5.4689 0.9305 2.3058 0.2035 5.3117
-#> 75: 94.2343 -1.9045 -4.0141 0.0189 5.1954 0.9141 2.3227 0.1933 5.1047
-#> 76: 94.0905 -1.9019 -4.0166 0.0170 5.5411 0.8978 2.3315 0.1836 5.1233
-#> 77: 94.2772 -1.9117 -4.0053 0.0584 5.2641 0.9238 2.3678 0.1866 4.9803
-#> 78: 94.7235 -1.9141 -4.0464 0.0758 5.0735 0.9308 2.3720 0.2062 5.0544
-#> 79: 94.4674 -1.9287 -4.0494 0.0724 5.7355 0.9063 2.3680 0.1959 5.0910
-#> 80: 93.9895 -1.9271 -4.0456 0.0366 7.2150 0.8857 2.4000 0.1861 5.0612
-#> 81: 94.3190 -1.9358 -4.0402 0.0506 7.5591 0.8891 2.3317 0.1814 4.8617
-#> 82: 94.1898 -1.9126 -4.0552 0.0595 7.6462 0.9157 2.3848 0.1854 4.7335
-#> 83: 94.2044 -1.9145 -4.0359 0.0295 7.8610 0.9451 2.4305 0.1871 4.9258
-#> 84: 93.8197 -1.9058 -3.9879 -0.0409 10.4218 0.9604 2.3848 0.2177 5.0619
-#> 85: 94.0219 -1.8957 -3.9753 -0.0441 9.9007 0.9637 2.4476 0.2219 5.0532
-#> 86: 94.0737 -1.8889 -3.9753 -0.0220 9.4056 0.9675 2.4476 0.2284 5.2694
-#> 87: 93.8548 -1.8755 -3.9707 -0.0024 8.9354 1.0066 2.4895 0.2340 5.4019
-#> 88: 93.7578 -1.9046 -3.9804 -0.0042 8.4886 0.9656 2.5006 0.2271 5.3724
-#> 89: 93.6848 -1.8936 -3.9689 -0.0396 10.6813 0.9805 2.4561 0.2254 5.2615
-#> 90: 93.3617 -1.9167 -3.9801 -0.0221 10.1472 1.0147 2.3589 0.2141 5.4193
-#> 91: 93.7419 -1.8964 -3.9888 -0.0363 9.6398 1.0077 2.3748 0.2066 5.3463
-#> 92: 93.8635 -1.8994 -3.9783 -0.0625 9.1578 1.0028 2.3282 0.2239 5.3026
-#> 93: 94.0864 -1.8648 -3.9426 -0.0813 8.8693 1.0348 2.3654 0.2127 5.2637
-#> 94: 93.9789 -1.8949 -3.9840 -0.0549 10.0871 1.0752 2.4551 0.2021 5.4225
-#> 95: 93.9008 -1.9141 -4.0080 -0.0644 9.8584 1.1599 2.4184 0.1920 5.2179
-#> 96: 93.6926 -2.0270 -3.8911 -0.0777 10.3968 1.1019 3.0518 0.1824 5.3163
-#> 97: 93.2478 -2.0074 -3.9034 -0.0427 10.7200 1.0468 2.9960 0.1732 5.5172
-#> 98: 93.4556 -2.0118 -3.9034 -0.0294 10.1840 1.0007 2.9960 0.1646 5.5887
-#> 99: 93.7548 -2.0076 -3.8894 -0.0157 9.7519 0.9507 3.0357 0.1569 5.7139
-#> 100: 93.8962 -2.0112 -3.8887 -0.0406 9.2643 0.9048 3.0369 0.1491 5.6145
-#> 101: 94.0889 -2.0221 -3.8612 -0.0145 8.8011 0.8728 3.1466 0.1499 5.4224
-#> 102: 94.5428 -2.0206 -3.8489 0.0115 8.3611 0.8292 3.1577 0.1473 5.6634
-#> 103: 94.4882 -2.0447 -3.8594 0.0514 7.9430 0.8202 3.1812 0.1562 5.5136
-#> 104: 94.3185 -2.0389 -3.8584 0.0258 8.3364 0.8346 3.1801 0.1484 5.3612
-#> 105: 94.2858 -2.0345 -3.8738 -0.0001 10.6008 0.8415 3.2251 0.1410 5.3359
-#> 106: 94.1264 -2.0415 -3.8756 0.0411 10.0707 0.8554 3.2182 0.1658 5.2280
-#> 107: 93.9801 -2.0574 -3.8674 0.0403 10.0269 0.8807 3.2628 0.1744 5.0299
-#> 108: 93.6911 -2.0295 -3.8693 0.0355 9.5255 0.8683 3.2708 0.1803 5.1880
-#> 109: 94.0646 -2.0260 -3.8806 0.0506 9.0493 0.8729 3.3140 0.1759 5.1927
-#> 110: 94.4591 -2.0378 -3.8962 0.0360 8.5968 0.8890 3.3076 0.1675 4.8961
-#> 111: 94.3748 -2.0319 -3.9053 0.0397 8.1670 0.8995 3.3254 0.1591 4.8066
-#> 112: 94.2370 -2.0338 -3.9017 0.0603 7.7586 0.8545 3.2484 0.1512 4.8856
-#> 113: 94.1242 -2.0237 -3.8954 0.0795 7.3707 0.8980 3.2127 0.1530 5.1859
-#> 114: 94.1452 -2.0298 -3.9197 0.0530 7.0021 0.8771 3.0744 0.1628 5.1303
-#> 115: 94.1403 -2.0410 -3.9093 0.0476 6.9173 0.9383 3.0223 0.1621 5.2563
-#> 116: 94.1612 -2.0424 -3.9063 0.0593 7.6367 0.8914 3.0420 0.1856 5.1566
-#> 117: 94.2018 -2.0488 -3.9041 0.0539 7.2549 0.8549 3.0204 0.1796 5.2119
-#> 118: 94.1315 -2.0579 -3.9139 0.0564 6.8922 0.8121 3.0180 0.1948 5.0302
-#> 119: 93.7398 -2.0747 -3.9202 0.0570 6.7510 0.7838 3.0084 0.1906 5.0863
-#> 120: 93.5945 -2.0511 -3.9388 0.0534 6.4134 0.7885 3.0100 0.2128 5.0597
-#> 121: 93.9845 -2.0613 -3.9338 0.0568 6.0928 0.7793 2.9944 0.2022 5.3179
-#> 122: 93.7779 -2.0831 -3.9338 0.0630 5.7881 0.7778 2.9944 0.1921 5.2399
-#> 123: 93.9128 -2.0623 -3.9135 0.0493 5.4987 0.8329 2.9729 0.1825 5.0752
-#> 124: 93.5190 -2.0804 -3.9315 0.0538 5.2238 0.8581 3.0220 0.1733 4.9713
-#> 125: 93.7427 -2.0649 -3.9309 0.0499 4.9626 0.8431 3.0260 0.1882 5.0718
-#> 126: 9.3540e+01 -2.0238e+00 -3.9006e+00 -6.8989e-05 4.7145e+00 8.3548e-01 2.9498e+00 1.9993e-01 5.2080e+00
-#> 127: 93.4310 -2.0496 -3.8898 -0.0173 4.4788 0.8864 2.9614 0.2302 5.6432
-#> 128: 93.7512 -2.0285 -3.9180 -0.0096 4.2548 0.8653 3.0768 0.2312 5.3906
-#> 129: 93.6908 -2.0718 -3.9113 -0.0194 4.0421 0.9022 3.0506 0.2386 5.3278
-#> 130: 93.5805 -1.9753 -4.0480 0.0065 3.8400 1.0388 2.8980 0.2276 5.2583
-#> 131: 93.8050 -1.9501 -4.0447 0.0040 3.8738 1.0957 2.7531 0.2162 5.3026
-#> 132: 93.6470 -1.9322 -4.0411 0.0048 3.6801 1.0618 2.6155 0.2159 5.2552
-#> 133: 94.2927 -1.9445 -4.0067 -0.0040 5.6903 1.0378 2.5425 0.2094 5.2430
-#> 134: 94.2814 -1.9286 -4.0021 -0.0144 6.9123 1.1316 2.5172 0.1990 5.3877
-#> 135: 94.0440 -1.9285 -4.0415 0.0254 6.5667 1.1416 2.4394 0.1975 5.3248
-#> 136: 94.0122 -1.9256 -4.0542 0.0156 6.6147 1.1511 2.4728 0.1954 5.2109
-#> 137: 93.8613 -1.9095 -4.0629 -0.0007 6.2840 1.1789 2.5078 0.2045 5.2876
-#> 138: 93.7410 -1.9345 -4.0788 -0.0005 6.0718 1.1507 2.5026 0.2086 5.3284
-#> 139: 93.6437 -1.9499 -4.0788 0.0159 5.7682 1.0932 2.5026 0.1982 5.4211
-#> 140: 93.4066 -1.9591 -4.0720 0.0472 6.9432 1.0883 2.4756 0.1947 5.4439
-#> 141: 93.6086 -1.9625 -4.1026 0.0785 7.7204 1.1027 2.3974 0.2084 5.6595
-#> 142: 93.8693 -1.9640 -4.1003 0.0670 10.1206 1.1196 2.2775 0.1980 5.4918
-#> 143: 93.6954 -1.9890 -4.0792 0.0824 9.6146 1.0636 2.3366 0.1881 5.2818
-#> 144: 93.5119 -1.9888 -4.0603 0.0645 9.1339 1.0557 2.3380 0.1787 5.3491
-#> 145: 93.3539 -1.9874 -4.0563 0.0764 8.6772 1.0340 2.3573 0.1697 5.4214
-#> 146: 93.2812 -1.9734 -4.0620 0.0674 8.4698 1.0504 2.3604 0.1641 5.5968
-#> 147: 93.8919 -1.9657 -4.0863 0.0596 8.0463 1.0288 2.4569 0.1668 5.3476
-#> 148: 93.7841 -1.9719 -4.0688 0.0880 9.4571 1.0719 2.4020 0.1692 5.1664
-#> 149: 93.6361 -1.9912 -4.0523 0.0895 8.9842 1.0183 2.5236 0.1671 5.5060
-#> 150: 93.6402 -1.9940 -4.0365 0.0730 9.1100 0.9674 2.3974 0.1669 5.5402
-#> 151: 93.4283 -1.9861 -4.0594 0.0805 8.6545 0.9567 2.4304 0.1652 5.3571
-#> 152: 93.7431 -1.9444 -4.0833 0.0612 9.2738 0.9789 2.3602 0.1571 5.0632
-#> 153: 93.7239 -1.9307 -4.0780 0.0780 8.9915 0.9995 2.3398 0.1600 5.1077
-#> 154: 94.0115 -1.9655 -4.0978 0.0859 9.0507 0.9894 2.3313 0.1628 5.2272
-#> 155: 94.3207 -1.9792 -4.0905 0.1114 8.5756 0.9988 2.3790 0.1873 5.0916
-#> 156: 94.3160 -1.9811 -4.0894 0.0906 5.0717 0.9968 2.3662 0.2003 4.9973
-#> 157: 94.3042 -1.9641 -4.1031 0.0966 5.1875 0.9911 2.3908 0.1943 4.9993
-#> 158: 94.0102 -1.9635 -4.1047 0.1003 5.2398 0.9834 2.3905 0.1809 5.2765
-#> 159: 94.5686 -2.0012 -4.1459 0.1212 6.8800 1.0317 2.5969 0.1215 5.3943
-#> 160: 94.2433 -1.9673 -4.1420 0.1165 8.0930 1.0286 2.5827 0.1092 5.2904
-#> 161: 94.1327 -1.9644 -4.1595 0.1196 9.5810 1.0786 2.7063 0.1123 5.1723
-#> 162: 94.0779 -1.9525 -4.1608 0.1103 6.6456 1.0562 2.7111 0.1277 5.0224
-#> 163: 94.0995 -1.9687 -4.1910 0.1320 8.2582 1.0701 2.8394 0.1232 5.1593
-#> 164: 94.4575 -1.9800 -4.1936 0.1208 6.4860 1.1603 2.8332 0.1254 5.1325
-#> 165: 94.3298 -1.9968 -4.1963 0.1506 5.7592 1.1484 2.9143 0.1196 5.3059
-#> 166: 94.2531 -1.9977 -4.1748 0.1566 5.3810 1.1262 2.8044 0.1142 5.2569
-#> 167: 94.4593 -1.9985 -4.1758 0.1435 7.0082 1.1247 2.8542 0.1125 5.4332
-#> 168: 94.0868 -2.0117 -4.2259 0.1345 7.5364 1.1395 3.0314 0.1137 5.2790
-#> 169: 93.7927 -2.0072 -4.2177 0.1276 6.7023 1.1292 3.0535 0.1135 5.1357
-#> 170: 93.8094 -2.0309 -4.2244 0.1298 6.7343 1.0975 3.2542 0.1065 5.2372
-#> 171: 93.7263 -2.0349 -4.2115 0.1204 8.2555 1.0626 3.2292 0.1020 5.4467
-#> 172: 93.3380 -2.0022 -4.2262 0.1193 6.6891 1.0822 3.2762 0.0989 5.3641
-#> 173: 93.5334 -2.0224 -4.2488 0.1145 6.0685 1.0328 3.4694 0.0978 5.4780
-#> 174: 93.1805 -2.0207 -4.2344 0.1025 6.1648 1.0612 3.2079 0.0976 5.2570
-#> 175: 93.3423 -2.0255 -4.1644 0.1070 5.9418 1.0701 2.8555 0.1059 5.3415
-#> 176: 93.3387 -2.0192 -4.1473 0.0786 4.7649 1.0508 2.9102 0.1101 5.3381
-#> 177: 93.4640 -2.0177 -4.1504 0.0709 4.5672 1.0590 2.9447 0.1103 5.3245
-#> 178: 93.4930 -2.0147 -4.1568 0.0777 4.5325 1.1063 2.7902 0.1247 5.2036
-#> 179: 93.7455 -2.0101 -4.1580 0.0823 4.2094 1.1020 2.8075 0.1246 5.1184
-#> 180: 93.4838 -1.9989 -4.1631 0.0868 3.6999 1.0782 2.8790 0.1280 5.2677
-#> 181: 93.5207 -1.9975 -4.1926 0.1013 4.5693 1.0706 2.9216 0.1375 5.3783
-#> 182: 93.6695 -2.0251 -4.1717 0.0809 3.8373 1.0341 2.9954 0.1328 5.3774
-#> 183: 93.7238 -2.0095 -4.1222 0.0861 3.8354 1.0138 2.7536 0.1512 5.2600
-#> 184: 93.7106 -2.0032 -4.1244 0.0853 4.1968 1.0250 2.6849 0.1590 5.1996
-#> 185: 93.2862 -2.0028 -4.1628 0.0743 5.4347 1.0373 2.6528 0.1640 5.3269
-#> 186: 93.5567 -2.0040 -4.1438 0.0807 6.5150 1.0562 2.6486 0.1589 5.4158
-#> 187: 93.7894 -2.0023 -4.1137 0.1288 5.1401 1.0207 2.5217 0.1745 5.6484
-#> 188: 93.4911 -1.8872 -4.2405 0.1324 4.3165 0.8176 2.2483 0.1870 5.5214
-#> 189: 93.9184 -1.8982 -4.2936 0.1606 3.7995 0.8383 2.2555 0.1766 5.6320
-#> 190: 93.7487 -1.8878 -4.2872 0.1651 3.6764 0.8860 2.2088 0.1748 5.4829
-#> 191: 93.8940 -1.8715 -4.3244 0.1650 2.8119 0.9024 2.1141 0.1903 5.7768
-#> 192: 93.9378 -1.9105 -4.3010 0.1954 2.5239 0.8232 2.1331 0.1831 5.8507
-#> 193: 94.5609 -1.8766 -4.3303 0.2042 3.9595 0.8413 2.0662 0.2095 5.6119
-#> 194: 94.7465 -1.9036 -4.3363 0.2112 5.0784 0.8176 2.1071 0.2149 5.6051
-#> 195: 94.4761 -1.8852 -4.3375 0.2021 4.7026 0.7615 2.0556 0.2333 5.3997
-#> 196: 93.7678 -1.9037 -4.3676 0.2273 5.6976 0.7824 2.1487 0.2478 5.2531
-#> 197: 94.0788 -1.9208 -4.3670 0.2203 3.8352 0.7644 2.0893 0.2354 5.2196
-#> 198: 94.3424 -1.8825 -4.3288 0.2075 4.9447 0.7304 1.9525 0.2502 5.1387
-#> 199: 94.0613 -1.9911 -4.1676 0.2379 3.6248 0.6126 2.8184 0.2801 5.3421
-#> 200: 94.4814 -2.0045 -4.1782 0.2245 3.5637 0.6427 2.7132 0.3014 5.3984
-#> 201: 94.3903 -1.9973 -4.1773 0.2165 3.4686 0.6525 2.7040 0.2901 5.4178
-#> 202: 94.1840 -1.9928 -4.1742 0.2117 3.6920 0.6576 2.7046 0.2870 5.3743
-#> 203: 94.1832 -1.9865 -4.1670 0.2025 3.8180 0.6618 2.7097 0.2758 5.3389
-#> 204: 94.1550 -1.9832 -4.1631 0.1955 3.9449 0.6613 2.6998 0.2691 5.2948
-#> 205: 94.1853 -1.9824 -4.1602 0.1948 4.1753 0.6598 2.6909 0.2695 5.2556
-#> 206: 94.1775 -1.9800 -4.1564 0.1918 4.1962 0.6581 2.6778 0.2678 5.2316
-#> 207: 94.1754 -1.9736 -4.1532 0.1864 4.2107 0.6580 2.6645 0.2694 5.2553
-#> 208: 94.1591 -1.9695 -4.1498 0.1811 4.2621 0.6596 2.6537 0.2712 5.2543
-#> 209: 94.1225 -1.9675 -4.1454 0.1744 4.1977 0.6651 2.6519 0.2687 5.3075
-#> 210: 94.1047 -1.9628 -4.1424 0.1666 4.1981 0.6663 2.6570 0.2717 5.3160
-#> 211: 94.1161 -1.9587 -4.1398 0.1600 4.1858 0.6674 2.6614 0.2728 5.3307
-#> 212: 94.0976 -1.9551 -4.1379 0.1529 4.2002 0.6693 2.6737 0.2709 5.3288
-#> 213: 94.0845 -1.9511 -4.1365 0.1449 4.1381 0.6710 2.6727 0.2680 5.3322
-#> 214: 94.0582 -1.9493 -4.1351 0.1394 4.0630 0.6733 2.6729 0.2663 5.3504
-#> 215: 94.0449 -1.9493 -4.1338 0.1340 3.9607 0.6733 2.6719 0.2641 5.3681
-#> 216: 94.0030 -1.9496 -4.1321 0.1299 4.0200 0.6742 2.6727 0.2622 5.3619
-#> 217: 93.9560 -1.9514 -4.1315 0.1267 4.0642 0.6778 2.6764 0.2612 5.3584
-#> 218: 93.9485 -1.9520 -4.1297 0.1235 4.1822 0.6795 2.6745 0.2599 5.3471
-#> 219: 93.9650 -1.9523 -4.1289 0.1211 4.3244 0.6807 2.6851 0.2591 5.3531
-#> 220: 93.9961 -1.9519 -4.1284 0.1193 4.4276 0.6837 2.6936 0.2577 5.3528
-#> 221: 94.0080 -1.9517 -4.1275 0.1183 4.5303 0.6866 2.6979 0.2578 5.3538
-#> 222: 94.0143 -1.9505 -4.1272 0.1159 4.5882 0.6887 2.7039 0.2570 5.3489
-#> 223: 94.0189 -1.9491 -4.1269 0.1138 4.5674 0.6910 2.7092 0.2562 5.3424
-#> 224: 94.0136 -1.9464 -4.1270 0.1126 4.5582 0.6923 2.7161 0.2548 5.3421
-#> 225: 94.0118 -1.9444 -4.1276 0.1112 4.6000 0.6929 2.7269 0.2533 5.3525
-#> 226: 93.9884 -1.9428 -4.1260 0.1099 4.6720 0.6935 2.7428 0.2530 5.3427
-#> 227: 93.9657 -1.9416 -4.1247 0.1097 4.7197 0.6937 2.7581 0.2529 5.3455
-#> 228: 93.9586 -1.9410 -4.1234 0.1105 4.7731 0.6945 2.7801 0.2528 5.3408
-#> 229: 93.9574 -1.9409 -4.1215 0.1102 4.7898 0.6963 2.7970 0.2518 5.3366
-#> 230: 93.9495 -1.9410 -4.1201 0.1096 4.7966 0.6982 2.8117 0.2505 5.3301
-#> 231: 93.9378 -1.9416 -4.1193 0.1093 4.7947 0.6993 2.8274 0.2492 5.3270
-#> 232: 93.9362 -1.9421 -4.1184 0.1086 4.8132 0.7011 2.8411 0.2477 5.3191
-#> 233: 93.9412 -1.9424 -4.1167 0.1074 4.8188 0.7028 2.8514 0.2459 5.3134
-#> 234: 93.9436 -1.9424 -4.1152 0.1061 4.7865 0.7040 2.8618 0.2440 5.3153
-#> 235: 93.9413 -1.9425 -4.1134 0.1051 4.8017 0.7062 2.8679 0.2426 5.3137
-#> 236: 93.9480 -1.9423 -4.1119 0.1033 4.8537 0.7085 2.8730 0.2416 5.3089
-#> 237: 93.9560 -1.9408 -4.1105 0.1020 4.9091 0.7098 2.8777 0.2411 5.2970
-#> 238: 93.9610 -1.9393 -4.1091 0.1003 4.9394 0.7113 2.8824 0.2409 5.2902
-#> 239: 93.9634 -1.9378 -4.1080 0.0993 4.9304 0.7121 2.8875 0.2407 5.2868
-#> 240: 93.9727 -1.9360 -4.1063 0.0980 4.9651 0.7128 2.8918 0.2404 5.2825
-#> 241: 93.9736 -1.9348 -4.1045 0.0969 5.0080 0.7139 2.8917 0.2395 5.2751
-#> 242: 93.9779 -1.9334 -4.1030 0.0959 5.0856 0.7150 2.8923 0.2389 5.2656
-#> 243: 93.9807 -1.9322 -4.1015 0.0953 5.1490 0.7158 2.8929 0.2385 5.2560
-#> 244: 93.9858 -1.9317 -4.0998 0.0942 5.2172 0.7171 2.8922 0.2380 5.2514
-#> 245: 93.9798 -1.9309 -4.0984 0.0920 5.2903 0.7172 2.8892 0.2383 5.2502
-#> 246: 93.9782 -1.9296 -4.0971 0.0903 5.3132 0.7180 2.8866 0.2384 5.2482
-#> 247: 93.9809 -1.9290 -4.0958 0.0886 5.3342 0.7188 2.8839 0.2386 5.2466
-#> 248: 93.9731 -1.9281 -4.0944 0.0873 5.3438 0.7187 2.8812 0.2393 5.2480
-#> 249: 93.9594 -1.9273 -4.0932 0.0852 5.3449 0.7181 2.8781 0.2401 5.2489
-#> 250: 93.9508 -1.9261 -4.0919 0.0835 5.3194 0.7173 2.8752 0.2406 5.2495
-#> 251: 93.9421 -1.9248 -4.0903 0.0812 5.3051 0.7180 2.8714 0.2410 5.2480
-#> 252: 93.9291 -1.9240 -4.0888 0.0793 5.3122 0.7175 2.8681 0.2415 5.2447
-#> 253: 93.9233 -1.9232 -4.0876 0.0777 5.3289 0.7170 2.8636 0.2420 5.2423
-#> 254: 93.9189 -1.9217 -4.0863 0.0760 5.3708 0.7165 2.8593 0.2425 5.2395
-#> 255: 93.9130 -1.9205 -4.0850 0.0743 5.4093 0.7157 2.8548 0.2428 5.2393
-#> 256: 93.9031 -1.9195 -4.0837 0.0731 5.4400 0.7153 2.8501 0.2432 5.2417
-#> 257: 93.9079 -1.9183 -4.0821 0.0720 5.4612 0.7138 2.8454 0.2434 5.2469
-#> 258: 93.9117 -1.9173 -4.0807 0.0711 5.4979 0.7126 2.8412 0.2439 5.2491
-#> 259: 93.9199 -1.9164 -4.0797 0.0708 5.5145 0.7107 2.8364 0.2449 5.2481
-#> 260: 93.9300 -1.9150 -4.0782 0.0699 5.5067 0.7086 2.8316 0.2453 5.2501
-#> 261: 93.9382 -1.9140 -4.0768 0.0689 5.5191 0.7070 2.8271 0.2455 5.2518
-#> 262: 93.9467 -1.9126 -4.0755 0.0681 5.5261 0.7049 2.8227 0.2454 5.2564
-#> 263: 93.9594 -1.9110 -4.0739 0.0667 5.5365 0.7039 2.8196 0.2455 5.2613
-#> 264: 93.9697 -1.9096 -4.0718 0.0650 5.5589 0.7033 2.8174 0.2459 5.2628
-#> 265: 93.9784 -1.9080 -4.0698 0.0631 5.5668 0.7025 2.8153 0.2458 5.2627
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-#> 272: 94.0244 -1.9017 -4.0623 0.0542 5.6452 0.6944 2.7863 0.2449 5.2626
-#> 273: 94.0312 -1.9010 -4.0620 0.0531 5.6581 0.6939 2.7821 0.2450 5.2620
-#> 274: 94.0387 -1.9004 -4.0615 0.0520 5.6569 0.6932 2.7774 0.2456 5.2657
-#> 275: 94.0381 -1.9000 -4.0611 0.0510 5.6525 0.6938 2.7727 0.2463 5.2662
-#> 276: 94.0426 -1.8994 -4.0606 0.0498 5.6664 0.6955 2.7682 0.2472 5.2687
-#> 277: 94.0437 -1.8988 -4.0604 0.0486 5.6705 0.6969 2.7646 0.2479 5.2699
-#> 278: 94.0470 -1.8982 -4.0606 0.0476 5.6495 0.6983 2.7620 0.2487 5.2741
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-#> 280: 94.0485 -1.8977 -4.0609 0.0462 5.6510 0.6997 2.7565 0.2501 5.2755
-#> 281: 94.0473 -1.8975 -4.0609 0.0456 5.6493 0.6998 2.7529 0.2504 5.2764
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-#> 286: 94.0255 -1.8986 -4.0615 0.0427 5.6683 0.7018 2.7371 0.2507 5.2795
-#> 287: 94.0234 -1.8992 -4.0619 0.0427 5.6533 0.7014 2.7340 0.2513 5.2803
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-#> 289: 94.0179 -1.9008 -4.0641 0.0433 5.6553 0.7016 2.7358 0.2523 5.2808
-#> 290: 94.0135 -1.9017 -4.0650 0.0435 5.6776 0.7015 2.7363 0.2528 5.2839
-#> 291: 94.0101 -1.9025 -4.0660 0.0440 5.7028 0.7012 2.7372 0.2531 5.2883
-#> 292: 94.0066 -1.9034 -4.0672 0.0442 5.7277 0.7007 2.7369 0.2536 5.2890
-#> 293: 94.0002 -1.9042 -4.0681 0.0441 5.7462 0.7004 2.7366 0.2538 5.2906
-#> 294: 93.9917 -1.9049 -4.0690 0.0440 5.7707 0.7001 2.7363 0.2539 5.2927
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-#> 296: 93.9807 -1.9060 -4.0716 0.0441 5.7884 0.7000 2.7362 0.2545 5.2974
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-#> 300: 93.9654 -1.9080 -4.0742 0.0441 5.7541 0.6993 2.7260 0.2563 5.3123
-#> 301: 93.9678 -1.9082 -4.0744 0.0439 5.7383 0.6980 2.7217 0.2568 5.3165
-#> 302: 93.9687 -1.9087 -4.0747 0.0435 5.7262 0.6977 2.7175 0.2574 5.3179
-#> 303: 93.9675 -1.9090 -4.0751 0.0430 5.7050 0.6966 2.7137 0.2580 5.3197
-#> 304: 93.9641 -1.9092 -4.0755 0.0428 5.6977 0.6954 2.7097 0.2583 5.3215
-#> 305: 93.9624 -1.9095 -4.0759 0.0427 5.6986 0.6947 2.7061 0.2585 5.3200
-#> 306: 93.9623 -1.9098 -4.0763 0.0428 5.7065 0.6941 2.7025 0.2587 5.3174
-#> 307: 93.9635 -1.9105 -4.0767 0.0430 5.7229 0.6938 2.6992 0.2585 5.3153
-#> 308: 93.9658 -1.9112 -4.0778 0.0435 5.7340 0.6935 2.6992 0.2580 5.3131
-#> 309: 93.9671 -1.9119 -4.0784 0.0440 5.7510 0.6929 2.6990 0.2576 5.3113
-#> 310: 93.9669 -1.9124 -4.0791 0.0441 5.7560 0.6926 2.6988 0.2569 5.3128
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-#> 312: 93.9689 -1.9132 -4.0799 0.0446 5.7554 0.6921 2.6959 0.2559 5.3125
-#> 313: 93.9685 -1.9136 -4.0806 0.0448 5.7489 0.6921 2.6960 0.2553 5.3110
-#> 314: 93.9673 -1.9138 -4.0812 0.0447 5.7562 0.6925 2.6964 0.2545 5.3107
-#> 315: 93.9635 -1.9139 -4.0818 0.0447 5.7392 0.6931 2.6971 0.2539 5.3127
-#> 316: 93.9581 -1.9139 -4.0823 0.0442 5.7376 0.6937 2.6974 0.2532 5.3140
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-#> 318: 93.9521 -1.9141 -4.0829 0.0432 5.7378 0.6951 2.6970 0.2521 5.3158
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-#> 320: 93.9538 -1.9136 -4.0828 0.0414 5.7416 0.6964 2.6980 0.2510 5.3135
-#> 321: 93.9557 -1.9132 -4.0827 0.0406 5.7539 0.6969 2.6983 0.2503 5.3141
-#> 322: 93.9568 -1.9130 -4.0825 0.0399 5.7460 0.6971 2.6988 0.2497 5.3155
-#> 323: 93.9594 -1.9125 -4.0824 0.0393 5.7274 0.6972 2.6993 0.2492 5.3166
-#> 324: 93.9608 -1.9122 -4.0823 0.0386 5.7161 0.6973 2.7006 0.2487 5.3156
-#> 325: 93.9601 -1.9120 -4.0822 0.0379 5.7036 0.6973 2.7019 0.2483 5.3161
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-#> 327: 93.9615 -1.9115 -4.0820 0.0364 5.6682 0.6986 2.7024 0.2476 5.3203
-#> 328: 93.9601 -1.9114 -4.0814 0.0355 5.6746 0.6999 2.7012 0.2472 5.3224
-#> 329: 93.9580 -1.9112 -4.0809 0.0348 5.6670 0.7014 2.7003 0.2469 5.3229
-#> 330: 93.9577 -1.9111 -4.0808 0.0341 5.6613 0.7023 2.7007 0.2466 5.3224
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-#> 334: 93.9672 -1.9096 -4.0805 0.0311 5.6801 0.7051 2.7033 0.2456 5.3168
-#> 335: 93.9714 -1.9093 -4.0805 0.0302 5.6855 0.7058 2.7038 0.2453 5.3156
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-#> 338: 93.9845 -1.9087 -4.0803 0.0278 5.7100 0.7074 2.7042 0.2443 5.3166
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-#> 352: 94.0059 -1.9067 -4.0788 0.0216 5.8778 0.7141 2.7039 0.2390 5.3139
-#> 353: 94.0073 -1.9067 -4.0792 0.0215 5.8709 0.7140 2.7047 0.2388 5.3129
-#> 354: 94.0078 -1.9065 -4.0795 0.0214 5.8623 0.7139 2.7054 0.2386 5.3135
-#> 355: 94.0065 -1.9064 -4.0795 0.0211 5.8637 0.7137 2.7048 0.2383 5.3122
-#> 356: 94.0080 -1.9063 -4.0796 0.0209 5.8613 0.7134 2.7041 0.2380 5.3121
-#> 357: 94.0105 -1.9061 -4.0797 0.0206 5.8613 0.7132 2.7036 0.2379 5.3119
-#> 358: 94.0114 -1.9059 -4.0798 0.0205 5.8539 0.7130 2.7029 0.2377 5.3107
-#> 359: 94.0154 -1.9058 -4.0799 0.0203 5.8559 0.7126 2.7024 0.2374 5.3112
-#> 360: 94.0165 -1.9057 -4.0800 0.0201 5.8544 0.7124 2.7020 0.2372 5.3099
-#> 361: 94.0198 -1.9056 -4.0802 0.0199 5.8511 0.7121 2.7018 0.2370 5.3089
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-#> 363: 94.0241 -1.9053 -4.0821 0.0197 5.8582 0.7121 2.7135 0.2366 5.3073
-#> 364: 94.0254 -1.9052 -4.0824 0.0195 5.8606 0.7122 2.7147 0.2362 5.3079
-#> 365: 94.0276 -1.9052 -4.0831 0.0195 5.8668 0.7119 2.7197 0.2359 5.3081
-#> 366: 94.0276 -1.9052 -4.0836 0.0195 5.8765 0.7121 2.7217 0.2357 5.3074
-#> 367: 94.0276 -1.9051 -4.0842 0.0194 5.8627 0.7120 2.7240 0.2354 5.3083
-#> 368: 94.0292 -1.9050 -4.0847 0.0195 5.8579 0.7120 2.7254 0.2352 5.3096
-#> 369: 94.0289 -1.9049 -4.0852 0.0195 5.8590 0.7122 2.7271 0.2350 5.3095
-#> 370: 94.0300 -1.9049 -4.0855 0.0194 5.8712 0.7123 2.7284 0.2348 5.3094
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-#> 373: 94.0315 -1.9051 -4.0861 0.0196 5.8840 0.7120 2.7305 0.2341 5.3091
-#> 374: 94.0323 -1.9052 -4.0862 0.0194 5.8755 0.7120 2.7301 0.2337 5.3101
-#> 375: 94.0344 -1.9055 -4.0863 0.0193 5.8744 0.7122 2.7308 0.2333 5.3121
-#> 376: 94.0341 -1.9056 -4.0865 0.0191 5.8738 0.7122 2.7311 0.2327 5.3136
-#> 377: 94.0320 -1.9055 -4.0868 0.0188 5.8703 0.7121 2.7311 0.2322 5.3161
-#> 378: 94.0291 -1.9058 -4.0869 0.0186 5.8771 0.7124 2.7311 0.2317 5.3187
-#> 379: 94.0273 -1.9062 -4.0872 0.0184 5.8829 0.7127 2.7316 0.2312 5.3206
-#> 380: 94.0259 -1.9067 -4.0875 0.0181 5.8786 0.7130 2.7321 0.2306 5.3235
-#> 381: 94.0231 -1.9068 -4.0877 0.0178 5.8716 0.7132 2.7331 0.2300 5.3231
-#> 382: 94.0210 -1.9069 -4.0879 0.0172 5.8636 0.7134 2.7340 0.2294 5.3240
-#> 383: 94.0189 -1.9070 -4.0880 0.0167 5.8596 0.7140 2.7351 0.2287 5.3246
-#> 384: 94.0171 -1.9070 -4.0882 0.0161 5.8588 0.7147 2.7365 0.2281 5.3251
-#> 385: 94.0141 -1.9070 -4.0880 0.0154 5.8659 0.7152 2.7365 0.2276 5.3263
-#> 386: 94.0116 -1.9070 -4.0879 0.0148 5.8785 0.7158 2.7364 0.2270 5.3272
-#> 387: 94.0090 -1.9070 -4.0877 0.0142 5.8874 0.7164 2.7363 0.2264 5.3286
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-#> 390: 94.0074 -1.9064 -4.0872 0.0126 5.9258 0.7175 2.7362 0.2249 5.3353
-#> 391: 94.0092 -1.9061 -4.0870 0.0121 5.9426 0.7174 2.7359 0.2245 5.3370
-#> 392: 94.0112 -1.9060 -4.0870 0.0119 5.9499 0.7175 2.7358 0.2242 5.3375
-#> 393: 94.0120 -1.9058 -4.0869 0.0116 5.9514 0.7177 2.7351 0.2237 5.3364
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-#> 398: 94.0201 -1.9056 -4.0867 0.0102 5.9353 0.7197 2.7348 0.2220 5.3380
-#> 399: 94.0204 -1.9056 -4.0868 0.0101 5.9282 0.7201 2.7350 0.2217 5.3387
-#> 400: 94.0198 -1.9058 -4.0867 0.0099 5.9243 0.7206 2.7348 0.2214 5.3383
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-#> 402: 94.0176 -1.9060 -4.0868 0.0096 5.9237 0.7215 2.7342 0.2209 5.3370
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-#> 404: 94.0147 -1.9062 -4.0870 0.0093 5.9322 0.7226 2.7330 0.2203 5.3382
-#> 405: 94.0131 -1.9065 -4.0872 0.0092 5.9354 0.7232 2.7326 0.2202 5.3385
-#> 406: 94.0117 -1.9066 -4.0872 0.0091 5.9399 0.7237 2.7318 0.2200 5.3388
-#> 407: 94.0114 -1.9069 -4.0871 0.0090 5.9495 0.7238 2.7314 0.2199 5.3397
-#> 408: 94.0133 -1.9071 -4.0870 0.0089 5.9505 0.7238 2.7310 0.2197 5.3401
-#> 409: 94.0159 -1.9074 -4.0868 0.0090 5.9523 0.7237 2.7309 0.2196 5.3417
-#> 410: 94.0171 -1.9076 -4.0864 0.0087 5.9503 0.7235 2.7307 0.2195 5.3449
-#> 411: 94.0193 -1.9078 -4.0862 0.0086 5.9528 0.7234 2.7304 0.2194 5.3476
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-#> 413: 94.0192 -1.9085 -4.0859 0.0087 5.9491 0.7235 2.7302 0.2195 5.3517
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-#> 415: 94.0156 -1.9088 -4.0861 0.0088 5.9408 0.7238 2.7289 0.2196 5.3528
-#> 416: 94.0145 -1.9090 -4.0861 0.0088 5.9442 0.7236 2.7281 0.2197 5.3540
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-#> 418: 94.0144 -1.9097 -4.0864 0.0095 5.9495 0.7233 2.7269 0.2199 5.3551
-#> 419: 94.0142 -1.9102 -4.0866 0.0099 5.9425 0.7233 2.7265 0.2200 5.3555
-#> 420: 94.0134 -1.9107 -4.0867 0.0102 5.9338 0.7234 2.7260 0.2200 5.3563
-#> 421: 94.0096 -1.9113 -4.0869 0.0105 5.9272 0.7236 2.7260 0.2200 5.3571
-#> 422: 94.0069 -1.9118 -4.0872 0.0108 5.9238 0.7238 2.7261 0.2200 5.3576
-#> 423: 94.0034 -1.9124 -4.0874 0.0111 5.9217 0.7240 2.7260 0.2200 5.3579
-#> 424: 94.0009 -1.9129 -4.0876 0.0114 5.9258 0.7240 2.7259 0.2200 5.3578
-#> 425: 94.0000 -1.9134 -4.0879 0.0119 5.9330 0.7240 2.7258 0.2199 5.3572
-#> 426: 93.9991 -1.9138 -4.0881 0.0122 5.9526 0.7243 2.7256 0.2198 5.3572
-#> 427: 93.9969 -1.9140 -4.0882 0.0124 5.9692 0.7247 2.7258 0.2196 5.3587
-#> 428: 93.9940 -1.9143 -4.0883 0.0124 5.9777 0.7247 2.7259 0.2194 5.3591
-#> 429: 93.9935 -1.9145 -4.0882 0.0123 5.9781 0.7247 2.7260 0.2192 5.3601
-#> 430: 93.9925 -1.9147 -4.0881 0.0122 5.9772 0.7247 2.7260 0.2190 5.3606
-#> 431: 93.9928 -1.9150 -4.0879 0.0120 5.9824 0.7249 2.7262 0.2189 5.3616
-#> 432: 93.9930 -1.9152 -4.0879 0.0120 5.9797 0.7251 2.7267 0.2188 5.3618
-#> 433: 93.9930 -1.9154 -4.0878 0.0119 5.9785 0.7254 2.7271 0.2187 5.3626
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-#> 435: 93.9935 -1.9157 -4.0878 0.0120 5.9659 0.7255 2.7269 0.2186 5.3643
-#> 436: 93.9951 -1.9158 -4.0876 0.0120 5.9570 0.7253 2.7263 0.2184 5.3667
-#> 437: 93.9980 -1.9158 -4.0874 0.0119 5.9492 0.7252 2.7259 0.2182 5.3680
-#> 438: 93.9999 -1.9158 -4.0872 0.0117 5.9361 0.7250 2.7255 0.2179 5.3700
-#> 439: 93.9990 -1.9159 -4.0868 0.0115 5.9312 0.7249 2.7247 0.2177 5.3700
-#> 440: 93.9986 -1.9160 -4.0865 0.0114 5.9280 0.7248 2.7235 0.2175 5.3698
-#> 441: 93.9996 -1.9160 -4.0863 0.0114 5.9248 0.7246 2.7222 0.2173 5.3696
-#> 442: 94.0001 -1.9160 -4.0861 0.0114 5.9266 0.7243 2.7213 0.2171 5.3702
-#> 443: 94.0004 -1.9159 -4.0859 0.0113 5.9228 0.7241 2.7202 0.2169 5.3707
-#> 444: 93.9989 -1.9161 -4.0858 0.0113 5.9200 0.7239 2.7194 0.2166 5.3722
-#> 445: 93.9971 -1.9162 -4.0857 0.0114 5.9257 0.7238 2.7182 0.2165 5.3736
-#> 446: 93.9970 -1.9164 -4.0858 0.0114 5.9286 0.7238 2.7177 0.2164 5.3738
-#> 447: 93.9959 -1.9163 -4.0858 0.0113 5.9407 0.7237 2.7166 0.2165 5.3731
-#> 448: 93.9947 -1.9163 -4.0856 0.0113 5.9442 0.7237 2.7159 0.2167 5.3723
-#> 449: 93.9948 -1.9164 -4.0854 0.0114 5.9386 0.7234 2.7151 0.2170 5.3730
-#> 450: 93.9937 -1.9164 -4.0853 0.0115 5.9368 0.7231 2.7142 0.2172 5.3732
-#> 451: 93.9929 -1.9164 -4.0851 0.0114 5.9312 0.7229 2.7135 0.2173 5.3735
-#> 452: 93.9923 -1.9163 -4.0850 0.0112 5.9288 0.7227 2.7121 0.2175 5.3747
-#> 453: 93.9918 -1.9162 -4.0849 0.0111 5.9339 0.7225 2.7112 0.2178 5.3759
-#> 454: 93.9912 -1.9164 -4.0849 0.0111 5.9355 0.7224 2.7103 0.2181 5.3777
-#> 455: 93.9902 -1.9164 -4.0849 0.0111 5.9412 0.7223 2.7097 0.2183 5.3784
-#> 456: 93.9894 -1.9164 -4.0848 0.0110 5.9554 0.7223 2.7076 0.2186 5.3801
-#> 457: 93.9902 -1.9161 -4.0846 0.0110 5.9675 0.7219 2.7054 0.2188 5.3807
-#> 458: 93.9907 -1.9159 -4.0845 0.0109 5.9710 0.7216 2.7032 0.2191 5.3815
-#> 459: 93.9926 -1.9157 -4.0844 0.0108 5.9751 0.7213 2.7011 0.2193 5.3817
-#> 460: 93.9930 -1.9155 -4.0845 0.0107 5.9788 0.7210 2.6985 0.2197 5.3818
-#> 461: 93.9933 -1.9153 -4.0845 0.0106 5.9809 0.7208 2.6959 0.2200 5.3822
-#> 462: 93.9941 -1.9153 -4.0845 0.0105 5.9904 0.7205 2.6935 0.2203 5.3820
-#> 463: 93.9945 -1.9152 -4.0844 0.0105 5.9971 0.7201 2.6913 0.2206 5.3817
-#> 464: 93.9942 -1.9151 -4.0844 0.0104 6.0010 0.7198 2.6892 0.2209 5.3818
-#> 465: 93.9931 -1.9152 -4.0843 0.0103 6.0113 0.7193 2.6872 0.2212 5.3823
-#> 466: 93.9937 -1.9152 -4.0840 0.0101 6.0145 0.7188 2.6853 0.2215 5.3828
-#> 467: 93.9939 -1.9152 -4.0838 0.0099 6.0189 0.7182 2.6835 0.2218 5.3832
-#> 468: 93.9933 -1.9153 -4.0835 0.0097 6.0247 0.7177 2.6818 0.2221 5.3830
-#> 469: 93.9933 -1.9153 -4.0832 0.0095 6.0251 0.7173 2.6801 0.2224 5.3822
-#> 470: 93.9914 -1.9153 -4.0829 0.0092 6.0332 0.7169 2.6785 0.2226 5.3823
-#> 471: 93.9894 -1.9153 -4.0826 0.0089 6.0455 0.7165 2.6769 0.2230 5.3822
-#> 472: 93.9869 -1.9152 -4.0824 0.0086 6.0454 0.7161 2.6754 0.2232 5.3836
-#> 473: 93.9852 -1.9152 -4.0822 0.0084 6.0501 0.7159 2.6740 0.2234 5.3832
-#> 474: 93.9829 -1.9152 -4.0821 0.0082 6.0579 0.7155 2.6725 0.2235 5.3831
-#> 475: 93.9826 -1.9152 -4.0819 0.0082 6.0661 0.7150 2.6711 0.2238 5.3829
-#> 476: 93.9837 -1.9152 -4.0819 0.0082 6.0774 0.7147 2.6696 0.2241 5.3824
-#> 477: 93.9852 -1.9151 -4.0819 0.0081 6.0890 0.7145 2.6681 0.2244 5.3817
-#> 478: 93.9851 -1.9151 -4.0820 0.0080 6.0957 0.7144 2.6665 0.2246 5.3827
-#> 479: 93.9857 -1.9150 -4.0820 0.0079 6.0981 0.7144 2.6651 0.2250 5.3838
-#> 480: 93.9856 -1.9151 -4.0821 0.0080 6.0944 0.7144 2.6638 0.2255 5.3854
-#> 481: 93.9864 -1.9152 -4.0823 0.0081 6.0912 0.7144 2.6624 0.2258 5.3865
-#> 482: 93.9870 -1.9153 -4.0825 0.0081 6.0954 0.7142 2.6613 0.2262 5.3864
-#> 483: 93.9888 -1.9153 -4.0826 0.0081 6.0888 0.7141 2.6602 0.2267 5.3870
-#> 484: 93.9903 -1.9154 -4.0828 0.0082 6.0848 0.7139 2.6592 0.2272 5.3861
-#> 485: 93.9914 -1.9154 -4.0831 0.0085 6.0851 0.7138 2.6586 0.2275 5.3858
-#> 486: 93.9909 -1.9154 -4.0834 0.0088 6.0824 0.7137 2.6581 0.2278 5.3850
-#> 487: 93.9899 -1.9155 -4.0838 0.0091 6.0870 0.7137 2.6577 0.2281 5.3838
-#> 488: 93.9882 -1.9156 -4.0842 0.0095 6.0877 0.7135 2.6574 0.2284 5.3835
-#> 489: 93.9865 -1.9163 -4.0841 0.0099 6.0839 0.7139 2.6581 0.2287 5.3835
-#> 490: 93.9859 -1.9170 -4.0841 0.0104 6.0783 0.7143 2.6587 0.2290 5.3830
-#> 491: 93.9847 -1.9177 -4.0838 0.0108 6.0773 0.7148 2.6596 0.2293 5.3824
-#> 492: 93.9840 -1.9183 -4.0836 0.0110 6.0833 0.7152 2.6606 0.2295 5.3817
-#> 493: 93.9832 -1.9188 -4.0834 0.0113 6.0832 0.7157 2.6613 0.2297 5.3814
-#> 494: 93.9824 -1.9195 -4.0832 0.0115 6.0859 0.7163 2.6620 0.2299 5.3819
-#> 495: 93.9813 -1.9200 -4.0830 0.0117 6.0878 0.7169 2.6633 0.2300 5.3820
-#> 496: 93.9798 -1.9206 -4.0827 0.0118 6.0871 0.7173 2.6644 0.2302 5.3825
-#> 497: 93.9787 -1.9213 -4.0824 0.0120 6.0856 0.7178 2.6653 0.2304 5.3834
-#> 498: 93.9771 -1.9220 -4.0822 0.0123 6.0759 0.7181 2.6660 0.2308 5.3850
-#> 499: 93.9744 -1.9225 -4.0819 0.0125 6.0692 0.7183 2.6666 0.2311 5.3868
-#> 500: 93.9728 -1.9229 -4.0816 0.0129 6.0609 0.7184 2.6675 0.2314 5.3884
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#>
Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> | #| Objective Fun | parent_0 | log_k1 | log_k2 | g_qlogis |
-#> |.....................| sigma | o1 | o2 | o3 |
-#>
|.....................| o4 |...........|...........|...........|
-#> |
1| 319.20504 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 319.20504 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
319.20504 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | G| Gill Diff. | 17.25 | -0.06517 | -0.2231 | 0.05323 |
-#> |.....................| -31.06 | 10.54 | -5.521 | 3.149 |
-#>
|.....................| -10.19 |...........|...........|...........|
-#> |
2| 930.59637 | 0.5572 | -0.9500 | -0.9943 | -0.9135 |
-#> |.....................| -0.07749 | -1.170 | -0.7520 | -0.9767 |
-#>
|.....................| -0.6292 |...........|...........|...........|
-#> | U| 930.59637 | 52.42 | -1.832 | -4.205 | 0.1099 |
-#> |.....................| 2.723 | 0.5378 | 1.159 | 0.8352 |
-#>
|.....................| 1.457 |...........|...........|...........|
-#> | X|
930.59637 | 52.42 | 0.1600 | 0.01492 | 0.5274 |
-#> |.....................| 2.723 | 0.5378 | 1.159 | 0.8352 |
-#>
|.....................| 1.457 |...........|...........|...........|
-#> |
3| 366.81009 | 0.9557 | -0.9515 | -0.9994 | -0.9122 |
-#> |.....................| -0.7950 | -0.9264 | -0.8795 | -0.9039 |
-#>
|.....................| -0.8647 |...........|...........|...........|
-#> | U| 366.81009 | 89.92 | -1.834 | -4.210 | 0.1100 |
-#> |.....................| 2.024 | 0.7174 | 1.030 | 0.9013 |
-#>
|.....................| 1.185 |...........|...........|...........|
-#> | X|
366.81009 | 89.92 | 0.1598 | 0.01484 | 0.5275 |
-#> |.....................| 2.024 | 0.7174 | 1.030 | 0.9013 |
-#>
|.....................| 1.185 |...........|...........|...........|
-#> |
4| 354.05577 | 0.9956 | -0.9516 | -0.9999 | -0.9121 |
-#> |.....................| -0.8667 | -0.9020 | -0.8922 | -0.8966 |
-#>
|.....................| -0.8882 |...........|...........|...........|
-#> | U| 354.05577 | 93.67 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.954 | 0.7353 | 1.017 | 0.9079 |
-#>
|.....................| 1.158 |...........|...........|...........|
-#> | X|
354.05577 | 93.67 | 0.1597 | 0.01484 | 0.5275 |
-#> |.....................| 1.954 | 0.7353 | 1.017 | 0.9079 |
-#>
|.....................| 1.158 |...........|...........|...........|
-#> |
5| 354.18966 | 0.9996 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8739 | -0.8996 | -0.8935 | -0.8959 |
-#>
|.....................| -0.8906 |...........|...........|...........|
-#> | U| 354.18966 | 94.04 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7371 | 1.015 | 0.9086 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.18966 | 94.04 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7371 | 1.015 | 0.9086 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
6| 354.21855 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8746 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.21855 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.21855 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
7| 354.22159 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22159 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22159 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
8| 354.22201 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22201 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22201 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
9| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
10| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
11| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
12| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
13| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
14| 354.22204 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.22204 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.22204 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
15| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.222 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
16| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.222 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> |
17| 354.22200 | 1.000 | -0.9516 | -1.000 | -0.9121 |
-#> |.....................| -0.8747 | -0.8993 | -0.8937 | -0.8958 |
-#>
|.....................| -0.8908 |...........|...........|...........|
-#> | U| 354.222 | 94.08 | -1.834 | -4.211 | 0.1100 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> | X|
354.222 | 94.08 | 0.1597 | 0.01483 | 0.5275 |
-#> |.....................| 1.947 | 0.7373 | 1.015 | 0.9087 |
-#>
|.....................| 1.155 |...........|...........|...........|
-#> calculating covariance matrix
+
f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP",
], est
= "saem",
+ control
= saemControl(print
= 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.5894 -2.4029 -3.9815 2.0318 3.0448 0.8581 1.0844 0.3182 21.0327
-#> 2: 93.5363 -2.3652 -3.9374 1.9473 2.8925 0.8152 1.0302 0.3023 14.7642
-#> 3: 93.3061 -2.3950 -3.8630 1.9537 2.7479 0.7744 1.0729 0.2872 12.2332
-#> 4: 93.4757 -2.3967 -3.8509 1.9504 2.6105 0.7357 1.1580 0.2729 11.6140
-#> 5: 93.6045 -2.3957 -3.8593 1.9732 2.4800 0.6989 1.1001 0.2592 11.0776
-#> 6: 93.6138 -2.4089 -3.9577 1.9557 2.8119 0.6640 1.0451 0.2463 11.5001
-#> 7: 93.4125 -2.3879 -3.8924 1.9950 3.1015 0.6308 1.0649 0.2339 10.6133
-#> 8: 93.5798 -2.3850 -3.9314 1.9888 3.0019 0.5992 1.0116 0.2222 10.4278
-#> 9: 93.1493 -2.3918 -3.9011 2.0040 4.3802 0.5693 1.0723 0.2111 10.2172
-#> 10: 93.5411 -2.3906 -3.8778 1.9664 4.5606 0.5408 1.0616 0.2006 10.1244
-#> 11: 93.3749 -2.4011 -3.8586 1.9682 4.3326 0.5138 1.0696 0.1905 10.1145
-#> 12: 93.0136 -2.3943 -3.8530 1.9633 4.1160 0.4881 1.0606 0.1810 10.0091
-#> 13: 93.1809 -2.4059 -3.9088 1.9821 3.9102 0.5448 1.0076 0.1720 9.8058
-#> 14: 93.3891 -2.4107 -3.9285 1.9894 3.7147 0.5504 0.9810 0.1634 10.2784
-#> 15: 93.4041 -2.4114 -3.9711 2.0216 4.4250 0.6070 0.9495 0.1552 9.4036
-#> 16: 93.4244 -2.4191 -4.0366 2.0511 4.2037 0.6035 0.9020 0.1474 10.0835
-#> 17: 93.6295 -2.4103 -4.0143 2.0509 4.0926 0.5997 0.8599 0.1401 9.7686
-#> 18: 93.6653 -2.4165 -3.9724 2.0405 3.8880 0.5979 0.9046 0.1331 9.6299
-#> 19: 93.6510 -2.4088 -3.9969 2.0328 3.6936 0.5934 0.9181 0.1264 9.3236
-#> 20: 93.6048 -2.4117 -3.9552 2.0268 3.9084 0.5879 1.0078 0.1201 9.6618
-#> 21: 94.0961 -2.4193 -3.9812 2.0552 3.7456 0.5743 0.9574 0.1141 9.6510
-#> 22: 93.9157 -2.4202 -3.9102 2.0263 5.0447 0.6198 0.9742 0.1294 9.6463
-#> 23: 94.1580 -2.4286 -3.9223 2.0441 4.7925 0.5981 0.9312 0.1230 9.8346
-#> 24: 94.4405 -2.4141 -3.9564 2.0383 4.5529 0.5925 0.9173 0.1168 10.6161
-#> 25: 93.8846 -2.3958 -4.0122 2.0053 4.9956 0.5677 0.8715 0.1173 10.3823
-#> 26: 93.6815 -2.3835 -3.9801 1.9872 5.6625 0.5514 0.8368 0.1114 9.8283
-#> 27: 93.6463 -2.3779 -3.9731 1.9833 5.3794 0.5566 0.8650 0.1059 9.5439
-#> 28: 93.7974 -2.3980 -3.9583 1.9657 6.4804 0.5366 0.8756 0.1006 9.7998
-#> 29: 93.6921 -2.4221 -3.8982 1.9701 6.1564 0.6070 0.9713 0.0955 9.2988
-#> 30: 93.3112 -2.4200 -3.8916 1.9702 6.6968 0.6110 0.9538 0.0908 9.1812
-#> 31: 93.9900 -2.4282 -3.9448 2.0257 6.3620 0.6071 0.9061 0.0862 9.4865
-#> 32: 93.8014 -2.4241 -3.9364 2.0053 6.8497 0.6173 0.8608 0.0819 9.5589
-#> 33: 94.0330 -2.4215 -3.9888 2.0034 6.5072 0.6142 0.8178 0.0778 10.2023
-#> 34: 93.5811 -2.4215 -3.9917 2.0170 6.1819 0.5907 0.8314 0.0842 10.2204
-#> 35: 93.9308 -2.4210 -3.8798 2.0046 6.7593 0.5877 1.1132 0.0800 9.2384
-#> 36: 94.0000 -2.4325 -3.8970 2.0457 6.4213 0.5886 1.0731 0.0835 8.8987
-#> 37: 93.4010 -2.4325 -3.9306 2.0550 7.2268 0.5886 1.0220 0.0969 9.1261
-#> 38: 93.3896 -2.4291 -3.9250 2.0148 6.8655 0.5885 0.9709 0.1039 9.2989
-#> 39: 93.3821 -2.4349 -3.9148 2.0368 6.5222 0.6059 0.9647 0.1095 9.2864
-#> 40: 93.1382 -2.4685 -3.9384 2.1083 8.6249 0.6287 1.0265 0.1066 9.6411
-#> 41: 92.7963 -2.4643 -3.8992 2.0585 8.1937 0.6376 1.1117 0.1234 9.4738
-#> 42: 92.7160 -2.4545 -3.9652 2.0680 7.7840 0.6068 1.0561 0.1173 9.4776
-#> 43: 93.0070 -2.4360 -4.0223 2.0624 7.9556 0.5840 1.0033 0.1114 9.7197
-#> 44: 93.3836 -2.4207 -4.0739 2.0872 7.5578 0.5788 0.9531 0.1058 10.3515
-#> 45: 93.3240 -2.4382 -4.0210 2.1103 7.1799 0.6211 0.9055 0.1165 10.5050
-#> 46: 93.1921 -2.4438 -4.0330 2.0842 7.3884 0.6159 0.8602 0.1107 10.7251
-#> 47: 92.9710 -2.4351 -4.0155 2.1117 7.0189 0.5998 0.8519 0.1091 10.2972
-#> 48: 93.0129 -2.4395 -3.9677 2.0986 6.6680 0.5804 0.8775 0.1058 10.8515
-#> 49: 92.6562 -2.4474 -4.0295 2.0877 6.3346 0.6338 0.8723 0.1155 10.0641
-#> 50: 92.5101 -2.4612 -4.0295 2.0845 6.0179 0.6197 0.8742 0.1097 9.9048
-#> 51: 92.9446 -2.4615 -3.9927 2.1199 5.7170 0.6165 0.9311 0.1042 9.8383
-#> 52: 92.8362 -2.4525 -3.9682 2.0787 5.4311 0.6329 0.9647 0.0990 9.0726
-#> 53: 92.8579 -2.4598 -3.9324 2.0529 5.1596 0.6057 0.9192 0.0940 9.5677
-#> 54: 92.8667 -2.4858 -3.9104 2.0454 5.0661 0.6304 1.0025 0.0893 9.0977
-#> 55: 93.2327 -2.4650 -3.8323 2.0628 6.8188 0.6499 1.1366 0.0852 8.5677
-#> 56: 92.9319 -2.4794 -3.8376 2.0490 6.4778 0.6635 1.1141 0.1064 9.0723
-#> 57: 93.1126 -2.5128 -3.8223 2.0834 6.1539 0.6637 1.1361 0.1010 9.2678
-#> 58: 93.5085 -2.4894 -3.8723 2.0650 5.8462 0.6745 1.0793 0.0960 9.0367
-#> 59: 93.7882 -2.4614 -3.9241 2.0707 5.5539 0.6898 1.0254 0.0912 8.7466
-#> 60: 94.1492 -2.4386 -3.9415 2.0599 5.2762 0.6711 0.9741 0.0932 8.4466
-#> 61: 94.4215 -2.4272 -3.9647 2.0482 5.0124 0.6549 0.9254 0.0911 8.7870
-#> 62: 94.3607 -2.4053 -3.9633 1.9966 4.7618 0.6534 0.8878 0.1221 9.0404
-#> 63: 94.3958 -2.4179 -3.9386 2.0041 4.5237 0.6462 0.9360 0.1245 9.0491
-#> 64: 94.5204 -2.4175 -3.9411 2.0106 4.2975 0.6532 0.9657 0.1183 8.9115
-#> 65: 94.5674 -2.4117 -3.9701 2.0546 4.0826 0.6438 0.9238 0.1247 8.7293
-#> 66: 94.2199 -2.4337 -3.9298 2.0287 4.7686 0.6582 0.9262 0.1185 9.0519
-#> 67: 94.2756 -2.4305 -3.9706 2.0782 4.5301 0.6512 0.8799 0.1126 9.1397
-#> 68: 94.4195 -2.4193 -4.0049 2.0643 4.3036 0.6804 0.8359 0.1220 9.5306
-#> 69: 94.5255 -2.4183 -4.0119 2.0733 4.0884 0.6784 0.8577 0.1297 9.4535
-#> 70: 94.5668 -2.4117 -3.9662 2.0762 4.2149 0.6511 0.9325 0.1475 9.1637
-#> 71: 94.7464 -2.4147 -3.9937 2.0942 4.2418 0.6571 0.9524 0.1540 9.6576
-#> 72: 94.4869 -2.4160 -4.0050 2.1075 4.8520 0.6687 1.0119 0.1488 9.4234
-#> 73: 94.3747 -2.4423 -4.0072 2.1484 6.4364 0.6948 1.0011 0.1438 9.1490
-#> 74: 94.3997 -2.4464 -4.0147 2.1965 6.1146 0.7030 1.0566 0.1521 9.0697
-#> 75: 94.4187 -2.4566 -3.9611 2.1337 5.8089 0.6866 1.1666 0.1656 8.9436
-#> 76: 94.4381 -2.4502 -3.9816 2.1209 5.6488 0.7266 1.1449 0.1573 8.9289
-#> 77: 94.6421 -2.4446 -3.9603 2.1544 5.3663 0.6968 1.2087 0.1662 8.5186
-#> 78: 94.8397 -2.4420 -3.9690 2.1380 5.0980 0.6969 1.1833 0.1578 8.9071
-#> 79: 94.4296 -2.4547 -3.9576 2.1569 6.3095 0.6829 1.1850 0.1544 9.1345
-#> 80: 93.9628 -2.4530 -3.9312 2.0956 8.5844 0.6880 1.2548 0.1835 8.6936
-#> 81: 94.2900 -2.4687 -3.8570 2.0779 9.0596 0.6993 1.2012 0.1743 8.9092
-#> 82: 93.9652 -2.4742 -3.9261 2.0913 8.6066 0.6970 1.1667 0.1656 8.4359
-#> 83: 94.0828 -2.4739 -3.8603 2.0587 8.1763 0.7123 1.2575 0.1638 8.5431
-#> 84: 93.5926 -2.4645 -3.8993 2.0391 9.8721 0.7178 1.1947 0.1556 8.5623
-#> 85: 93.7052 -2.4692 -3.8411 2.0448 9.3785 0.7251 1.1349 0.1478 8.5558
-#> 86: 93.8043 -2.4726 -3.9028 2.0745 8.9096 0.7064 1.0782 0.1404 9.1308
-#> 87: 93.5704 -2.4836 -3.8694 2.0999 12.3224 0.7284 1.0922 0.1334 8.8645
-#> 88: 93.5715 -2.4827 -3.9202 2.0861 11.7063 0.7541 1.0376 0.1267 9.2433
-#> 89: 93.6894 -2.4720 -3.8964 2.1093 12.4610 0.7727 1.0218 0.1325 9.0321
-#> 90: 93.2881 -2.4787 -3.9464 2.1137 11.8380 0.7850 0.9707 0.1258 8.8265
-#> 91: 93.8454 -2.4626 -3.9566 2.1181 11.2461 0.7620 0.9579 0.1396 8.8279
-#> 92: 93.8268 -2.4639 -3.8951 2.0936 10.6838 0.7618 1.1083 0.1553 8.4609
-#> 93: 94.0622 -2.4853 -3.8531 2.0740 10.1496 0.7493 1.1237 0.1596 8.2057
-#> 94: 93.6190 -2.4843 -3.8857 2.0625 9.6421 0.7596 1.1104 0.1686 8.3522
-#> 95: 93.6352 -2.4725 -3.9243 2.0582 9.1600 0.7732 1.0549 0.1694 8.3993
-#> 96: 93.5291 -2.4707 -3.9318 2.0612 8.7020 0.7853 1.0639 0.1609 8.2908
-#> 97: 93.0626 -2.4639 -3.9255 2.0887 8.4092 0.7717 1.1477 0.1685 8.2710
-#> 98: 93.3712 -2.4677 -3.9642 2.1350 7.9888 0.7703 1.0903 0.1921 8.5468
-#> 99: 93.7108 -2.4848 -3.9775 2.1733 7.5893 0.7490 1.0367 0.1825 8.5629
-#> 100: 94.1114 -2.4867 -4.0111 2.1705 7.2099 0.7446 0.9849 0.1832 8.6964
-#> 101: 93.7547 -2.4897 -3.9793 2.1817 7.1755 0.7513 0.9899 0.1774 8.5077
-#> 102: 93.8818 -2.5029 -3.9929 2.2028 6.8167 0.7137 1.0045 0.1685 8.3706
-#> 103: 94.0026 -2.5094 -3.9680 2.2059 6.4759 0.7073 1.0498 0.1601 8.3087
-#> 104: 93.5946 -2.5260 -3.9640 2.2209 6.2674 0.7688 1.0548 0.1531 8.3444
-#> 105: 93.3863 -2.5431 -4.0087 2.2211 7.1040 0.7987 1.0020 0.1454 8.2210
-#> 106: 93.1536 -2.5365 -4.0243 2.2457 6.7488 0.7909 0.9519 0.1389 8.0950
-#> 107: 93.2220 -2.5446 -4.0016 2.2508 6.4114 0.8108 0.9483 0.1364 8.5629
-#> 108: 93.0778 -2.5470 -3.9678 2.2329 6.4774 0.8077 1.0081 0.1850 9.2740
-#> 109: 93.8925 -2.5453 -3.9560 2.2193 6.1535 0.8079 1.0608 0.2111 9.2651
-#> 110: 94.3171 -2.5179 -4.0040 2.2145 5.8458 0.7874 1.0520 0.2135 8.9788
-#> 111: 94.0655 -2.5069 -3.9752 2.2009 5.5536 0.8056 1.1206 0.2192 8.9410
-#> 112: 93.8552 -2.4994 -3.9791 2.1597 5.2759 0.8012 1.0646 0.2365 8.9570
-#> 113: 93.5190 -2.5053 -3.9760 2.1727 5.0121 0.8326 1.0114 0.2246 9.2154
-#> 114: 93.5531 -2.5083 -3.9569 2.1636 4.7615 0.8255 0.9879 0.2134 9.1197
-#> 115: 93.4780 -2.5217 -3.9467 2.1529 4.5234 0.8314 1.0392 0.2027 8.7850
-#> 116: 93.5707 -2.5216 -3.9098 2.1667 4.2972 0.8261 1.1213 0.1926 9.2991
-#> 117: 93.6610 -2.5445 -3.8775 2.1473 4.0824 0.8122 1.1232 0.1830 9.2054
-#> 118: 93.4315 -2.5251 -3.9166 2.1365 4.6012 0.7933 1.0690 0.1738 8.8061
-#> 119: 93.2491 -2.5265 -3.9236 2.1671 5.0672 0.8046 1.0711 0.1709 8.2293
-#> 120: 93.2605 -2.5327 -3.9714 2.1984 4.8138 0.8025 1.0176 0.1623 7.9088
-#> 121: 93.5831 -2.5448 -3.9669 2.2195 4.5731 0.8079 0.9921 0.1542 8.2211
-#> 122: 93.3408 -2.5460 -3.9710 2.2235 4.6838 0.8053 1.0377 0.1658 8.2934
-#> 123: 93.4581 -2.5395 -3.9487 2.2279 4.4496 0.8298 1.0338 0.1732 8.2859
-#> 124: 93.0562 -2.5565 -3.9587 2.2299 4.2272 0.8590 1.0531 0.1964 8.1244
-#> 125: 93.0576 -2.5660 -3.9434 2.2457 4.0158 0.8564 1.0768 0.1866 8.3730
-#> 126: 92.8366 -2.5571 -3.9463 2.2096 3.8150 0.8551 1.0476 0.1773 8.3820
-#> 127: 92.9607 -2.5595 -3.9773 2.2325 3.6243 0.8497 0.9952 0.1684 9.2276
-#> 128: 93.0655 -2.5463 -3.9731 2.1901 3.4430 0.8903 0.9454 0.1600 8.8096
-#> 129: 93.0669 -2.5467 -3.9713 2.2204 3.2709 0.8905 0.9234 0.1520 8.8686
-#> 130: 93.2036 -2.5524 -3.9702 2.2070 3.1073 0.8719 0.9514 0.1578 8.8433
-#> 131: 93.3565 -2.5544 -3.9809 2.1654 2.9520 0.8777 0.9117 0.1764 8.9770
-#> 132: 93.0371 -2.5364 -3.9250 2.1761 2.8044 0.8338 1.0518 0.1731 8.5405
-#> 133: 93.5727 -2.5388 -3.8759 2.1580 3.6769 0.8616 1.0981 0.1858 8.5303
-#> 134: 93.4962 -2.5341 -3.9006 2.1394 4.3695 0.8904 1.0432 0.1765 8.7067
-#> 135: 93.3219 -2.5413 -3.8922 2.1888 4.1510 0.8971 1.0435 0.1857 8.4977
-#> 136: 93.3582 -2.5477 -3.8412 2.1957 3.9435 0.8816 1.1954 0.2102 8.1330
-#> 137: 93.2791 -2.5313 -3.8936 2.1570 3.7463 0.8875 1.1356 0.1997 8.3094
-#> 138: 93.0890 -2.5428 -3.8910 2.1414 3.5590 0.8826 1.1008 0.2120 8.2653
-#> 139: 93.2404 -2.5407 -3.8926 2.1727 3.3810 0.8829 1.1068 0.2014 8.3739
-#> 140: 93.0870 -2.5514 -3.9131 2.2182 3.2120 0.8712 1.0870 0.1914 8.6179
-#> 141: 93.2715 -2.5499 -3.9460 2.2216 3.4383 0.8470 1.0662 0.1900 8.4034
-#> 142: 93.1915 -2.5583 -3.9990 2.2475 5.2653 0.8607 1.0129 0.2061 7.9891
-#> 143: 93.3709 -2.5650 -3.9422 2.2369 5.0020 0.8748 1.2043 0.2248 8.0084
-#> 144: 93.2092 -2.5706 -3.9016 2.1930 4.7519 0.8667 1.1977 0.2179 8.2733
-#> 145: 92.6640 -2.5733 -3.9225 2.1859 4.5143 0.8636 1.1695 0.2070 8.6212
-#> 146: 92.7581 -2.5695 -3.9055 2.1801 5.4209 0.8589 1.1678 0.1967 8.9378
-#> 147: 93.1089 -2.5707 -3.9825 2.2113 7.6640 0.8710 1.1094 0.1934 9.0543
-#> 148: 93.0803 -2.5672 -3.9461 2.2066 9.9043 0.8648 1.1043 0.1863 8.6209
-#> 149: 92.6332 -2.5468 -3.9425 2.1881 9.4091 0.8278 1.1313 0.1769 8.4652
-#> 150: 92.9068 -2.5440 -3.9531 2.2005 8.9386 0.8189 1.1104 0.1681 8.4196
-#> 151: 92.7324 -2.5497 -3.9648 2.2387 8.4917 0.8205 1.1421 0.1597 8.4228
-#> 152: 93.0394 -2.5282 -3.9916 2.2251 3.9029 0.8190 1.0320 0.1612 8.3453
-#> 153: 93.3137 -2.5268 -3.9993 2.2294 3.7951 0.8187 1.0311 0.1780 8.4258
-#> 154: 93.6677 -2.5264 -3.9756 2.2615 4.8704 0.8177 1.1355 0.1799 8.7204
-#> 155: 94.0822 -2.5409 -4.0456 2.2507 5.1202 0.8032 0.9930 0.1613 8.8844
-#> 156: 93.6289 -2.5388 -4.1150 2.2777 4.6367 0.8080 0.8336 0.1817 8.4370
-#> 157: 93.9171 -2.5327 -4.0218 2.2696 3.1121 0.8069 1.0394 0.1800 8.5006
-#> 158: 94.0010 -2.5357 -4.0036 2.2695 3.1485 0.8087 1.1132 0.2048 8.7160
-#> 159: 94.1277 -2.5541 -3.9717 2.2773 5.1432 0.8088 1.0732 0.1980 8.5378
-#> 160: 94.0075 -2.5436 -3.9550 2.2796 4.7826 0.8286 1.0820 0.1953 8.3885
-#> 161: 93.6793 -2.5471 -3.9675 2.2713 3.9366 0.8603 1.0682 0.1972 8.3026
-#> 162: 93.2649 -2.5429 -3.9564 2.2406 2.7349 0.8469 1.0889 0.1929 8.3765
-#> 163: 93.2072 -2.5519 -3.9786 2.2535 3.1500 0.8361 1.1240 0.1997 8.4527
-#> 164: 93.4059 -2.5471 -4.0398 2.2257 2.8708 0.8284 1.0541 0.2105 8.4984
-#> 165: 93.2579 -2.5407 -3.9665 2.2305 2.7397 0.8251 1.1355 0.2302 7.9794
-#> 166: 93.4900 -2.5465 -3.9565 2.2316 1.9775 0.8359 1.0939 0.2243 8.1279
-#> 167: 93.3825 -2.5567 -3.9784 2.2276 2.3737 0.8251 1.0894 0.2254 8.6657
-#> 168: 93.2568 -2.5681 -3.9993 2.2818 2.6721 0.8237 1.1398 0.2207 8.4894
-#> 169: 93.0484 -2.5468 -3.9693 2.2586 1.9105 0.8518 1.1911 0.1917 8.5627
-#> 170: 93.2703 -2.5730 -3.9059 2.2512 2.1481 0.8068 1.3267 0.2198 8.2260
-#> 171: 93.2041 -2.5720 -3.8992 2.2227 2.7790 0.8045 1.2387 0.2059 8.1401
-#> 172: 92.7596 -2.5722 -3.8802 2.2537 2.9977 0.8049 1.2807 0.1831 8.3375
-#> 173: 92.7734 -2.5716 -3.8811 2.1987 3.0176 0.8063 1.3070 0.2285 8.5061
-#> 174: 92.5561 -2.5700 -3.9236 2.2351 3.0286 0.8250 1.2000 0.2200 8.0725
-#> 175: 92.5072 -2.5724 -3.9968 2.2479 2.4287 0.8333 1.0169 0.2235 8.2600
-#> 176: 92.3531 -2.5787 -3.9977 2.2407 2.9999 0.8167 0.9813 0.2451 8.7505
-#> 177: 92.4672 -2.5746 -4.0095 2.2733 2.8040 0.8361 0.9794 0.2363 8.5176
-#> 178: 92.5747 -2.5981 -3.9921 2.2835 1.8203 0.8411 0.9795 0.2112 8.8034
-#> 179: 92.7101 -2.5766 -3.9697 2.2337 1.7808 0.8348 1.0402 0.2247 8.3952
-#> 180: 92.5348 -2.5714 -3.9595 2.2236 1.2661 0.8361 1.0107 0.2375 8.7156
-#> 181: 92.7241 -2.5730 -3.9205 2.2162 1.1047 0.8321 1.1192 0.2147 8.8821
-#> 182: 92.9177 -2.5864 -3.9351 2.2280 1.2069 0.8108 1.1022 0.2163 8.5703
-#> 183: 92.8646 -2.5704 -3.9755 2.2192 1.5680 0.8232 0.9400 0.1848 8.6586
-#> 184: 92.8081 -2.5759 -3.9981 2.2411 1.7739 0.8394 0.8711 0.1788 8.6327
-#> 185: 92.6830 -2.5700 -4.0110 2.2360 1.5375 0.8093 0.9114 0.1782 8.6703
-#> 186: 92.7691 -2.5764 -3.9671 2.2148 1.8813 0.8117 0.9794 0.1901 8.4813
-#> 187: 92.7540 -2.5659 -3.9695 2.2543 1.3755 0.8130 1.0332 0.1960 8.5371
-#> 188: 92.5722 -2.5650 -3.9527 2.2552 1.4000 0.8142 1.1013 0.1881 8.2025
-#> 189: 92.9404 -2.5644 -3.9446 2.2579 1.3589 0.8157 1.1262 0.1741 8.2347
-#> 190: 92.8142 -2.5628 -3.9397 2.2549 1.1871 0.8241 1.1571 0.1728 8.1590
-#> 191: 92.7352 -2.5682 -3.9476 2.2502 0.8302 0.7954 1.1448 0.1859 8.6148
-#> 192: 92.7380 -2.5574 -3.9273 2.2318 0.6692 0.8185 1.1124 0.1932 8.5279
-#> 193: 92.9199 -2.5652 -3.9586 2.2184 0.9877 0.8097 1.1689 0.1709 8.7071
-#> 194: 93.0042 -2.5651 -3.9699 2.2302 1.3311 0.8135 1.1202 0.1832 8.8051
-#> 195: 92.8090 -2.5890 -3.9799 2.2360 0.9251 0.8313 1.0192 0.1806 9.3110
-#> 196: 92.5114 -2.5894 -3.9883 2.2553 0.8504 0.8299 1.0665 0.1855 8.9668
-#> 197: 92.6704 -2.5845 -3.9577 2.2490 0.3567 0.8365 1.0893 0.1896 8.5856
-#> 198: 92.7249 -2.5753 -3.9775 2.2327 0.4282 0.8506 1.0736 0.2003 8.7110
-#> 199: 92.5538 -2.5696 -3.9550 2.2382 0.3177 0.8550 1.1060 0.2132 8.5431
-#> 200: 92.6352 -2.5716 -3.9921 2.2372 0.2500 0.8592 1.0083 0.2057 8.5811
-#> 201: 92.6440 -2.5663 -3.9931 2.2219 0.2611 0.8647 1.0130 0.1931 8.6428
-#> 202: 92.6090 -2.5633 -3.9837 2.2198 0.2389 0.8680 1.0373 0.1958 8.6818
-#> 203: 92.6180 -2.5627 -3.9823 2.2185 0.2315 0.8627 1.0398 0.1939 8.6310
-#> 204: 92.6140 -2.5628 -3.9783 2.2176 0.2289 0.8588 1.0462 0.1923 8.5391
-#> 205: 92.6337 -2.5619 -3.9802 2.2190 0.2227 0.8579 1.0407 0.1965 8.5514
-#> 206: 92.6373 -2.5615 -3.9835 2.2175 0.2313 0.8580 1.0330 0.2006 8.5635
-#> 207: 92.6403 -2.5594 -3.9836 2.2189 0.2365 0.8608 1.0282 0.2017 8.5721
-#> 208: 92.6415 -2.5587 -3.9862 2.2192 0.2480 0.8615 1.0221 0.2001 8.5738
-#> 209: 92.6303 -2.5586 -3.9872 2.2180 0.2544 0.8608 1.0127 0.1966 8.6159
-#> 210: 92.6278 -2.5584 -3.9829 2.2178 0.2577 0.8576 1.0149 0.1932 8.6336
-#> 211: 92.6320 -2.5580 -3.9844 2.2163 0.2614 0.8544 1.0057 0.1902 8.6594
-#> 212: 92.6266 -2.5576 -3.9802 2.2140 0.2554 0.8515 1.0125 0.1891 8.6549
-#> 213: 92.6226 -2.5570 -3.9771 2.2114 0.2491 0.8468 1.0201 0.1879 8.6612
-#> 214: 92.6217 -2.5570 -3.9759 2.2119 0.2430 0.8429 1.0289 0.1859 8.6700
-#> 215: 92.6212 -2.5573 -3.9743 2.2121 0.2354 0.8394 1.0383 0.1853 8.6796
-#> 216: 92.6151 -2.5566 -3.9736 2.2125 0.2329 0.8378 1.0446 0.1850 8.7036
-#> 217: 92.6073 -2.5558 -3.9759 2.2133 0.2311 0.8373 1.0459 0.1854 8.7185
-#> 218: 92.6090 -2.5556 -3.9771 2.2142 0.2312 0.8373 1.0499 0.1866 8.7181
-#> 219: 92.6166 -2.5553 -3.9764 2.2142 0.2358 0.8376 1.0624 0.1882 8.7228
-#> 220: 92.6268 -2.5549 -3.9770 2.2150 0.2404 0.8395 1.0671 0.1899 8.7325
-#> 221: 92.6337 -2.5548 -3.9765 2.2172 0.2460 0.8412 1.0713 0.1900 8.7409
-#> 222: 92.6383 -2.5563 -3.9796 2.2211 0.2499 0.8412 1.0667 0.1898 8.7456
-#> 223: 92.6399 -2.5575 -3.9806 2.2259 0.2494 0.8406 1.0665 0.1898 8.7564
-#> 224: 92.6424 -2.5589 -3.9840 2.2296 0.2451 0.8412 1.0624 0.1894 8.7571
-#> 225: 92.6431 -2.5599 -3.9883 2.2336 0.2427 0.8423 1.0555 0.1885 8.7754
-#> 226: 92.6393 -2.5612 -3.9919 2.2371 0.2384 0.8431 1.0488 0.1886 8.7904
-#> 227: 92.6354 -2.5630 -3.9918 2.2406 0.2361 0.8432 1.0501 0.1892 8.8070
-#> 228: 92.6328 -2.5650 -3.9926 2.2437 0.2336 0.8434 1.0524 0.1908 8.8133
-#> 229: 92.6328 -2.5672 -3.9913 2.2462 0.2318 0.8439 1.0578 0.1926 8.8314
-#> 230: 92.6322 -2.5684 -3.9911 2.2482 0.2269 0.8426 1.0621 0.1952 8.8464
-#> 231: 92.6263 -2.5698 -3.9910 2.2500 0.2240 0.8418 1.0628 0.1963 8.8734
-#> 232: 92.6228 -2.5710 -3.9908 2.2515 0.2218 0.8411 1.0644 0.1977 8.9056
-#> 233: 92.6235 -2.5721 -3.9919 2.2545 0.2192 0.8409 1.0649 0.1983 8.9192
-#> 234: 92.6232 -2.5727 -3.9927 2.2551 0.2171 0.8397 1.0649 0.1981 8.9294
-#> 235: 92.6219 -2.5733 -3.9924 2.2562 0.2155 0.8390 1.0646 0.1978 8.9242
-#> 236: 92.6212 -2.5737 -3.9924 2.2574 0.2145 0.8384 1.0639 0.1975 8.9292
-#> 237: 92.6211 -2.5738 -3.9938 2.2588 0.2142 0.8379 1.0607 0.1970 8.9400
-#> 238: 92.6194 -2.5735 -3.9931 2.2589 0.2155 0.8373 1.0630 0.1969 8.9371
-#> 239: 92.6175 -2.5734 -3.9928 2.2593 0.2155 0.8371 1.0648 0.1967 8.9315
-#> 240: 92.6175 -2.5729 -3.9923 2.2593 0.2143 0.8367 1.0673 0.1963 8.9180
-#> 241: 92.6155 -2.5728 -3.9917 2.2591 0.2133 0.8372 1.0695 0.1960 8.9139
-#> 242: 92.6135 -2.5726 -3.9923 2.2588 0.2136 0.8375 1.0681 0.1965 8.9191
-#> 243: 92.6115 -2.5726 -3.9930 2.2592 0.2127 0.8375 1.0683 0.1969 8.9117
-#> 244: 92.6106 -2.5726 -3.9925 2.2588 0.2123 0.8381 1.0704 0.1975 8.9124
-#> 245: 92.6065 -2.5730 -3.9930 2.2586 0.2127 0.8388 1.0691 0.1982 8.9140
-#> 246: 92.6046 -2.5734 -3.9931 2.2588 0.2109 0.8397 1.0701 0.1986 8.9132
-#> 247: 92.6048 -2.5737 -3.9938 2.2597 0.2081 0.8404 1.0708 0.1989 8.9224
-#> 248: 92.6029 -2.5739 -3.9932 2.2599 0.2056 0.8410 1.0718 0.1993 8.9198
-#> 249: 92.6006 -2.5743 -3.9934 2.2598 0.2052 0.8419 1.0705 0.1996 8.9244
-#> 250: 92.5984 -2.5740 -3.9930 2.2595 0.2037 0.8417 1.0709 0.1997 8.9208
-#> 251: 92.5967 -2.5739 -3.9932 2.2595 0.2018 0.8418 1.0700 0.1996 8.9143
-#> 252: 92.5943 -2.5737 -3.9920 2.2594 0.2009 0.8412 1.0734 0.1992 8.9090
-#> 253: 92.5944 -2.5736 -3.9904 2.2588 0.1997 0.8405 1.0769 0.1995 8.9035
-#> 254: 92.5941 -2.5732 -3.9896 2.2582 0.1987 0.8394 1.0788 0.1993 8.8940
-#> 255: 92.5916 -2.5728 -3.9892 2.2571 0.1983 0.8387 1.0794 0.1988 8.8894
-#> 256: 92.5889 -2.5724 -3.9880 2.2562 0.1988 0.8382 1.0813 0.1992 8.8834
-#> 257: 92.5889 -2.5719 -3.9872 2.2557 0.2003 0.8378 1.0831 0.1995 8.8806
-#> 258: 92.5889 -2.5717 -3.9866 2.2556 0.2021 0.8377 1.0858 0.1995 8.8792
-#> 259: 92.5898 -2.5715 -3.9867 2.2556 0.2033 0.8373 1.0884 0.1999 8.8785
-#> 260: 92.5924 -2.5709 -3.9868 2.2556 0.2033 0.8367 1.0891 0.2006 8.8743
-#> 261: 92.5956 -2.5703 -3.9866 2.2552 0.2045 0.8360 1.0908 0.2014 8.8635
-#> 262: 92.5985 -2.5698 -3.9859 2.2546 0.2054 0.8354 1.0940 0.2022 8.8551
-#> 263: 92.6014 -2.5694 -3.9857 2.2544 0.2067 0.8347 1.0964 0.2028 8.8479
-#> 264: 92.6041 -2.5690 -3.9858 2.2543 0.2069 0.8338 1.0977 0.2028 8.8421
-#> 265: 92.6063 -2.5687 -3.9861 2.2541 0.2079 0.8327 1.0976 0.2029 8.8394
-#> 266: 92.6087 -2.5684 -3.9867 2.2540 0.2107 0.8318 1.0968 0.2027 8.8351
-#> 267: 92.6108 -2.5682 -3.9863 2.2534 0.2118 0.8314 1.0970 0.2032 8.8283
-#> 268: 92.6130 -2.5680 -3.9860 2.2530 0.2131 0.8309 1.0970 0.2034 8.8263
-#> 269: 92.6139 -2.5678 -3.9851 2.2526 0.2155 0.8306 1.0979 0.2040 8.8240
-#> 270: 92.6144 -2.5676 -3.9851 2.2521 0.2176 0.8303 1.0972 0.2044 8.8283
-#> 271: 92.6153 -2.5675 -3.9855 2.2518 0.2190 0.8305 1.0961 0.2049 8.8310
-#> 272: 92.6163 -2.5674 -3.9859 2.2521 0.2196 0.8305 1.0965 0.2051 8.8378
-#> 273: 92.6178 -2.5672 -3.9862 2.2520 0.2198 0.8302 1.0959 0.2051 8.8421
-#> 274: 92.6193 -2.5670 -3.9870 2.2524 0.2195 0.8299 1.0955 0.2051 8.8441
-#> 275: 92.6197 -2.5669 -3.9874 2.2526 0.2194 0.8295 1.0947 0.2052 8.8477
-#> 276: 92.6215 -2.5665 -3.9875 2.2523 0.2206 0.8288 1.0956 0.2058 8.8462
-#> 277: 92.6225 -2.5660 -3.9878 2.2522 0.2231 0.8282 1.0974 0.2064 8.8450
-#> 278: 92.6237 -2.5655 -3.9883 2.2522 0.2240 0.8277 1.0988 0.2074 8.8501
-#> 279: 92.6249 -2.5651 -3.9888 2.2524 0.2244 0.8274 1.0994 0.2083 8.8504
-#> 280: 92.6259 -2.5647 -3.9891 2.2523 0.2235 0.8270 1.0992 0.2087 8.8514
-#> 281: 92.6264 -2.5643 -3.9889 2.2522 0.2225 0.8262 1.1001 0.2090 8.8559
-#> 282: 92.6270 -2.5639 -3.9889 2.2516 0.2223 0.8255 1.0997 0.2090 8.8593
-#> 283: 92.6280 -2.5633 -3.9885 2.2503 0.2214 0.8248 1.0999 0.2101 8.8586
-#> 284: 92.6281 -2.5627 -3.9883 2.2491 0.2212 0.8241 1.0993 0.2110 8.8580
-#> 285: 92.6283 -2.5621 -3.9881 2.2481 0.2213 0.8235 1.0986 0.2118 8.8590
-#> 286: 92.6288 -2.5615 -3.9886 2.2475 0.2219 0.8231 1.0973 0.2123 8.8602
-#> 287: 92.6291 -2.5611 -3.9890 2.2470 0.2217 0.8230 1.0961 0.2133 8.8577
-#> 288: 92.6292 -2.5607 -3.9893 2.2468 0.2202 0.8229 1.0960 0.2142 8.8570
-#> 289: 92.6275 -2.5602 -3.9895 2.2464 0.2192 0.8226 1.0964 0.2151 8.8554
-#> 290: 92.6262 -2.5598 -3.9892 2.2457 0.2189 0.8223 1.0977 0.2161 8.8578
-#> 291: 92.6246 -2.5596 -3.9890 2.2454 0.2183 0.8218 1.0999 0.2165 8.8596
-#> 292: 92.6223 -2.5593 -3.9892 2.2451 0.2183 0.8213 1.1003 0.2173 8.8575
-#> 293: 92.6201 -2.5590 -3.9896 2.2447 0.2193 0.8209 1.1003 0.2175 8.8569
-#> 294: 92.6169 -2.5587 -3.9902 2.2445 0.2202 0.8204 1.0998 0.2176 8.8568
-#> 295: 92.6144 -2.5584 -3.9906 2.2442 0.2217 0.8197 1.0994 0.2176 8.8565
-#> 296: 92.6126 -2.5581 -3.9913 2.2441 0.2223 0.8188 1.0983 0.2175 8.8585
-#> 297: 92.6112 -2.5576 -3.9920 2.2439 0.2235 0.8182 1.0969 0.2175 8.8600
-#> 298: 92.6108 -2.5572 -3.9921 2.2433 0.2250 0.8174 1.0964 0.2177 8.8612
-#> 299: 92.6101 -2.5567 -3.9919 2.2425 0.2254 0.8169 1.0960 0.2178 8.8626
-#> 300: 92.6097 -2.5562 -3.9913 2.2415 0.2257 0.8163 1.0974 0.2182 8.8632
-#> 301: 92.6102 -2.5556 -3.9913 2.2407 0.2255 0.8156 1.0972 0.2183 8.8600
-#> 302: 92.6102 -2.5551 -3.9916 2.2400 0.2252 0.8156 1.0966 0.2186 8.8586
-#> 303: 92.6099 -2.5546 -3.9915 2.2391 0.2250 0.8152 1.0978 0.2189 8.8589
-#> 304: 92.6096 -2.5541 -3.9913 2.2387 0.2242 0.8149 1.0987 0.2194 8.8570
-#> 305: 92.6100 -2.5538 -3.9914 2.2383 0.2247 0.8144 1.0995 0.2202 8.8553
-#> 306: 92.6109 -2.5533 -3.9915 2.2378 0.2255 0.8144 1.1001 0.2212 8.8531
-#> 307: 92.6119 -2.5529 -3.9913 2.2371 0.2252 0.8143 1.1007 0.2217 8.8498
-#> 308: 92.6128 -2.5525 -3.9912 2.2366 0.2249 0.8142 1.1012 0.2219 8.8490
-#> 309: 92.6143 -2.5519 -3.9905 2.2357 0.2251 0.8138 1.1018 0.2224 8.8449
-#> 310: 92.6160 -2.5513 -3.9900 2.2346 0.2255 0.8136 1.1020 0.2230 8.8403
-#> 311: 92.6177 -2.5506 -3.9891 2.2333 0.2258 0.8132 1.1031 0.2236 8.8392
-#> 312: 92.6190 -2.5499 -3.9881 2.2319 0.2267 0.8130 1.1047 0.2242 8.8382
-#> 313: 92.6192 -2.5493 -3.9872 2.2305 0.2273 0.8127 1.1057 0.2249 8.8350
-#> 314: 92.6196 -2.5490 -3.9864 2.2300 0.2279 0.8129 1.1067 0.2257 8.8315
-#> 315: 92.6197 -2.5488 -3.9858 2.2295 0.2277 0.8132 1.1072 0.2266 8.8285
-#> 316: 92.6192 -2.5485 -3.9850 2.2284 0.2276 0.8133 1.1087 0.2275 8.8278
-#> 317: 92.6190 -2.5482 -3.9840 2.2275 0.2278 0.8135 1.1105 0.2282 8.8296
-#> 318: 92.6193 -2.5480 -3.9833 2.2266 0.2274 0.8133 1.1120 0.2289 8.8313
-#> 319: 92.6200 -2.5476 -3.9827 2.2257 0.2265 0.8129 1.1133 0.2297 8.8326
-#> 320: 92.6211 -2.5472 -3.9820 2.2250 0.2260 0.8124 1.1150 0.2302 8.8359
-#> 321: 92.6226 -2.5468 -3.9816 2.2246 0.2254 0.8118 1.1158 0.2308 8.8396
-#> 322: 92.6238 -2.5464 -3.9808 2.2238 0.2249 0.8114 1.1169 0.2316 8.8424
-#> 323: 92.6248 -2.5461 -3.9805 2.2231 0.2241 0.8109 1.1173 0.2320 8.8458
-#> 324: 92.6252 -2.5458 -3.9801 2.2224 0.2233 0.8103 1.1182 0.2324 8.8474
-#> 325: 92.6248 -2.5455 -3.9799 2.2216 0.2225 0.8096 1.1192 0.2328 8.8507
-#> 326: 92.6247 -2.5451 -3.9802 2.2209 0.2216 0.8091 1.1186 0.2331 8.8519
-#> 327: 92.6248 -2.5446 -3.9806 2.2203 0.2203 0.8088 1.1179 0.2335 8.8535
-#> 328: 92.6242 -2.5442 -3.9808 2.2198 0.2196 0.8084 1.1175 0.2339 8.8533
-#> 329: 92.6234 -2.5437 -3.9809 2.2192 0.2188 0.8081 1.1176 0.2342 8.8550
-#> 330: 92.6229 -2.5433 -3.9806 2.2187 0.2182 0.8078 1.1187 0.2346 8.8574
-#> 331: 92.6220 -2.5429 -3.9801 2.2181 0.2183 0.8075 1.1210 0.2352 8.8599
-#> 332: 92.6214 -2.5425 -3.9796 2.2175 0.2185 0.8072 1.1235 0.2360 8.8612
-#> 333: 92.6215 -2.5421 -3.9794 2.2170 0.2184 0.8068 1.1248 0.2365 8.8660
-#> 334: 92.6218 -2.5417 -3.9795 2.2168 0.2180 0.8065 1.1257 0.2369 8.8675
-#> 335: 92.6220 -2.5413 -3.9793 2.2164 0.2177 0.8062 1.1269 0.2374 8.8683
-#> 336: 92.6228 -2.5410 -3.9792 2.2159 0.2173 0.8059 1.1275 0.2378 8.8707
-#> 337: 92.6244 -2.5405 -3.9792 2.2153 0.2175 0.8057 1.1278 0.2387 8.8734
-#> 338: 92.6266 -2.5401 -3.9792 2.2146 0.2184 0.8057 1.1283 0.2396 8.8757
-#> 339: 92.6290 -2.5398 -3.9790 2.2144 0.2191 0.8060 1.1294 0.2403 8.8770
-#> 340: 92.6309 -2.5396 -3.9790 2.2142 0.2200 0.8061 1.1295 0.2405 8.8766
-#> 341: 92.6328 -2.5394 -3.9788 2.2142 0.2211 0.8061 1.1300 0.2406 8.8752
-#> 342: 92.6347 -2.5392 -3.9788 2.2140 0.2223 0.8062 1.1291 0.2405 8.8744
-#> 343: 92.6365 -2.5390 -3.9787 2.2139 0.2233 0.8063 1.1288 0.2405 8.8732
-#> 344: 92.6383 -2.5388 -3.9785 2.2136 0.2242 0.8060 1.1295 0.2404 8.8730
-#> 345: 92.6392 -2.5386 -3.9781 2.2133 0.2248 0.8055 1.1303 0.2401 8.8737
-#> 346: 92.6401 -2.5384 -3.9780 2.2129 0.2249 0.8051 1.1302 0.2399 8.8739
-#> 347: 92.6411 -2.5381 -3.9777 2.2124 0.2248 0.8049 1.1302 0.2399 8.8794
-#> 348: 92.6427 -2.5380 -3.9777 2.2122 0.2251 0.8047 1.1306 0.2398 8.8814
-#> 349: 92.6444 -2.5378 -3.9777 2.2119 0.2252 0.8047 1.1304 0.2397 8.8834
-#> 350: 92.6462 -2.5376 -3.9776 2.2115 0.2260 0.8043 1.1300 0.2395 8.8859
-#> 351: 92.6470 -2.5375 -3.9772 2.2110 0.2265 0.8041 1.1303 0.2392 8.8883
-#> 352: 92.6478 -2.5373 -3.9772 2.2106 0.2266 0.8037 1.1293 0.2386 8.8926
-#> 353: 92.6493 -2.5373 -3.9772 2.2103 0.2268 0.8032 1.1285 0.2381 8.8928
-#> 354: 92.6504 -2.5372 -3.9772 2.2100 0.2264 0.8028 1.1274 0.2376 8.8946
-#> 355: 92.6512 -2.5370 -3.9771 2.2096 0.2267 0.8023 1.1273 0.2373 8.8951
-#> 356: 92.6522 -2.5367 -3.9767 2.2089 0.2275 0.8018 1.1272 0.2370 8.8947
-#> 357: 92.6534 -2.5364 -3.9765 2.2080 0.2290 0.8015 1.1268 0.2369 8.8932
-#> 358: 92.6545 -2.5362 -3.9761 2.2072 0.2301 0.8011 1.1270 0.2368 8.8919
-#> 359: 92.6566 -2.5360 -3.9757 2.2064 0.2310 0.8008 1.1269 0.2369 8.8928
-#> 360: 92.6584 -2.5358 -3.9751 2.2059 0.2311 0.8005 1.1272 0.2368 8.8924
-#> 361: 92.6611 -2.5356 -3.9744 2.2051 0.2317 0.8004 1.1280 0.2369 8.8932
-#> 362: 92.6639 -2.5353 -3.9740 2.2043 0.2321 0.8003 1.1284 0.2370 8.8914
-#> 363: 92.6662 -2.5349 -3.9733 2.2033 0.2328 0.8001 1.1289 0.2371 8.8902
-#> 364: 92.6679 -2.5345 -3.9729 2.2025 0.2325 0.7998 1.1292 0.2372 8.8883
-#> 365: 92.6695 -2.5341 -3.9725 2.2019 0.2321 0.7994 1.1297 0.2373 8.8865
-#> 366: 92.6709 -2.5337 -3.9722 2.2011 0.2321 0.7990 1.1297 0.2373 8.8860
-#> 367: 92.6724 -2.5334 -3.9720 2.2005 0.2317 0.7987 1.1295 0.2372 8.8848
-#> 368: 92.6736 -2.5330 -3.9719 2.1999 0.2314 0.7985 1.1288 0.2371 8.8844
-#> 369: 92.6745 -2.5326 -3.9717 2.1994 0.2310 0.7982 1.1283 0.2371 8.8840
-#> 370: 92.6758 -2.5323 -3.9714 2.1990 0.2312 0.7980 1.1283 0.2370 8.8854
-#> 371: 92.6776 -2.5321 -3.9708 2.1984 0.2313 0.7977 1.1286 0.2369 8.8852
-#> 372: 92.6791 -2.5317 -3.9704 2.1978 0.2311 0.7973 1.1282 0.2367 8.8865
-#> 373: 92.6804 -2.5312 -3.9701 2.1969 0.2308 0.7969 1.1280 0.2366 8.8884
-#> 374: 92.6814 -2.5308 -3.9699 2.1962 0.2305 0.7965 1.1279 0.2364 8.8898
-#> 375: 92.6827 -2.5304 -3.9698 2.1954 0.2305 0.7961 1.1271 0.2360 8.8938
-#> 376: 92.6832 -2.5301 -3.9695 2.1947 0.2301 0.7957 1.1268 0.2359 8.8930
-#> 377: 92.6835 -2.5298 -3.9692 2.1941 0.2300 0.7953 1.1269 0.2357 8.8933
-#> 378: 92.6831 -2.5295 -3.9693 2.1935 0.2303 0.7950 1.1266 0.2357 8.8990
-#> 379: 92.6827 -2.5293 -3.9694 2.1933 0.2307 0.7948 1.1265 0.2356 8.9027
-#> 380: 92.6826 -2.5291 -3.9695 2.1931 0.2307 0.7947 1.1262 0.2356 8.9045
-#> 381: 92.6822 -2.5290 -3.9695 2.1929 0.2307 0.7945 1.1259 0.2355 8.9040
-#> 382: 92.6817 -2.5289 -3.9694 2.1925 0.2305 0.7943 1.1258 0.2357 8.9033
-#> 383: 92.6812 -2.5288 -3.9695 2.1922 0.2305 0.7942 1.1255 0.2358 8.9045
-#> 384: 92.6810 -2.5288 -3.9695 2.1920 0.2302 0.7940 1.1253 0.2360 8.9058
-#> 385: 92.6806 -2.5287 -3.9694 2.1918 0.2301 0.7938 1.1254 0.2361 8.9052
-#> 386: 92.6801 -2.5286 -3.9692 2.1914 0.2298 0.7936 1.1256 0.2362 8.9039
-#> 387: 92.6800 -2.5285 -3.9687 2.1914 0.2294 0.7934 1.1261 0.2361 8.9032
-#> 388: 92.6801 -2.5284 -3.9683 2.1913 0.2293 0.7931 1.1267 0.2360 8.9027
-#> 389: 92.6802 -2.5283 -3.9684 2.1912 0.2288 0.7928 1.1261 0.2360 8.9028
-#> 390: 92.6805 -2.5281 -3.9684 2.1910 0.2283 0.7925 1.1258 0.2360 8.9044
-#> 391: 92.6806 -2.5280 -3.9685 2.1908 0.2285 0.7921 1.1254 0.2360 8.9047
-#> 392: 92.6810 -2.5278 -3.9682 2.1907 0.2288 0.7918 1.1257 0.2360 8.9057
-#> 393: 92.6810 -2.5275 -3.9681 2.1906 0.2290 0.7916 1.1257 0.2360 8.9049
-#> 394: 92.6811 -2.5272 -3.9682 2.1904 0.2292 0.7913 1.1253 0.2360 8.9056
-#> 395: 92.6812 -2.5269 -3.9682 2.1900 0.2295 0.7911 1.1251 0.2362 8.9044
-#> 396: 92.6817 -2.5269 -3.9683 2.1901 0.2292 0.7911 1.1251 0.2361 8.9031
-#> 397: 92.6824 -2.5269 -3.9686 2.1903 0.2292 0.7911 1.1250 0.2361 8.9043
-#> 398: 92.6828 -2.5270 -3.9688 2.1907 0.2291 0.7913 1.1248 0.2359 8.9035
-#> 399: 92.6829 -2.5271 -3.9689 2.1909 0.2292 0.7916 1.1248 0.2358 8.9043
-#> 400: 92.6829 -2.5273 -3.9688 2.1909 0.2295 0.7919 1.1250 0.2356 8.9037
-#> 401: 92.6827 -2.5274 -3.9687 2.1910 0.2299 0.7922 1.1249 0.2356 8.9035
-#> 402: 92.6822 -2.5276 -3.9687 2.1911 0.2303 0.7926 1.1248 0.2355 8.9033
-#> 403: 92.6821 -2.5277 -3.9686 2.1913 0.2307 0.7929 1.1250 0.2354 8.9009
-#> 404: 92.6817 -2.5279 -3.9684 2.1914 0.2314 0.7930 1.1249 0.2352 8.9012
-#> 405: 92.6813 -2.5281 -3.9683 2.1915 0.2318 0.7930 1.1252 0.2349 8.9015
-#> 406: 92.6811 -2.5283 -3.9680 2.1916 0.2321 0.7930 1.1255 0.2345 8.9019
-#> 407: 92.6817 -2.5285 -3.9677 2.1918 0.2329 0.7930 1.1255 0.2343 8.9014
-#> 408: 92.6824 -2.5287 -3.9675 2.1919 0.2330 0.7930 1.1253 0.2341 8.9019
-#> 409: 92.6833 -2.5289 -3.9674 2.1922 0.2331 0.7931 1.1249 0.2338 8.9031
-#> 410: 92.6840 -2.5291 -3.9673 2.1924 0.2331 0.7930 1.1245 0.2335 8.9054
-#> 411: 92.6848 -2.5292 -3.9672 2.1926 0.2333 0.7929 1.1243 0.2333 8.9083
-#> 412: 92.6852 -2.5293 -3.9671 2.1928 0.2333 0.7931 1.1243 0.2333 8.9107
-#> 413: 92.6858 -2.5293 -3.9671 2.1929 0.2332 0.7932 1.1246 0.2332 8.9119
-#> 414: 92.6863 -2.5293 -3.9671 2.1928 0.2332 0.7934 1.1252 0.2333 8.9112
-#> 415: 92.6868 -2.5293 -3.9671 2.1928 0.2330 0.7935 1.1253 0.2332 8.9109
-#> 416: 92.6872 -2.5293 -3.9672 2.1928 0.2327 0.7935 1.1247 0.2330 8.9101
-#> 417: 92.6875 -2.5293 -3.9674 2.1929 0.2324 0.7934 1.1241 0.2330 8.9126
-#> 418: 92.6881 -2.5294 -3.9675 2.1929 0.2322 0.7935 1.1238 0.2332 8.9148
-#> 419: 92.6885 -2.5295 -3.9674 2.1929 0.2322 0.7936 1.1236 0.2331 8.9179
-#> 420: 92.6890 -2.5297 -3.9674 2.1929 0.2322 0.7936 1.1235 0.2331 8.9194
-#> 421: 92.6891 -2.5299 -3.9672 2.1930 0.2318 0.7937 1.1236 0.2330 8.9192
-#> 422: 92.6894 -2.5301 -3.9670 2.1930 0.2318 0.7937 1.1239 0.2329 8.9183
-#> 423: 92.6898 -2.5302 -3.9667 2.1931 0.2318 0.7937 1.1242 0.2327 8.9190
-#> 424: 92.6905 -2.5304 -3.9667 2.1931 0.2316 0.7937 1.1243 0.2326 8.9190
-#> 425: 92.6910 -2.5305 -3.9667 2.1932 0.2316 0.7936 1.1240 0.2327 8.9203
-#> 426: 92.6917 -2.5306 -3.9668 2.1935 0.2318 0.7937 1.1237 0.2326 8.9200
-#> 427: 92.6918 -2.5308 -3.9671 2.1939 0.2322 0.7938 1.1227 0.2326 8.9224
-#> 428: 92.6912 -2.5310 -3.9670 2.1941 0.2319 0.7939 1.1225 0.2325 8.9268
-#> 429: 92.6912 -2.5312 -3.9670 2.1944 0.2316 0.7939 1.1225 0.2324 8.9301
-#> 430: 92.6910 -2.5314 -3.9674 2.1948 0.2314 0.7940 1.1217 0.2322 8.9314
-#> 431: 92.6911 -2.5315 -3.9675 2.1950 0.2314 0.7942 1.1210 0.2320 8.9320
-#> 432: 92.6911 -2.5316 -3.9677 2.1953 0.2312 0.7944 1.1204 0.2320 8.9327
-#> 433: 92.6910 -2.5317 -3.9681 2.1955 0.2309 0.7946 1.1196 0.2320 8.9336
-#> 434: 92.6910 -2.5318 -3.9683 2.1957 0.2306 0.7949 1.1188 0.2320 8.9337
-#> 435: 92.6912 -2.5319 -3.9687 2.1960 0.2302 0.7951 1.1178 0.2319 8.9343
-#> 436: 92.6914 -2.5320 -3.9688 2.1961 0.2300 0.7953 1.1173 0.2319 8.9345
-#> 437: 92.6919 -2.5321 -3.9688 2.1962 0.2299 0.7955 1.1168 0.2318 8.9335
-#> 438: 92.6920 -2.5323 -3.9688 2.1964 0.2296 0.7957 1.1164 0.2318 8.9334
-#> 439: 92.6917 -2.5324 -3.9689 2.1965 0.2292 0.7959 1.1165 0.2317 8.9322
-#> 440: 92.6910 -2.5326 -3.9688 2.1969 0.2289 0.7960 1.1170 0.2316 8.9319
-#> 441: 92.6907 -2.5328 -3.9688 2.1973 0.2283 0.7961 1.1175 0.2316 8.9317
-#> 442: 92.6909 -2.5330 -3.9689 2.1976 0.2280 0.7962 1.1174 0.2315 8.9326
-#> 443: 92.6911 -2.5332 -3.9689 2.1980 0.2277 0.7963 1.1180 0.2315 8.9338
-#> 444: 92.6906 -2.5332 -3.9690 2.1981 0.2275 0.7963 1.1181 0.2315 8.9354
-#> 445: 92.6897 -2.5333 -3.9691 2.1982 0.2276 0.7962 1.1181 0.2315 8.9364
-#> 446: 92.6896 -2.5333 -3.9692 2.1982 0.2272 0.7962 1.1176 0.2314 8.9363
-#> 447: 92.6893 -2.5334 -3.9693 2.1982 0.2272 0.7961 1.1173 0.2313 8.9365
-#> 448: 92.6890 -2.5334 -3.9693 2.1982 0.2271 0.7961 1.1173 0.2313 8.9364
-#> 449: 92.6888 -2.5335 -3.9693 2.1982 0.2267 0.7961 1.1170 0.2313 8.9372
-#> 450: 92.6884 -2.5335 -3.9693 2.1982 0.2262 0.7959 1.1166 0.2312 8.9364
-#> 451: 92.6885 -2.5335 -3.9691 2.1981 0.2261 0.7958 1.1167 0.2312 8.9350
-#> 452: 92.6887 -2.5335 -3.9691 2.1980 0.2260 0.7957 1.1164 0.2311 8.9349
-#> 453: 92.6888 -2.5335 -3.9691 2.1979 0.2258 0.7957 1.1163 0.2310 8.9375
-#> 454: 92.6890 -2.5335 -3.9689 2.1977 0.2258 0.7957 1.1160 0.2308 8.9385
-#> 455: 92.6894 -2.5334 -3.9687 2.1975 0.2259 0.7956 1.1158 0.2307 8.9382
-#> 456: 92.6898 -2.5334 -3.9685 2.1974 0.2261 0.7957 1.1154 0.2306 8.9380
-#> 457: 92.6904 -2.5334 -3.9685 2.1975 0.2265 0.7956 1.1146 0.2304 8.9391
-#> 458: 92.6908 -2.5334 -3.9687 2.1975 0.2266 0.7956 1.1137 0.2303 8.9418
-#> 459: 92.6911 -2.5335 -3.9689 2.1975 0.2270 0.7956 1.1129 0.2303 8.9442
-#> 460: 92.6912 -2.5335 -3.9687 2.1976 0.2274 0.7957 1.1126 0.2301 8.9461
-#> 461: 92.6913 -2.5336 -3.9687 2.1975 0.2276 0.7958 1.1125 0.2300 8.9463
-#> 462: 92.6914 -2.5336 -3.9686 2.1974 0.2280 0.7959 1.1126 0.2299 8.9456
-#> 463: 92.6917 -2.5336 -3.9684 2.1973 0.2280 0.7960 1.1127 0.2297 8.9452
-#> 464: 92.6918 -2.5336 -3.9683 2.1970 0.2280 0.7961 1.1127 0.2295 8.9444
-#> 465: 92.6921 -2.5336 -3.9682 2.1967 0.2277 0.7962 1.1127 0.2294 8.9447
-#> 466: 92.6924 -2.5336 -3.9679 2.1967 0.2275 0.7964 1.1127 0.2291 8.9454
-#> 467: 92.6930 -2.5336 -3.9677 2.1966 0.2273 0.7967 1.1128 0.2290 8.9453
-#> 468: 92.6935 -2.5337 -3.9675 2.1966 0.2275 0.7970 1.1128 0.2289 8.9458
-#> 469: 92.6937 -2.5338 -3.9676 2.1967 0.2278 0.7972 1.1123 0.2287 8.9455
-#> 470: 92.6938 -2.5338 -3.9677 2.1967 0.2283 0.7974 1.1122 0.2285 8.9451
-#> 471: 92.6940 -2.5339 -3.9676 2.1969 0.2290 0.7976 1.1124 0.2283 8.9448
-#> 472: 92.6938 -2.5339 -3.9676 2.1972 0.2293 0.7977 1.1125 0.2281 8.9460
-#> 473: 92.6937 -2.5340 -3.9676 2.1972 0.2298 0.7978 1.1121 0.2278 8.9461
-#> 474: 92.6934 -2.5341 -3.9677 2.1974 0.2308 0.7978 1.1118 0.2276 8.9470
-#> 475: 92.6936 -2.5342 -3.9677 2.1978 0.2316 0.7979 1.1113 0.2273 8.9486
-#> 476: 92.6940 -2.5345 -3.9679 2.1983 0.2324 0.7981 1.1106 0.2271 8.9491
-#> 477: 92.6945 -2.5347 -3.9681 2.1989 0.2332 0.7983 1.1099 0.2269 8.9502
-#> 478: 92.6951 -2.5349 -3.9682 2.1992 0.2344 0.7986 1.1093 0.2267 8.9502
-#> 479: 92.6958 -2.5352 -3.9683 2.1995 0.2357 0.7987 1.1088 0.2266 8.9521
-#> 480: 92.6967 -2.5354 -3.9684 2.1998 0.2370 0.7988 1.1083 0.2265 8.9524
-#> 481: 92.6977 -2.5355 -3.9685 2.2001 0.2383 0.7990 1.1079 0.2263 8.9521
-#> 482: 92.6985 -2.5357 -3.9687 2.2004 0.2395 0.7992 1.1073 0.2262 8.9518
-#> 483: 92.6992 -2.5359 -3.9690 2.2008 0.2403 0.7995 1.1066 0.2262 8.9524
-#> 484: 92.7000 -2.5361 -3.9691 2.2010 0.2406 0.7998 1.1061 0.2260 8.9516
-#> 485: 92.7009 -2.5362 -3.9693 2.2015 0.2410 0.8001 1.1057 0.2261 8.9508
-#> 486: 92.7010 -2.5363 -3.9695 2.2019 0.2412 0.8004 1.1051 0.2261 8.9502
-#> 487: 92.7008 -2.5365 -3.9698 2.2023 0.2413 0.8009 1.1048 0.2260 8.9502
-#> 488: 92.7006 -2.5366 -3.9700 2.2026 0.2411 0.8012 1.1044 0.2260 8.9501
-#> 489: 92.7006 -2.5367 -3.9701 2.2029 0.2410 0.8015 1.1041 0.2261 8.9504
-#> 490: 92.7006 -2.5368 -3.9702 2.2031 0.2407 0.8015 1.1043 0.2260 8.9498
-#> 491: 92.7007 -2.5369 -3.9701 2.2034 0.2405 0.8016 1.1047 0.2261 8.9484
-#> 492: 92.7008 -2.5370 -3.9702 2.2035 0.2406 0.8017 1.1046 0.2261 8.9473
-#> 493: 92.7010 -2.5370 -3.9704 2.2037 0.2406 0.8018 1.1044 0.2261 8.9469
-#> 494: 92.7015 -2.5371 -3.9707 2.2038 0.2408 0.8019 1.1040 0.2261 8.9453
-#> 495: 92.7017 -2.5371 -3.9708 2.2039 0.2407 0.8021 1.1042 0.2262 8.9447
-#> 496: 92.7016 -2.5371 -3.9708 2.2039 0.2407 0.8022 1.1042 0.2262 8.9433
-#> 497: 92.7015 -2.5371 -3.9709 2.2039 0.2408 0.8023 1.1044 0.2262 8.9431
-#> 498: 92.7013 -2.5371 -3.9709 2.2040 0.2409 0.8024 1.1047 0.2262 8.9452
-#> 499: 92.7011 -2.5371 -3.9710 2.2039 0.2409 0.8023 1.1049 0.2261 8.9481
-#> 500: 92.7010 -2.5371 -3.9712 2.2040 0.2412 0.8022 1.1049 0.2260 8.9498
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#>
Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> | #| Objective Fun | parent_0 | log_k1 | log_k2 | log_tb |
-#> |.....................| sigma | o1 | o2 | o3 |
-#>
|.....................| o4 |...........|...........|...........|
-#> |
1| 360.27275 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 360.27275 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
360.27275 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | G| Gill Diff. | 106.2 | 0.7918 | 0.06750 | 10.50 |
-#> |.....................| -26.04 | 2.358 | -5.196 | -2.491 |
-#>
|.....................| -12.13 |...........|...........|...........|
-#> |
2| 7055.7467 | 0.04059 | -0.9733 | -1.001 | -0.9739 |
-#> |.....................| -0.6317 | -0.9263 | -0.8528 | -0.8784 |
-#>
|.....................| -0.7843 |...........|...........|...........|
-#> | U| 7055.7467 | 3.818 | -2.236 | -3.887 | 1.944 |
-#> |.....................| 2.941 | 0.7466 | 1.074 | 0.9892 |
-#>
|.....................| 1.458 |...........|...........|...........|
-#> | X|
7055.7467 | 3.818 | 0.1069 | 0.02050 | 6.988 |
-#> |.....................| 2.941 | 0.7466 | 1.074 | 0.9892 |
-#>
|.....................| 1.458 |...........|...........|...........|
-#> |
3| 499.76989 | 0.9041 | -0.9669 | -1.000 | -0.8885 |
-#> |.....................| -0.8434 | -0.9072 | -0.8950 | -0.8986 |
-#>
|.....................| -0.8828 |...........|...........|...........|
-#> | U| 499.76989 | 85.03 | -2.229 | -3.887 | 2.030 |
-#> |.....................| 2.663 | 0.7612 | 1.031 | 0.9696 |
-#>
|.....................| 1.329 |...........|...........|...........|
-#> | X|
499.76989 | 85.03 | 0.1076 | 0.02051 | 7.611 |
-#> |.....................| 2.663 | 0.7612 | 1.031 | 0.9696 |
-#>
|.....................| 1.329 |...........|...........|...........|
-#> |
4| 360.48011 | 0.9904 | -0.9662 | -1.000 | -0.8799 |
-#> |.....................| -0.8645 | -0.9053 | -0.8992 | -0.9007 |
-#>
|.....................| -0.8927 |...........|...........|...........|
-#> | U| 360.48011 | 93.15 | -2.229 | -3.887 | 2.038 |
-#> |.....................| 2.635 | 0.7627 | 1.026 | 0.9677 |
-#>
|.....................| 1.316 |...........|...........|...........|
-#> | X|
360.48011 | 93.15 | 0.1077 | 0.02051 | 7.676 |
-#> |.....................| 2.635 | 0.7627 | 1.026 | 0.9677 |
-#>
|.....................| 1.316 |...........|...........|...........|
-#> |
5| 360.80998 | 0.9960 | -0.9662 | -1.000 | -0.8794 |
-#> |.....................| -0.8659 | -0.9051 | -0.8995 | -0.9008 |
-#>
|.....................| -0.8933 |...........|...........|...........|
-#> | U| 360.80998 | 93.68 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.633 | 0.7628 | 1.026 | 0.9676 |
-#>
|.....................| 1.315 |...........|...........|...........|
-#> | X|
360.80998 | 93.68 | 0.1077 | 0.02051 | 7.680 |
-#> |.....................| 2.633 | 0.7628 | 1.026 | 0.9676 |
-#>
|.....................| 1.315 |...........|...........|...........|
-#> |
6| 361.20154 | 0.9991 | -0.9661 | -1.000 | -0.8791 |
-#> |.....................| -0.8667 | -0.9051 | -0.8996 | -0.9009 |
-#>
|.....................| -0.8937 |...........|...........|...........|
-#> | U| 361.20154 | 93.97 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.315 |...........|...........|...........|
-#> | X|
361.20154 | 93.97 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.315 |...........|...........|...........|
-#> |
7| 361.33469 | 0.9999 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.33469 | 94.05 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.33469 | 94.05 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
8| 361.34878 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.34878 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.34878 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
9| 361.35091 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35091 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35091 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
10| 361.35004 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35004 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35004 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
11| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
12| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
13| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
14| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
15| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
16| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
17| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> |
18| 361.35006 | 1.000 | -0.9661 | -1.000 | -0.8790 |
-#> |.....................| -0.8669 | -0.9051 | -0.8997 | -0.9009 |
-#>
|.....................| -0.8938 |...........|...........|...........|
-#> | U| 361.35006 | 94.06 | -2.229 | -3.887 | 2.039 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> | X|
361.35006 | 94.06 | 0.1077 | 0.02051 | 7.683 |
-#> |.....................| 2.632 | 0.7629 | 1.026 | 0.9675 |
-#>
|.....................| 1.314 |...........|...........|...........|
-#> calculating covariance matrix
+
f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS",
], est
= "saem",
+ control
= saemControl(print
= 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 92.2167 0.0936 1.9256 3.3974 0.7958 0.7197 11.8539 0.0004
-#> 2: 92.5446 0.0892 2.4952 3.3516 0.8528 0.6837 4.5197 0.0001
-#> 3: 9.2720e+01 1.3849e-01 2.5917e+00 3.9204e+00 9.5883e-01 6.4953e-01 4.0268e+00 5.9554e-05
-#> 4: 92.6098 0.1052 2.5494 5.0533 1.0968 0.6171 3.2396 0.0200
-#> 5: 92.6795 0.0406 2.4151 5.6729 1.0420 0.5862 3.1558 0.0183
-#> 6: 92.6580 0.0258 2.3640 5.7014 0.9899 0.5569 3.0212 0.0140
-#> 7: 93.0532 -0.0754 2.2262 7.3582 0.9404 0.5291 2.5591 0.0180
-#> 8: 92.8372 -0.0760 2.2080 6.9903 0.8934 0.5026 2.5653 0.0187
-#> 9: 93.0757 -0.1322 2.1663 6.6408 0.8487 0.4775 2.4943 0.0182
-#> 10: 93.0704 -0.1520 2.1410 6.3087 0.8063 0.4536 2.4004 0.0225
-#> 11: 93.1611 -0.1366 2.1740 5.9933 0.7659 0.4309 2.4242 0.0199
-#> 12: 92.7195 -0.0787 2.2947 5.6936 0.7277 0.4094 2.4532 0.0205
-#> 13: 92.6573 -0.1543 2.1929 5.4089 0.6913 0.3889 2.3750 0.0244
-#> 14: 93.1138 -0.1547 2.1924 5.1385 0.6567 0.3695 2.3590 0.0187
-#> 15: 93.5083 -0.1625 2.1831 4.8816 0.6239 0.3510 2.4420 0.0125
-#> 16: 93.2086 -0.1667 2.1516 4.6375 0.5927 0.3334 2.4527 0.0004
-#> 17: 93.3988 -0.1766 2.1521 4.4056 0.5630 0.3168 2.4527 0.0004
-#> 18: 93.4526 -0.1748 2.1461 4.1853 0.5349 0.3009 2.3775 0.0116
-#> 19: 93.5953 -0.1963 2.1167 3.9761 0.5081 0.2859 2.4693 0.0031
-#> 20: 9.3404e+01 -2.4408e-01 2.0453e+00 3.7773e+00 4.8274e-01 2.7158e-01 2.4789e+00 2.0760e-05
-#> 21: 9.3624e+01 -2.4691e-01 2.0524e+00 3.5884e+00 4.5860e-01 2.5800e-01 2.4789e+00 2.0760e-05
-#> 22: 9.3821e+01 -2.5932e-01 2.0021e+00 3.4090e+00 4.3567e-01 2.8670e-01 2.4182e+00 9.3297e-06
-#> 23: 9.3572e+01 -2.3703e-01 2.0725e+00 3.2385e+00 4.4889e-01 2.7237e-01 2.4525e+00 1.5592e-06
-#> 24: 9.3496e+01 -2.2704e-01 2.0746e+00 3.0766e+00 4.3674e-01 2.5875e-01 2.4569e+00 6.1365e-05
-#> 25: 9.3772e+01 -2.2211e-01 2.0762e+00 2.9228e+00 4.4843e-01 2.6194e-01 2.4015e+00 8.3288e-05
-#> 26: 9.3266e+01 -1.9408e-01 2.1345e+00 2.7766e+00 4.6952e-01 2.4885e-01 2.3827e+00 2.9029e-05
-#> 27: 9.3472e+01 -1.9793e-01 2.1141e+00 3.5922e+00 4.7687e-01 2.3640e-01 2.3827e+00 2.9029e-05
-#> 28: 9.3411e+01 -1.7721e-01 2.1334e+00 3.4125e+00 4.8209e-01 2.2458e-01 2.3864e+00 6.5503e-06
-#> 29: 93.6868 -0.1863 2.1258 4.5379 0.4744 0.2134 2.3001 0.0045
-#> 30: 9.4054e+01 -1.8122e-01 2.1287e+00 4.9729e+00 4.7945e-01 2.0269e-01 2.2979e+00 5.8327e-05
-#> 31: 9.3955e+01 -1.9131e-01 2.1202e+00 5.6375e+00 4.7965e-01 1.9255e-01 2.2671e+00 1.6931e-05
-#> 32: 9.4376e+01 -1.6810e-01 2.1287e+00 5.3556e+00 4.7567e-01 1.8972e-01 2.2483e+00 1.1778e-05
-#> 33: 9.4067e+01 -1.5819e-01 2.1656e+00 5.0878e+00 4.5710e-01 1.9389e-01 2.2696e+00 2.4282e-05
-#> 34: 9.4526e+01 -1.6367e-01 2.1473e+00 4.8334e+00 4.7085e-01 1.8419e-01 2.2919e+00 8.8644e-06
-#> 35: 9.4972e+01 -1.6784e-01 2.1353e+00 4.5917e+00 4.7510e-01 1.7498e-01 2.3129e+00 2.2851e-05
-#> 36: 9.4744e+01 -1.5973e-01 2.1281e+00 5.2356e+00 4.5695e-01 1.8499e-01 2.2896e+00 6.8824e-05
-#> 37: 9.4721e+01 -1.6756e-01 2.1168e+00 5.1111e+00 4.6804e-01 1.8407e-01 2.3035e+00 1.5534e-06
-#> 38: 9.4613e+01 -1.5952e-01 2.1385e+00 4.8555e+00 4.6107e-01 1.7720e-01 2.2650e+00 1.2489e-05
-#> 39: 9.4787e+01 -1.6113e-01 2.1458e+00 4.6128e+00 4.6317e-01 1.8378e-01 2.2831e+00 1.3668e-05
-#> 40: 94.5315 -0.1765 2.1186 4.3821 0.4428 0.1902 2.3132 0.0001
-#> 41: 9.4336e+01 -1.8333e-01 2.1285e+00 4.1630e+00 4.4521e-01 1.9913e-01 2.3092e+00 1.3482e-05
-#> 42: 94.0780 -0.2031 2.0724 3.9549 0.4405 0.1892 2.2704 0.0056
-#> 43: 93.9276 -0.1896 2.1191 3.7571 0.4590 0.1797 2.2396 0.0080
-#> 44: 94.2491 -0.1896 2.1006 3.8473 0.4590 0.1764 2.2774 0.0083
-#> 45: 94.4073 -0.1811 2.1156 3.6550 0.4519 0.1676 2.2682 0.0078
-#> 46: 93.9736 -0.1882 2.1196 3.4722 0.4545 0.1633 2.2775 0.0035
-#> 47: 94.1930 -0.1965 2.1102 3.2986 0.4599 0.1664 2.3243 0.0005
-#> 48: 9.4147e+01 -1.9494e-01 2.1118e+00 3.3188e+00 4.7005e-01 1.7181e-01 2.3345e+00 1.1669e-05
-#> 49: 9.4139e+01 -1.7920e-01 2.1199e+00 3.1528e+00 4.7417e-01 1.6322e-01 2.2794e+00 3.5582e-05
-#> 50: 9.4031e+01 -1.9074e-01 2.1098e+00 2.9952e+00 4.7498e-01 1.6695e-01 2.2574e+00 2.7302e-06
-#> 51: 9.3982e+01 -1.9369e-01 2.1058e+00 2.8848e+00 4.8158e-01 1.8408e-01 2.2447e+00 1.8188e-05
-#> 52: 9.3924e+01 -2.0726e-01 2.0809e+00 3.6064e+00 4.7008e-01 2.0029e-01 2.2319e+00 6.8301e-06
-#> 53: 9.4094e+01 -1.9609e-01 2.0780e+00 4.4341e+00 4.7556e-01 1.9742e-01 2.2701e+00 2.1343e-06
-#> 54: 9.4351e+01 -1.9839e-01 2.0746e+00 4.2124e+00 4.7456e-01 1.8866e-01 2.2778e+00 4.8058e-06
-#> 55: 93.9450 -0.1876 2.1059 4.0017 0.4892 0.1792 2.2720 0.0001
-#> 56: 9.3741e+01 -1.8208e-01 2.1172e+00 3.8017e+00 4.7696e-01 1.7027e-01 2.2332e+00 2.1237e-05
-#> 57: 9.3668e+01 -1.8580e-01 2.1181e+00 3.9224e+00 4.7704e-01 1.7425e-01 2.2512e+00 2.2766e-05
-#> 58: 9.3811e+01 -1.8324e-01 2.1178e+00 3.7263e+00 4.7945e-01 1.7939e-01 2.2512e+00 2.2766e-05
-#> 59: 9.3800e+01 -1.6691e-01 2.1250e+00 3.8213e+00 4.9353e-01 1.8464e-01 2.2763e+00 4.6129e-06
-#> 60: 9.3997e+01 -1.5920e-01 2.1489e+00 3.6303e+00 5.0788e-01 1.7541e-01 2.2466e+00 4.1975e-06
-#> 61: 9.4215e+01 -1.6445e-01 2.1482e+00 3.9303e+00 5.1966e-01 1.6664e-01 2.3053e+00 5.8982e-07
-#> 62: 9.3936e+01 -1.6721e-01 2.1376e+00 4.0316e+00 5.3719e-01 1.7228e-01 2.2841e+00 7.8603e-05
-#> 63: 9.3832e+01 -1.6209e-01 2.1334e+00 3.8698e+00 5.4370e-01 1.7064e-01 2.3046e+00 6.4415e-07
-#> 64: 93.9042 -0.1617 2.1563 5.5384 0.5430 0.1622 2.2988 0.0002
-#> 65: 93.8613 -0.1723 2.1239 6.2143 0.5304 0.1541 2.2949 0.0001
-#> 66: 9.4113e+01 -1.9168e-01 2.1019e+00 7.3588e+00 5.1287e-01 1.4641e-01 2.3164e+00 1.2580e-05
-#> 67: 9.3954e+01 -1.8141e-01 2.1199e+00 6.9909e+00 5.0278e-01 1.4993e-01 2.2676e+00 1.1126e-05
-#> 68: 93.8741 -0.1852 2.1343 6.6414 0.4997 0.1493 2.2706 0.0001
-#> 69: 9.3657e+01 -1.8345e-01 2.1375e+00 6.3093e+00 5.0292e-01 1.6326e-01 2.2809e+00 1.7299e-07
-#> 70: 9.3762e+01 -1.7493e-01 2.1512e+00 5.9938e+00 5.1042e-01 1.5509e-01 2.2837e+00 4.5745e-05
-#> 71: 9.4060e+01 -1.6516e-01 2.1440e+00 5.6941e+00 5.1615e-01 1.4734e-01 2.3001e+00 3.9993e-07
-#> 72: 9.3927e+01 -1.7365e-01 2.1347e+00 5.4094e+00 5.2582e-01 1.3997e-01 2.3075e+00 6.3748e-06
-#> 73: 9.4049e+01 -1.8080e-01 2.1254e+00 5.1390e+00 5.1154e-01 1.3297e-01 2.3042e+00 9.5858e-06
-#> 74: 9.3917e+01 -1.9083e-01 2.1051e+00 4.8820e+00 5.0104e-01 1.4605e-01 2.2733e+00 7.4923e-05
-#> 75: 9.4271e+01 -1.8281e-01 2.1059e+00 5.0872e+00 5.0773e-01 1.5322e-01 2.2387e+00 1.4240e-05
-#> 76: 9.4205e+01 -1.8352e-01 2.1160e+00 4.8328e+00 5.0684e-01 1.5669e-01 2.2708e+00 3.6346e-05
-#> 77: 9.4480e+01 -1.8352e-01 2.0942e+00 4.9009e+00 5.0684e-01 1.4885e-01 2.3098e+00 1.8186e-06
-#> 78: 9.4699e+01 -1.9686e-01 2.0671e+00 4.6559e+00 4.9182e-01 1.4503e-01 2.2806e+00 7.9443e-08
-#> 79: 9.4785e+01 -2.0649e-01 2.0500e+00 6.0608e+00 4.6723e-01 1.6185e-01 2.2607e+00 2.1557e-07
-#> 80: 9.4782e+01 -2.0045e-01 2.0680e+00 5.7578e+00 4.5759e-01 1.5747e-01 2.2926e+00 8.6381e-06
-#> 81: 9.4339e+01 -2.0435e-01 2.0885e+00 6.9051e+00 4.5054e-01 1.7410e-01 2.2796e+00 1.5517e-05
-#> 82: 9.4805e+01 -2.1032e-01 2.0658e+00 7.1580e+00 4.7091e-01 1.6539e-01 2.3013e+00 1.3893e-05
-#> 83: 9.4650e+01 -2.0507e-01 2.0485e+00 6.8001e+00 4.7624e-01 1.5938e-01 2.3104e+00 6.6569e-06
-#> 84: 9.4766e+01 -1.9959e-01 2.0667e+00 6.4601e+00 4.7322e-01 1.5619e-01 2.3359e+00 1.8890e-09
-#> 85: 9.4714e+01 -1.9959e-01 2.0756e+00 6.1371e+00 4.7322e-01 1.6894e-01 2.2738e+00 4.9578e-06
-#> 86: 9.4466e+01 -2.0544e-01 2.0626e+00 5.8302e+00 4.6340e-01 1.6050e-01 2.2773e+00 3.6221e-07
-#> 87: 9.4786e+01 -1.9292e-01 2.0703e+00 5.5387e+00 4.6881e-01 1.5641e-01 2.2746e+00 2.3326e-05
-#> 88: 9.4573e+01 -1.9488e-01 2.0597e+00 5.2618e+00 4.6538e-01 1.5079e-01 2.3225e+00 4.7054e-05
-#> 89: 94.8466 -0.2040 2.0603 4.9987 0.4620 0.1456 2.2807 0.0002
-#> 90: 9.4839e+01 -2.0359e-01 2.0673e+00 4.7488e+00 4.5379e-01 1.4729e-01 2.3099e+00 2.7922e-05
-#> 91: 9.4897e+01 -2.0635e-01 2.0496e+00 4.5113e+00 4.4018e-01 1.3993e-01 2.2924e+00 1.7074e-05
-#> 92: 9.4740e+01 -2.0567e-01 2.0518e+00 4.2858e+00 4.6190e-01 1.3293e-01 2.3396e+00 9.0471e-05
-#> 93: 94.9558 -0.2033 2.0824 4.0715 0.4877 0.1263 2.3785 0.0082
-#> 94: 95.1673 -0.1801 2.0900 3.8679 0.5150 0.1200 2.4128 0.0106
-#> 95: 95.3129 -0.1686 2.1057 3.6745 0.4892 0.1140 2.4135 0.0147
-#> 96: 9.5235e+01 -1.6834e-01 2.1069e+00 3.4908e+00 4.9584e-01 1.0827e-01 2.4408e+00 2.5829e-06
-#> 97: 9.4892e+01 -1.5911e-01 2.1277e+00 3.3162e+00 4.7518e-01 1.0286e-01 2.4658e+00 1.8589e-05
-#> 98: 9.4749e+01 -1.6133e-01 2.1204e+00 4.5926e+00 4.6435e-01 1.0192e-01 2.4716e+00 5.8808e-09
-#> 99: 9.4546e+01 -1.5627e-01 2.1358e+00 5.5648e+00 4.8843e-01 1.0047e-01 2.5033e+00 2.5865e-05
-#> 100: 9.4544e+01 -1.6341e-01 2.1317e+00 5.2974e+00 4.7076e-01 1.1065e-01 2.4711e+00 4.4438e-05
-#> 101: 94.2461 -0.1640 2.1458 5.0325 0.4750 0.1107 2.5297 0.0002
-#> 102: 9.4039e+01 -1.6946e-01 2.1490e+00 4.9929e+00 4.7265e-01 1.2109e-01 2.3907e+00 2.3093e-05
-#> 103: 9.4132e+01 -1.6840e-01 2.1250e+00 5.3879e+00 4.7062e-01 1.2389e-01 2.3401e+00 5.4840e-07
-#> 104: 9.4376e+01 -1.6842e-01 2.1239e+00 7.9826e+00 4.7053e-01 1.1769e-01 2.3663e+00 1.9617e-05
-#> 105: 9.4370e+01 -1.7024e-01 2.1187e+00 7.5834e+00 4.6738e-01 1.1683e-01 2.3471e+00 1.4035e-05
-#> 106: 9.4462e+01 -1.6562e-01 2.1406e+00 7.5466e+00 4.6364e-01 1.2640e-01 2.3140e+00 4.7933e-05
-#> 107: 9.4541e+01 -1.6582e-01 2.1308e+00 7.1692e+00 4.6457e-01 1.2964e-01 2.3395e+00 1.8489e-05
-#> 108: 9.4709e+01 -1.6157e-01 2.1484e+00 6.8108e+00 4.5925e-01 1.3393e-01 2.3340e+00 1.5230e-06
-#> 109: 9.4450e+01 -1.8900e-01 2.0799e+00 6.4702e+00 4.4801e-01 1.4728e-01 2.3847e+00 3.2613e-05
-#> 110: 9.4180e+01 -1.9104e-01 2.1172e+00 6.1467e+00 4.5389e-01 1.4273e-01 2.3775e+00 6.0285e-05
-#> 111: 9.4366e+01 -1.8908e-01 2.1031e+00 5.8394e+00 4.4875e-01 1.4983e-01 2.3898e+00 7.2653e-05
-#> 112: 9.4008e+01 -1.8144e-01 2.1008e+00 5.5474e+00 4.6433e-01 1.4234e-01 2.3705e+00 9.9395e-06
-#> 113: 9.4372e+01 -1.8885e-01 2.1154e+00 5.2700e+00 4.7983e-01 1.3522e-01 2.3641e+00 1.8643e-05
-#> 114: 94.1292 -0.1872 2.1134 5.0065 0.4824 0.1285 2.3163 0.0001
-#> 115: 9.4510e+01 -1.7805e-01 2.1185e+00 4.7562e+00 4.8451e-01 1.2204e-01 2.3568e+00 1.6277e-07
-#> 116: 9.4234e+01 -1.8613e-01 2.1214e+00 4.5184e+00 4.7967e-01 1.2275e-01 2.3388e+00 3.4361e-05
-#> 117: 9.4438e+01 -1.7276e-01 2.1218e+00 4.2925e+00 4.6200e-01 1.1662e-01 2.3686e+00 5.6594e-06
-#> 118: 9.4498e+01 -1.7628e-01 2.1143e+00 6.2395e+00 4.5445e-01 1.2378e-01 2.3303e+00 6.5645e-05
-#> 119: 9.4303e+01 -1.8107e-01 2.1120e+00 7.5774e+00 4.6102e-01 1.2829e-01 2.3595e+00 9.4057e-06
-#> 120: 9.4022e+01 -1.7626e-01 2.1258e+00 9.9044e+00 4.6505e-01 1.5188e-01 2.3582e+00 3.6907e-05
-#> 121: 9.4103e+01 -1.5976e-01 2.1354e+00 9.4091e+00 4.7792e-01 1.5429e-01 2.3729e+00 4.6749e-05
-#> 122: 9.4727e+01 -1.9092e-01 2.0956e+00 8.9387e+00 4.5402e-01 1.6371e-01 2.3118e+00 6.8573e-06
-#> 123: 9.4447e+01 -1.9139e-01 2.0898e+00 8.4918e+00 4.3317e-01 1.7569e-01 2.3083e+00 4.4068e-05
-#> 124: 9.4422e+01 -1.9130e-01 2.0920e+00 8.0672e+00 4.3952e-01 1.7160e-01 2.3003e+00 1.7162e-05
-#> 125: 9.4608e+01 -1.7777e-01 2.1007e+00 7.6638e+00 4.8253e-01 1.6302e-01 2.3244e+00 1.9896e-05
-#> 126: 9.4512e+01 -1.6596e-01 2.1139e+00 7.2806e+00 4.7648e-01 1.7588e-01 2.2913e+00 4.9747e-05
-#> 127: 9.4983e+01 -1.6562e-01 2.1290e+00 6.9166e+00 4.7028e-01 1.6709e-01 2.3141e+00 3.3357e-05
-#> 128: 94.3910 -0.1728 2.1159 6.5708 0.4914 0.1850 2.3173 0.0001
-#> 129: 9.4578e+01 -1.7211e-01 2.1177e+00 6.2422e+00 4.8295e-01 1.7709e-01 2.2815e+00 4.8158e-05
-#> 130: 9.4646e+01 -1.6785e-01 2.1333e+00 5.9301e+00 4.6360e-01 1.6823e-01 2.3140e+00 2.1204e-05
-#> 131: 9.4670e+01 -1.4897e-01 2.1480e+00 5.6336e+00 4.8826e-01 1.5982e-01 2.3436e+00 1.3221e-05
-#> 132: 9.4625e+01 -1.6160e-01 2.1599e+00 5.3519e+00 4.6385e-01 1.6125e-01 2.2830e+00 9.6815e-06
-#> 133: 9.3985e+01 -1.7636e-01 2.1299e+00 5.8178e+00 4.4885e-01 1.5389e-01 2.2810e+00 6.7789e-06
-#> 134: 9.4105e+01 -1.7389e-01 2.1199e+00 5.5269e+00 4.5848e-01 1.4628e-01 2.2992e+00 7.6542e-06
-#> 135: 9.4387e+01 -1.5936e-01 2.1418e+00 5.2506e+00 4.5002e-01 1.6349e-01 2.3403e+00 7.6250e-05
-#> 136: 94.3595 -0.1696 2.1493 4.9880 0.4407 0.1722 2.3121 0.0001
-#> 137: 9.4056e+01 -1.6030e-01 2.1720e+00 5.5600e+00 4.4954e-01 1.8233e-01 2.3099e+00 2.1195e-05
-#> 138: 9.4043e+01 -1.4848e-01 2.1876e+00 5.2820e+00 4.5696e-01 1.8542e-01 2.2876e+00 8.7271e-06
-#> 139: 94.3020 -0.1374 2.1965 5.6428 0.4668 0.1927 2.3341 0.0001
-#> 140: 9.4260e+01 -1.3603e-01 2.2014e+00 5.7727e+00 4.6823e-01 1.8302e-01 2.3248e+00 1.4731e-06
-#> 141: 9.4302e+01 -1.2134e-01 2.1992e+00 5.4841e+00 4.8967e-01 1.7947e-01 2.3212e+00 1.6339e-05
-#> 142: 94.0970 -0.1143 2.2570 5.4173 0.4766 0.1726 2.3581 0.0077
-#> 143: 94.2078 -0.1162 2.2460 5.1464 0.4745 0.1874 2.3551 0.0152
-#> 144: 94.2085 -0.0953 2.2685 4.8891 0.5010 0.1780 2.3881 0.0095
-#> 145: 94.1483 -0.0906 2.2751 5.0705 0.4959 0.1770 2.3103 0.0143
-#> 146: 94.4257 -0.0859 2.2735 5.0201 0.5331 0.2050 2.3104 0.0160
-#> 147: 93.8072 -0.0887 2.2766 4.7691 0.5253 0.2200 2.2903 0.0180
-#> 148: 94.4354 -0.0901 2.2770 4.5306 0.5237 0.2147 2.3108 0.0150
-#> 149: 94.1171 -0.1126 2.2342 4.3041 0.5412 0.2300 2.3454 0.0126
-#> 150: 94.0704 -0.1267 2.2071 4.0889 0.5324 0.2185 2.3673 0.0097
-#> 151: 93.9860 -0.1480 2.1852 3.8844 0.5101 0.2529 2.3280 0.0056
-#> 152: 93.9500 -0.1419 2.1940 4.4687 0.5066 0.2371 2.3617 0.0002
-#> 153: 93.8058 -0.1368 2.1917 4.2493 0.5068 0.2057 2.3481 0.0002
-#> 154: 9.4043e+01 -1.3331e-01 2.1972e+00 4.3921e+00 4.7605e-01 1.9689e-01 2.3952e+00 9.5657e-05
-#> 155: 94.2500 -0.1223 2.2260 5.7786 0.4848 0.1829 2.3361 0.0075
-#> 156: 94.5035 -0.1223 2.2091 6.1344 0.4848 0.1558 2.3951 0.0048
-#> 157: 9.4448e+01 -1.3268e-01 2.1797e+00 6.4746e+00 4.6934e-01 1.6035e-01 2.3496e+00 5.2771e-05
-#> 158: 94.7438 -0.1401 2.1904 6.0162 0.4589 0.1692 2.3444 0.0001
-#> 159: 94.2681 -0.1430 2.1852 4.6165 0.4774 0.1617 2.3601 0.0001
-#> 160: 9.3911e+01 -1.1659e-01 2.2267e+00 4.9756e+00 4.9349e-01 1.7150e-01 2.3500e+00 9.0374e-06
-#> 161: 9.3914e+01 -1.1938e-01 2.2233e+00 4.8238e+00 4.9674e-01 1.8358e-01 2.3536e+00 1.1877e-06
-#> 162: 93.9974 -0.1188 2.2349 5.1092 0.4967 0.1714 2.3237 0.0041
-#> 163: 9.3939e+01 -1.2170e-01 2.2147e+00 4.8315e+00 5.0622e-01 1.8195e-01 2.3823e+00 2.4030e-05
-#> 164: 93.8015 -0.1362 2.2166 3.9112 0.4958 0.1684 2.3488 0.0072
-#> 165: 93.4082 -0.1398 2.2132 3.2992 0.5087 0.1734 2.2861 0.0125
-#> 166: 93.4680 -0.1421 2.2077 3.3232 0.5075 0.1643 2.2792 0.0149
-#> 167: 93.5455 -0.1443 2.2080 3.7465 0.4972 0.1685 2.2194 0.0191
-#> 168: 93.5603 -0.1711 2.1421 3.2407 0.5201 0.1940 2.3029 0.0198
-#> 169: 93.7281 -0.1578 2.1553 2.5110 0.4988 0.1836 2.3343 0.0134
-#> 170: 93.9675 -0.1564 2.1532 2.2507 0.5049 0.1753 2.3089 0.0110
-#> 171: 93.8255 -0.1543 2.1647 2.7302 0.5114 0.1691 2.2959 0.0113
-#> 172: 93.8071 -0.1536 2.1689 2.5849 0.5069 0.1751 2.3047 0.0099
-#> 173: 93.7137 -0.1403 2.2096 1.5160 0.5204 0.1622 2.3452 0.0155
-#> 174: 93.7182 -0.1376 2.1975 1.3366 0.5222 0.1700 2.3311 0.0149
-#> 175: 93.5957 -0.1587 2.1613 1.3539 0.5321 0.1470 2.3893 0.0156
-#> 176: 93.6058 -0.1587 2.1602 1.4588 0.5321 0.1412 2.4323 0.0116
-#> 177: 93.4496 -0.1858 2.1323 1.2423 0.4987 0.1460 2.3491 0.0167
-#> 178: 93.5894 -0.1935 2.1217 1.7812 0.4776 0.1643 2.3046 0.0168
-#> 179: 93.6386 -0.1887 2.1445 2.8813 0.4808 0.1585 2.2689 0.0192
-#> 180: 93.9288 -0.1950 2.1015 2.0905 0.4681 0.1557 2.2783 0.0170
-#> 181: 93.8165 -0.1950 2.0840 2.6302 0.4681 0.1592 2.3643 0.0173
-#> 182: 94.2132 -0.1936 2.0866 3.0185 0.5131 0.1712 2.3164 0.0147
-#> 183: 94.0929 -0.1896 2.0782 3.0716 0.5288 0.1644 2.5169 0.0066
-#> 184: 93.8694 -0.1968 2.0946 2.4734 0.5121 0.1709 2.3795 0.0071
-#> 185: 93.8138 -0.1970 2.0987 2.9707 0.4957 0.1500 2.3995 0.0034
-#> 186: 9.4047e+01 -2.1045e-01 2.0791e+00 3.6686e+00 4.8764e-01 1.4347e-01 2.3654e+00 3.8127e-05
-#> 187: 9.4498e+01 -1.9649e-01 2.0949e+00 2.0912e+00 4.7479e-01 1.6122e-01 2.3873e+00 4.7739e-06
-#> 188: 9.4650e+01 -1.8508e-01 2.1132e+00 2.1529e+00 4.6244e-01 1.4403e-01 2.3367e+00 3.5345e-06
-#> 189: 9.4301e+01 -1.8137e-01 2.1132e+00 2.6433e+00 4.4894e-01 1.3537e-01 2.3145e+00 9.6836e-06
-#> 190: 9.4501e+01 -1.8209e-01 2.0962e+00 3.1460e+00 4.4908e-01 1.2006e-01 2.3563e+00 3.3387e-05
-#> 191: 9.4156e+01 -2.0214e-01 2.0803e+00 3.2334e+00 4.7635e-01 1.1917e-01 2.3782e+00 6.6641e-06
-#> 192: 9.3981e+01 -2.1562e-01 2.0492e+00 3.0526e+00 5.0505e-01 1.3669e-01 2.3412e+00 7.3871e-05
-#> 193: 9.4085e+01 -2.2693e-01 2.0318e+00 2.9855e+00 4.9563e-01 1.4371e-01 2.3727e+00 8.6443e-05
-#> 194: 9.3922e+01 -2.3089e-01 2.0323e+00 2.9709e+00 4.9151e-01 1.4470e-01 2.3667e+00 3.5941e-05
-#> 195: 9.4180e+01 -2.2865e-01 2.0284e+00 2.2426e+00 4.8793e-01 1.5283e-01 2.3442e+00 1.8882e-05
-#> 196: 9.4259e+01 -2.0053e-01 2.0541e+00 1.5155e+00 5.1571e-01 1.5596e-01 2.3638e+00 2.9015e-05
-#> 197: 9.4225e+01 -2.0144e-01 2.0551e+00 1.6032e+00 5.0920e-01 1.6454e-01 2.3564e+00 2.7823e-05
-#> 198: 9.4166e+01 -1.9411e-01 2.0602e+00 1.8793e+00 5.5190e-01 1.8338e-01 2.3611e+00 1.6669e-05
-#> 199: 9.4230e+01 -1.9621e-01 2.0737e+00 1.8847e+00 5.4082e-01 1.7340e-01 2.3488e+00 5.8282e-07
-#> 200: 9.4215e+01 -1.9629e-01 2.0888e+00 1.9185e+00 5.4293e-01 1.7502e-01 2.3563e+00 5.7303e-06
-#> 201: 94.0654 -0.1931 2.0901 1.8074 0.5373 0.1886 2.3869 0.0025
-#> 202: 93.9801 -0.1898 2.0990 1.6823 0.5318 0.1841 2.4043 0.0016
-#> 203: 94.0246 -0.1893 2.1004 1.6503 0.5286 0.1855 2.3971 0.0012
-#> 204: 93.9893 -0.1870 2.1014 1.6166 0.5276 0.1846 2.3900 0.0010
-#> 205: 94.0154 -0.1854 2.1006 1.5294 0.5286 0.1828 2.3939 0.0009
-#> 206: 94.0468 -0.1833 2.1024 1.5102 0.5295 0.1807 2.3967 0.0007
-#> 207: 94.0641 -0.1810 2.1049 1.5136 0.5289 0.1798 2.4037 0.0008
-#> 208: 94.0794 -0.1790 2.1062 1.5078 0.5286 0.1790 2.4139 0.0007
-#> 209: 94.0892 -0.1799 2.1049 1.4549 0.5261 0.1793 2.4144 0.0006
-#> 210: 94.0911 -0.1817 2.1042 1.4537 0.5217 0.1810 2.4069 0.0012
-#> 211: 94.1011 -0.1828 2.1016 1.4582 0.5235 0.1825 2.4049 0.0011
-#> 212: 94.1081 -0.1839 2.0989 1.4657 0.5255 0.1838 2.4031 0.0010
-#> 213: 94.1264 -0.1842 2.0973 1.4527 0.5263 0.1851 2.4026 0.0010
-#> 214: 94.1287 -0.1844 2.0974 1.4405 0.5270 0.1869 2.4006 0.0009
-#> 215: 94.1440 -0.1850 2.0973 1.4556 0.5269 0.1876 2.3985 0.0009
-#> 216: 94.1352 -0.1863 2.0970 1.4698 0.5258 0.1885 2.3977 0.0008
-#> 217: 94.1261 -0.1868 2.0962 1.4850 0.5244 0.1897 2.3946 0.0008
-#> 218: 94.1100 -0.1858 2.0987 1.4673 0.5230 0.1934 2.3924 0.0007
-#> 219: 94.1073 -0.1845 2.1013 1.4630 0.5218 0.1993 2.3890 0.0011
-#> 220: 94.1026 -0.1836 2.1030 1.4705 0.5205 0.2028 2.3904 0.0010
-#> 221: 94.0972 -0.1824 2.1046 1.4732 0.5198 0.2065 2.3907 0.0010
-#> 222: 94.0898 -0.1824 2.1052 1.4952 0.5180 0.2083 2.3892 0.0010
-#> 223: 94.0975 -0.1830 2.1050 1.5035 0.5161 0.2107 2.3888 0.0011
-#> 224: 94.1027 -0.1831 2.1050 1.5196 0.5148 0.2124 2.3878 0.0011
-#> 225: 94.0977 -0.1828 2.1065 1.5153 0.5142 0.2141 2.3856 0.0013
-#> 226: 94.0907 -0.1831 2.1066 1.5287 0.5130 0.2151 2.3828 0.0014
-#> 227: 94.0831 -0.1833 2.1065 1.5535 0.5119 0.2159 2.3814 0.0014
-#> 228: 94.0834 -0.1832 2.1072 1.5713 0.5114 0.2174 2.3813 0.0014
-#> 229: 94.0793 -0.1832 2.1076 1.6041 0.5111 0.2184 2.3811 0.0015
-#> 230: 94.0701 -0.1843 2.1064 1.6177 0.5096 0.2181 2.3803 0.0017
-#> 231: 94.0598 -0.1853 2.1052 1.6254 0.5085 0.2180 2.3818 0.0016
-#> 232: 94.0539 -0.1862 2.1045 1.6254 0.5074 0.2175 2.3824 0.0017
-#> 233: 94.0498 -0.1869 2.1034 1.6380 0.5065 0.2169 2.3826 0.0017
-#> 234: 94.0514 -0.1872 2.1035 1.6300 0.5050 0.2160 2.3829 0.0017
-#> 235: 94.0521 -0.1876 2.1026 1.6263 0.5041 0.2148 2.3825 0.0018
-#> 236: 94.0587 -0.1876 2.1024 1.6277 0.5023 0.2134 2.3834 0.0020
-#> 237: 94.0741 -0.1873 2.1025 1.6349 0.5013 0.2120 2.3828 0.0019
-#> 238: 94.0898 -0.1876 2.1022 1.6509 0.4997 0.2107 2.3837 0.0019
-#> 239: 94.1055 -0.1880 2.1016 1.6596 0.4979 0.2098 2.3836 0.0018
-#> 240: 94.1209 -0.1885 2.1007 1.6627 0.4958 0.2092 2.3831 0.0018
-#> 241: 94.1322 -0.1893 2.0992 1.6563 0.4945 0.2085 2.3825 0.0017
-#> 242: 94.1404 -0.1904 2.0976 1.6574 0.4930 0.2082 2.3814 0.0017
-#> 243: 94.1428 -0.1914 2.0961 1.6412 0.4918 0.2078 2.3800 0.0017
-#> 244: 94.1477 -0.1923 2.0945 1.6287 0.4907 0.2071 2.3795 0.0016
-#> 245: 94.1525 -0.1931 2.0933 1.6225 0.4897 0.2064 2.3791 0.0016
-#> 246: 94.1557 -0.1938 2.0927 1.6243 0.4890 0.2048 2.3780 0.0016
-#> 247: 94.1576 -0.1943 2.0919 1.6333 0.4881 0.2034 2.3777 0.0015
-#> 248: 94.1603 -0.1951 2.0909 1.6328 0.4863 0.2026 2.3775 0.0015
-#> 249: 94.1648 -0.1957 2.0898 1.6427 0.4847 0.2018 2.3774 0.0015
-#> 250: 94.1766 -0.1963 2.0889 1.6482 0.4829 0.2012 2.3770 0.0015
-#> 251: 94.1854 -0.1971 2.0875 1.6536 0.4806 0.2011 2.3769 0.0016
-#> 252: 94.1906 -0.1980 2.0861 1.6527 0.4785 0.2013 2.3763 0.0017
-#> 253: 94.1913 -0.1982 2.0857 1.6459 0.4772 0.2014 2.3751 0.0019
-#> 254: 94.1945 -0.1985 2.0852 1.6413 0.4759 0.2019 2.3755 0.0019
-#> 255: 94.1972 -0.1989 2.0837 1.6451 0.4754 0.2027 2.3753 0.0018
-#> 256: 94.1994 -0.1989 2.0833 1.6548 0.4758 0.2024 2.3752 0.0018
-#> 257: 94.2014 -0.1987 2.0833 1.6708 0.4765 0.2024 2.3752 0.0018
-#> 258: 94.2081 -0.1984 2.0836 1.6903 0.4768 0.2023 2.3749 0.0017
-#> 259: 94.2151 -0.1982 2.0839 1.7169 0.4767 0.2023 2.3737 0.0017
-#> 260: 94.2212 -0.1980 2.0838 1.7426 0.4766 0.2031 2.3725 0.0017
-#> 261: 94.2229 -0.1981 2.0835 1.7696 0.4764 0.2038 2.3714 0.0017
-#> 262: 94.2213 -0.1983 2.0832 1.7977 0.4762 0.2045 2.3704 0.0016
-#> 263: 94.2220 -0.1984 2.0830 1.8277 0.4764 0.2051 2.3700 0.0016
-#> 264: 94.2230 -0.1983 2.0830 1.8430 0.4766 0.2057 2.3690 0.0016
-#> 265: 94.2235 -0.1983 2.0832 1.8679 0.4768 0.2060 2.3674 0.0016
-#> 266: 94.2242 -0.1982 2.0833 1.8705 0.4769 0.2064 2.3658 0.0015
-#> 267: 94.2267 -0.1982 2.0832 1.8715 0.4769 0.2070 2.3643 0.0015
-#> 268: 94.2312 -0.1980 2.0834 1.8824 0.4769 0.2074 2.3631 0.0015
-#> 269: 94.2329 -0.1981 2.0829 1.8843 0.4766 0.2084 2.3628 0.0015
-#> 270: 94.2321 -0.1982 2.0825 1.8904 0.4770 0.2093 2.3629 0.0015
-#> 271: 94.2349 -0.1985 2.0820 1.8942 0.4769 0.2101 2.3633 0.0016
-#> 272: 94.2388 -0.1989 2.0818 1.9099 0.4767 0.2110 2.3634 0.0018
-#> 273: 94.2420 -0.1992 2.0816 1.9259 0.4765 0.2118 2.3632 0.0018
-#> 274: 94.2454 -0.1994 2.0813 1.9330 0.4763 0.2128 2.3629 0.0017
-#> 275: 94.2456 -0.1997 2.0810 1.9316 0.4761 0.2138 2.3624 0.0018
-#> 276: 94.2472 -0.1999 2.0807 1.9306 0.4758 0.2146 2.3624 0.0019
-#> 277: 94.2492 -0.2001 2.0808 1.9326 0.4756 0.2153 2.3623 0.0020
-#> 278: 94.2493 -0.2003 2.0807 1.9225 0.4752 0.2163 2.3628 0.0020
-#> 279: 94.2481 -0.2002 2.0808 1.9206 0.4750 0.2168 2.3628 0.0019
-#> 280: 94.2433 -0.2002 2.0810 1.9257 0.4749 0.2173 2.3626 0.0019
-#> 281: 94.2358 -0.2004 2.0809 1.9217 0.4748 0.2173 2.3620 0.0019
-#> 282: 94.2307 -0.2005 2.0807 1.9209 0.4748 0.2172 2.3617 0.0019
-#> 283: 94.2302 -0.2008 2.0803 1.9131 0.4748 0.2172 2.3615 0.0019
-#> 284: 94.2309 -0.2009 2.0802 1.9085 0.4749 0.2171 2.3610 0.0018
-#> 285: 94.2344 -0.2010 2.0799 1.9135 0.4749 0.2170 2.3603 0.0018
-#> 286: 94.2381 -0.2013 2.0794 1.9099 0.4749 0.2167 2.3596 0.0018
-#> 287: 94.2420 -0.2016 2.0786 1.9105 0.4749 0.2164 2.3596 0.0018
-#> 288: 94.2425 -0.2020 2.0778 1.9081 0.4749 0.2161 2.3590 0.0019
-#> 289: 94.2386 -0.2023 2.0773 1.9136 0.4749 0.2158 2.3586 0.0019
-#> 290: 94.2357 -0.2026 2.0768 1.9171 0.4750 0.2154 2.3581 0.0019
-#> 291: 94.2326 -0.2026 2.0765 1.9162 0.4750 0.2150 2.3577 0.0019
-#> 292: 94.2305 -0.2026 2.0766 1.9178 0.4753 0.2144 2.3577 0.0020
-#> 293: 94.2268 -0.2023 2.0771 1.9257 0.4754 0.2138 2.3574 0.0022
-#> 294: 94.2216 -0.2023 2.0773 1.9326 0.4754 0.2132 2.3565 0.0023
-#> 295: 94.2193 -0.2024 2.0769 1.9378 0.4762 0.2125 2.3565 0.0024
-#> 296: 94.2160 -0.2025 2.0765 1.9463 0.4771 0.2117 2.3565 0.0025
-#> 297: 94.2106 -0.2026 2.0761 1.9523 0.4779 0.2109 2.3569 0.0026
-#> 298: 94.2089 -0.2028 2.0756 1.9622 0.4787 0.2099 2.3578 0.0025
-#> 299: 94.2077 -0.2029 2.0753 1.9721 0.4794 0.2090 2.3586 0.0026
-#> 300: 94.2064 -0.2030 2.0749 1.9838 0.4802 0.2080 2.3589 0.0026
-#> 301: 94.2086 -0.2029 2.0747 1.9942 0.4806 0.2071 2.3587 0.0025
-#> 302: 94.2111 -0.2031 2.0744 1.9938 0.4810 0.2063 2.3593 0.0025
-#> 303: 94.2133 -0.2031 2.0743 1.9923 0.4811 0.2056 2.3593 0.0025
-#> 304: 94.2151 -0.2032 2.0739 1.9885 0.4811 0.2049 2.3595 0.0025
-#> 305: 94.2159 -0.2035 2.0735 1.9872 0.4813 0.2044 2.3594 0.0024
-#> 306: 94.2192 -0.2038 2.0729 1.9806 0.4813 0.2041 2.3592 0.0024
-#> 307: 94.2226 -0.2040 2.0724 1.9796 0.4814 0.2038 2.3588 0.0024
-#> 308: 94.2224 -0.2042 2.0723 1.9828 0.4814 0.2036 2.3589 0.0024
-#> 309: 94.2200 -0.2043 2.0723 1.9859 0.4812 0.2034 2.3587 0.0024
-#> 310: 94.2183 -0.2044 2.0723 1.9892 0.4810 0.2034 2.3583 0.0023
-#> 311: 94.2175 -0.2044 2.0724 1.9895 0.4805 0.2033 2.3580 0.0023
-#> 312: 94.2171 -0.2044 2.0725 1.9977 0.4800 0.2032 2.3581 0.0023
-#> 313: 94.2108 -0.2044 2.0728 1.9995 0.4795 0.2030 2.3578 0.0023
-#> 314: 94.2068 -0.2045 2.0730 1.9929 0.4790 0.2029 2.3576 0.0024
-#> 315: 94.2031 -0.2047 2.0730 1.9884 0.4784 0.2028 2.3579 0.0024
-#> 316: 94.2018 -0.2048 2.0731 1.9860 0.4779 0.2026 2.3582 0.0024
-#> 317: 94.2015 -0.2050 2.0729 1.9836 0.4773 0.2025 2.3582 0.0024
-#> 318: 94.2025 -0.2052 2.0728 1.9814 0.4768 0.2024 2.3580 0.0023
-#> 319: 94.2066 -0.2053 2.0726 1.9867 0.4764 0.2024 2.3577 0.0023
-#> 320: 94.2074 -0.2055 2.0727 1.9896 0.4760 0.2024 2.3575 0.0023
-#> 321: 94.2097 -0.2055 2.0728 1.9985 0.4758 0.2026 2.3573 0.0023
-#> 322: 94.2080 -0.2054 2.0731 2.0108 0.4759 0.2028 2.3570 0.0023
-#> 323: 94.2042 -0.2054 2.0732 2.0253 0.4762 0.2030 2.3566 0.0023
-#> 324: 94.2005 -0.2054 2.0733 2.0514 0.4765 0.2032 2.3566 0.0023
-#> 325: 94.2000 -0.2053 2.0735 2.0719 0.4767 0.2034 2.3570 0.0023
-#> 326: 94.2002 -0.2052 2.0738 2.0907 0.4769 0.2034 2.3573 0.0023
-#> 327: 94.1997 -0.2051 2.0741 2.1140 0.4770 0.2035 2.3571 0.0023
-#> 328: 94.1976 -0.2050 2.0743 2.1379 0.4770 0.2035 2.3569 0.0023
-#> 329: 94.1969 -0.2051 2.0741 2.1485 0.4769 0.2038 2.3566 0.0022
-#> 330: 94.1959 -0.2053 2.0738 2.1533 0.4767 0.2042 2.3561 0.0022
-#> 331: 94.1962 -0.2055 2.0733 2.1588 0.4763 0.2046 2.3555 0.0022
-#> 332: 94.1967 -0.2059 2.0727 2.1626 0.4760 0.2051 2.3551 0.0022
-#> 333: 94.1964 -0.2062 2.0721 2.1666 0.4757 0.2056 2.3547 0.0022
-#> 334: 94.1978 -0.2064 2.0718 2.1703 0.4756 0.2063 2.3543 0.0022
-#> 335: 94.1985 -0.2066 2.0715 2.1698 0.4755 0.2068 2.3538 0.0021
-#> 336: 94.1999 -0.2068 2.0711 2.1705 0.4757 0.2075 2.3534 0.0021
-#> 337: 94.1990 -0.2069 2.0708 2.1690 0.4759 0.2080 2.3530 0.0021
-#> 338: 94.1965 -0.2071 2.0706 2.1708 0.4760 0.2085 2.3525 0.0021
-#> 339: 94.1934 -0.2071 2.0704 2.1769 0.4761 0.2088 2.3518 0.0021
-#> 340: 94.1908 -0.2072 2.0704 2.1794 0.4763 0.2091 2.3515 0.0021
-#> 341: 94.1875 -0.2072 2.0706 2.1859 0.4762 0.2092 2.3512 0.0021
-#> 342: 94.1840 -0.2071 2.0707 2.1903 0.4762 0.2093 2.3513 0.0021
-#> 343: 94.1816 -0.2072 2.0706 2.1909 0.4761 0.2093 2.3512 0.0020
-#> 344: 94.1815 -0.2070 2.0708 2.1877 0.4758 0.2091 2.3514 0.0021
-#> 345: 94.1839 -0.2070 2.0710 2.1844 0.4757 0.2090 2.3517 0.0021
-#> 346: 94.1868 -0.2068 2.0713 2.1787 0.4756 0.2088 2.3520 0.0020
-#> 347: 94.1871 -0.2066 2.0717 2.1762 0.4756 0.2086 2.3519 0.0020
-#> 348: 94.1868 -0.2064 2.0722 2.1724 0.4756 0.2084 2.3521 0.0020
-#> 349: 94.1892 -0.2062 2.0725 2.1673 0.4755 0.2080 2.3524 0.0020
-#> 350: 94.1921 -0.2060 2.0726 2.1632 0.4754 0.2076 2.3527 0.0020
-#> 351: 94.1947 -0.2060 2.0726 2.1613 0.4752 0.2073 2.3530 0.0020
-#> 352: 94.1988 -0.2060 2.0725 2.1647 0.4751 0.2069 2.3530 0.0020
-#> 353: 94.2036 -0.2061 2.0721 2.1684 0.4749 0.2067 2.3530 0.0020
-#> 354: 94.2082 -0.2061 2.0719 2.1670 0.4747 0.2063 2.3529 0.0020
-#> 355: 94.2111 -0.2061 2.0718 2.1645 0.4747 0.2062 2.3526 0.0020
-#> 356: 94.2123 -0.2061 2.0717 2.1628 0.4747 0.2063 2.3525 0.0020
-#> 357: 94.2146 -0.2062 2.0716 2.1610 0.4746 0.2064 2.3523 0.0020
-#> 358: 94.2161 -0.2062 2.0715 2.1656 0.4744 0.2065 2.3520 0.0020
-#> 359: 94.2178 -0.2063 2.0714 2.1684 0.4743 0.2065 2.3516 0.0020
-#> 360: 94.2194 -0.2063 2.0713 2.1687 0.4742 0.2065 2.3512 0.0019
-#> 361: 94.2191 -0.2064 2.0713 2.1738 0.4741 0.2065 2.3508 0.0019
-#> 362: 94.2186 -0.2064 2.0713 2.1762 0.4740 0.2065 2.3502 0.0019
-#> 363: 94.2179 -0.2064 2.0714 2.1754 0.4740 0.2065 2.3495 0.0019
-#> 364: 94.2165 -0.2063 2.0715 2.1740 0.4741 0.2064 2.3495 0.0019
-#> 365: 94.2149 -0.2063 2.0716 2.1736 0.4741 0.2062 2.3495 0.0020
-#> 366: 94.2141 -0.2062 2.0717 2.1813 0.4740 0.2064 2.3490 0.0020
-#> 367: 94.2158 -0.2062 2.0717 2.1905 0.4739 0.2063 2.3491 0.0019
-#> 368: 94.2173 -0.2062 2.0718 2.1963 0.4737 0.2063 2.3485 0.0019
-#> 369: 94.2183 -0.2062 2.0717 2.2005 0.4736 0.2064 2.3481 0.0019
-#> 370: 94.2194 -0.2062 2.0716 2.2016 0.4735 0.2063 2.3477 0.0019
-#> 371: 94.2192 -0.2063 2.0715 2.1997 0.4733 0.2064 2.3476 0.0019
-#> 372: 94.2202 -0.2062 2.0716 2.1957 0.4733 0.2065 2.3479 0.0019
-#> 373: 94.2208 -0.2061 2.0717 2.1913 0.4733 0.2065 2.3480 0.0019
-#> 374: 94.2209 -0.2061 2.0719 2.1870 0.4731 0.2065 2.3479 0.0019
-#> 375: 94.2219 -0.2061 2.0719 2.1864 0.4729 0.2064 2.3477 0.0019
-#> 376: 94.2231 -0.2061 2.0720 2.1849 0.4726 0.2063 2.3473 0.0019
-#> 377: 94.2251 -0.2061 2.0720 2.1835 0.4724 0.2063 2.3471 0.0019
-#> 378: 94.2238 -0.2062 2.0719 2.1777 0.4721 0.2062 2.3472 0.0018
-#> 379: 94.2226 -0.2064 2.0717 2.1741 0.4717 0.2063 2.3471 0.0018
-#> 380: 94.2216 -0.2066 2.0714 2.1759 0.4714 0.2063 2.3468 0.0018
-#> 381: 94.2206 -0.2068 2.0711 2.1784 0.4711 0.2063 2.3465 0.0018
-#> 382: 94.2200 -0.2071 2.0707 2.1753 0.4707 0.2062 2.3462 0.0018
-#> 383: 94.2205 -0.2073 2.0704 2.1757 0.4703 0.2061 2.3461 0.0018
-#> 384: 94.2201 -0.2076 2.0702 2.1802 0.4698 0.2060 2.3458 0.0018
-#> 385: 94.2210 -0.2078 2.0701 2.1795 0.4693 0.2061 2.3457 0.0018
-#> 386: 94.2199 -0.2079 2.0700 2.1788 0.4688 0.2061 2.3455 0.0018
-#> 387: 94.2181 -0.2081 2.0699 2.1801 0.4683 0.2061 2.3454 0.0018
-#> 388: 94.2169 -0.2082 2.0699 2.1850 0.4679 0.2061 2.3452 0.0017
-#> 389: 94.2158 -0.2083 2.0699 2.1881 0.4674 0.2063 2.3449 0.0017
-#> 390: 94.2162 -0.2084 2.0696 2.1928 0.4671 0.2064 2.3447 0.0017
-#> 391: 94.2172 -0.2085 2.0696 2.1921 0.4669 0.2063 2.3444 0.0017
-#> 392: 94.2175 -0.2085 2.0695 2.1933 0.4667 0.2063 2.3442 0.0017
-#> 393: 94.2174 -0.2086 2.0695 2.1972 0.4666 0.2062 2.3440 0.0017
-#> 394: 94.2179 -0.2087 2.0694 2.1972 0.4664 0.2061 2.3439 0.0017
-#> 395: 94.2200 -0.2087 2.0694 2.2009 0.4663 0.2059 2.3438 0.0017
-#> 396: 94.2189 -0.2086 2.0695 2.2062 0.4662 0.2058 2.3434 0.0017
-#> 397: 94.2183 -0.2085 2.0696 2.2151 0.4663 0.2056 2.3431 0.0017
-#> 398: 94.2186 -0.2085 2.0696 2.2200 0.4664 0.2056 2.3430 0.0017
-#> 399: 94.2183 -0.2084 2.0698 2.2204 0.4664 0.2056 2.3428 0.0017
-#> 400: 94.2184 -0.2082 2.0703 2.2252 0.4665 0.2054 2.3428 0.0016
-#> 401: 94.2176 -0.2080 2.0707 2.2323 0.4666 0.2052 2.3427 0.0016
-#> 402: 94.2167 -0.2078 2.0712 2.2397 0.4668 0.2050 2.3426 0.0016
-#> 403: 94.2157 -0.2075 2.0716 2.2464 0.4669 0.2049 2.3426 0.0016
-#> 404: 94.2152 -0.2074 2.0719 2.2508 0.4670 0.2047 2.3427 0.0016
-#> 405: 94.2152 -0.2072 2.0723 2.2537 0.4671 0.2046 2.3427 0.0016
-#> 406: 94.2151 -0.2070 2.0726 2.2565 0.4672 0.2044 2.3427 0.0016
-#> 407: 94.2132 -0.2067 2.0731 2.2568 0.4673 0.2044 2.3426 0.0016
-#> 408: 94.2142 -0.2065 2.0734 2.2579 0.4674 0.2046 2.3424 0.0016
-#> 409: 94.2136 -0.2063 2.0738 2.2630 0.4674 0.2046 2.3420 0.0016
-#> 410: 94.2125 -0.2062 2.0739 2.2635 0.4674 0.2047 2.3417 0.0016
-#> 411: 94.2131 -0.2061 2.0741 2.2634 0.4674 0.2048 2.3413 0.0016
-#> 412: 94.2132 -0.2060 2.0742 2.2662 0.4674 0.2048 2.3409 0.0016
-#> 413: 94.2143 -0.2059 2.0743 2.2666 0.4673 0.2048 2.3407 0.0016
-#> 414: 94.2156 -0.2058 2.0743 2.2710 0.4672 0.2048 2.3404 0.0015
-#> 415: 94.2174 -0.2057 2.0745 2.2751 0.4671 0.2049 2.3400 0.0015
-#> 416: 94.2185 -0.2057 2.0746 2.2762 0.4669 0.2049 2.3399 0.0015
-#> 417: 94.2208 -0.2056 2.0748 2.2759 0.4667 0.2049 2.3397 0.0015
-#> 418: 94.2231 -0.2054 2.0751 2.2772 0.4664 0.2050 2.3398 0.0015
-#> 419: 94.2249 -0.2053 2.0754 2.2783 0.4663 0.2050 2.3396 0.0015
-#> 420: 94.2255 -0.2052 2.0757 2.2798 0.4660 0.2050 2.3395 0.0015
-#> 421: 94.2265 -0.2051 2.0759 2.2848 0.4659 0.2050 2.3392 0.0016
-#> 422: 94.2288 -0.2049 2.0761 2.2929 0.4659 0.2050 2.3390 0.0016
-#> 423: 94.2307 -0.2048 2.0762 2.2988 0.4657 0.2051 2.3390 0.0016
-#> 424: 94.2313 -0.2047 2.0764 2.3017 0.4656 0.2051 2.3391 0.0016
-#> 425: 94.2322 -0.2046 2.0765 2.3028 0.4655 0.2050 2.3388 0.0016
-#> 426: 94.2327 -0.2046 2.0765 2.3049 0.4654 0.2050 2.3386 0.0016
-#> 427: 94.2323 -0.2045 2.0768 2.3053 0.4655 0.2049 2.3386 0.0016
-#> 428: 94.2324 -0.2044 2.0770 2.3016 0.4655 0.2048 2.3387 0.0017
-#> 429: 94.2322 -0.2043 2.0772 2.2984 0.4656 0.2047 2.3386 0.0017
-#> 430: 94.2306 -0.2042 2.0774 2.2971 0.4656 0.2046 2.3384 0.0017
-#> 431: 94.2295 -0.2042 2.0775 2.2931 0.4657 0.2044 2.3384 0.0017
-#> 432: 94.2298 -0.2040 2.0778 2.2896 0.4656 0.2044 2.3383 0.0018
-#> 433: 94.2311 -0.2039 2.0780 2.2885 0.4656 0.2044 2.3383 0.0018
-#> 434: 94.2311 -0.2037 2.0783 2.2854 0.4655 0.2044 2.3381 0.0018
-#> 435: 94.2314 -0.2036 2.0786 2.2838 0.4654 0.2044 2.3378 0.0018
-#> 436: 94.2315 -0.2035 2.0788 2.2817 0.4653 0.2044 2.3377 0.0018
-#> 437: 94.2326 -0.2034 2.0790 2.2801 0.4652 0.2044 2.3378 0.0018
-#> 438: 94.2338 -0.2034 2.0791 2.2802 0.4650 0.2046 2.3380 0.0018
-#> 439: 94.2340 -0.2033 2.0791 2.2810 0.4649 0.2046 2.3377 0.0018
-#> 440: 94.2330 -0.2034 2.0791 2.2822 0.4646 0.2046 2.3376 0.0018
-#> 441: 94.2323 -0.2035 2.0790 2.2818 0.4644 0.2046 2.3375 0.0018
-#> 442: 94.2321 -0.2034 2.0792 2.2804 0.4642 0.2043 2.3375 0.0018
-#> 443: 94.2313 -0.2033 2.0794 2.2812 0.4641 0.2041 2.3372 0.0018
-#> 444: 94.2301 -0.2032 2.0796 2.2820 0.4640 0.2040 2.3369 0.0018
-#> 445: 94.2279 -0.2031 2.0799 2.2872 0.4639 0.2039 2.3366 0.0018
-#> 446: 94.2272 -0.2030 2.0801 2.2874 0.4639 0.2037 2.3363 0.0018
-#> 447: 94.2262 -0.2029 2.0803 2.2881 0.4639 0.2036 2.3359 0.0018
-#> 448: 94.2248 -0.2028 2.0806 2.2905 0.4639 0.2036 2.3358 0.0018
-#> 449: 94.2245 -0.2027 2.0808 2.2914 0.4638 0.2035 2.3356 0.0018
-#> 450: 94.2237 -0.2027 2.0809 2.2928 0.4638 0.2035 2.3356 0.0018
-#> 451: 94.2233 -0.2025 2.0813 2.2917 0.4639 0.2033 2.3355 0.0018
-#> 452: 94.2232 -0.2023 2.0816 2.2898 0.4640 0.2031 2.3356 0.0018
-#> 453: 94.2230 -0.2021 2.0819 2.2890 0.4641 0.2030 2.3356 0.0018
-#> 454: 94.2222 -0.2020 2.0822 2.2851 0.4641 0.2029 2.3357 0.0018
-#> 455: 94.2214 -0.2018 2.0824 2.2820 0.4640 0.2028 2.3357 0.0017
-#> 456: 94.2212 -0.2017 2.0827 2.2797 0.4640 0.2026 2.3357 0.0017
-#> 457: 94.2216 -0.2016 2.0829 2.2771 0.4640 0.2024 2.3358 0.0017
-#> 458: 94.2220 -0.2015 2.0831 2.2740 0.4639 0.2022 2.3358 0.0017
-#> 459: 94.2229 -0.2013 2.0834 2.2765 0.4638 0.2021 2.3358 0.0017
-#> 460: 94.2226 -0.2012 2.0837 2.2810 0.4637 0.2020 2.3359 0.0017
-#> 461: 94.2227 -0.2009 2.0841 2.2893 0.4637 0.2018 2.3358 0.0017
-#> 462: 94.2235 -0.2007 2.0844 2.2942 0.4637 0.2016 2.3357 0.0017
-#> 463: 94.2241 -0.2005 2.0848 2.2971 0.4637 0.2014 2.3358 0.0017
-#> 464: 94.2236 -0.2002 2.0853 2.2953 0.4637 0.2012 2.3360 0.0017
-#> 465: 94.2230 -0.2000 2.0858 2.2946 0.4638 0.2010 2.3360 0.0017
-#> 466: 94.2215 -0.1997 2.0863 2.2995 0.4638 0.2009 2.3363 0.0017
-#> 467: 94.2193 -0.1995 2.0868 2.3051 0.4637 0.2008 2.3363 0.0017
-#> 468: 94.2174 -0.1992 2.0874 2.3086 0.4636 0.2006 2.3363 0.0018
-#> 469: 94.2160 -0.1989 2.0881 2.3072 0.4636 0.2006 2.3361 0.0018
-#> 470: 94.2152 -0.1985 2.0887 2.3075 0.4637 0.2005 2.3363 0.0018
-#> 471: 94.2139 -0.1982 2.0891 2.3126 0.4638 0.2004 2.3361 0.0018
-#> 472: 94.2134 -0.1980 2.0895 2.3151 0.4640 0.2002 2.3360 0.0018
-#> 473: 94.2141 -0.1979 2.0897 2.3149 0.4640 0.2001 2.3360 0.0018
-#> 474: 94.2144 -0.1978 2.0900 2.3140 0.4640 0.2001 2.3358 0.0018
-#> 475: 94.2151 -0.1977 2.0901 2.3151 0.4640 0.2000 2.3358 0.0018
-#> 476: 94.2154 -0.1975 2.0903 2.3195 0.4641 0.2001 2.3357 0.0018
-#> 477: 94.2167 -0.1974 2.0905 2.3253 0.4642 0.2002 2.3358 0.0018
-#> 478: 94.2163 -0.1972 2.0909 2.3324 0.4641 0.2004 2.3357 0.0017
-#> 479: 94.2156 -0.1970 2.0912 2.3364 0.4640 0.2006 2.3355 0.0017
-#> 480: 94.2149 -0.1969 2.0915 2.3395 0.4638 0.2007 2.3353 0.0017
-#> 481: 94.2140 -0.1968 2.0918 2.3431 0.4637 0.2008 2.3350 0.0017
-#> 482: 94.2137 -0.1967 2.0919 2.3440 0.4635 0.2010 2.3349 0.0017
-#> 483: 94.2139 -0.1966 2.0920 2.3468 0.4634 0.2011 2.3348 0.0017
-#> 484: 94.2149 -0.1966 2.0921 2.3488 0.4633 0.2012 2.3346 0.0017
-#> 485: 94.2153 -0.1966 2.0921 2.3486 0.4632 0.2012 2.3345 0.0017
-#> 486: 94.2148 -0.1965 2.0923 2.3483 0.4631 0.2015 2.3345 0.0017
-#> 487: 94.2140 -0.1965 2.0923 2.3492 0.4628 0.2018 2.3345 0.0017
-#> 488: 94.2121 -0.1965 2.0923 2.3489 0.4625 0.2020 2.3347 0.0017
-#> 489: 94.2119 -0.1966 2.0923 2.3497 0.4622 0.2023 2.3346 0.0017
-#> 490: 94.2120 -0.1966 2.0923 2.3476 0.4618 0.2025 2.3346 0.0017
-#> 491: 94.2124 -0.1966 2.0923 2.3462 0.4615 0.2028 2.3346 0.0017
-#> 492: 94.2118 -0.1966 2.0923 2.3453 0.4613 0.2029 2.3346 0.0017
-#> 493: 94.2113 -0.1967 2.0923 2.3452 0.4610 0.2030 2.3347 0.0017
-#> 494: 94.2118 -0.1968 2.0922 2.3488 0.4608 0.2030 2.3347 0.0017
-#> 495: 94.2122 -0.1969 2.0920 2.3530 0.4605 0.2029 2.3347 0.0017
-#> 496: 94.2138 -0.1969 2.0919 2.3540 0.4603 0.2028 2.3350 0.0017
-#> 497: 94.2148 -0.1970 2.0917 2.3554 0.4601 0.2029 2.3352 0.0017
-#> 498: 94.2152 -0.1971 2.0916 2.3534 0.4600 0.2029 2.3356 0.0017
-#> 499: 94.2157 -0.1972 2.0914 2.3519 0.4598 0.2029 2.3357 0.0016
-#> 500: 94.2162 -0.1973 2.0912 2.3498 0.4596 0.2030 2.3358 0.0016
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> | #| Objective Fun | parent_0 | log_alpha | log_beta | sigma_low |
-#> |.....................| rsd_high | o1 | o2 | o3 |
-#> | 1| 356.08238 | 1.000 | -1.000 | -0.9495 | -0.9739 |
-#> |.....................| -0.9969 | -0.9818 | -0.9750 | -0.9744 |
-#> | U| 356.08238 | 93.10 | -0.1209 | 2.232 | 1.095 |
-#> |.....................| 0.02509 | 0.7272 | 1.045 | 1.072 |
-#> | X| 356.08238 | 93.10 | 0.8861 | 9.321 | 1.095 |
-#> |.....................| 0.02509 | 0.7272 | 1.045 | 1.072 |
-#> | G| Gill Diff. | -85.81 | 0.5929 | 0.9043 | -97.79 |
-#> |.....................| -28.71 | -0.07427 | -8.550 | -12.99 |
-#> | 2| 1940.7752 | 1.640 | -1.004 | -0.9563 | -0.2449 |
-#> |.....................| -0.7829 | -0.9813 | -0.9112 | -0.8775 |
-#> | U| 1940.7752 | 152.7 | -0.1253 | 2.226 | 1.495 |
-#> |.....................| 0.02778 | 0.7276 | 1.112 | 1.176 |
-#> | X| 1940.7752 | 152.7 | 0.8822 | 9.258 | 1.495 |
-#> |.....................| 0.02778 | 0.7276 | 1.112 | 1.176 |
-#> | 3| 370.78508 | 1.064 | -1.000 | -0.9502 | -0.9010 |
-#> |.....................| -0.9755 | -0.9817 | -0.9686 | -0.9647 |
-#> | U| 370.78508 | 99.05 | -0.1213 | 2.232 | 1.135 |
-#> |.....................| 0.02536 | 0.7272 | 1.052 | 1.082 |
-#> | X| 370.78508 | 99.05 | 0.8857 | 9.315 | 1.135 |
-#> |.....................| 0.02536 | 0.7272 | 1.052 | 1.082 |
-#> | 4| 354.52588 | 1.015 | -1.000 | -0.9497 | -0.9565 |
-#> |.....................| -0.9918 | -0.9818 | -0.9735 | -0.9721 |
-#> | U| 354.52588 | 94.52 | -0.1210 | 2.232 | 1.105 |
-#> |.....................| 0.02516 | 0.7272 | 1.047 | 1.074 |
-#> | X| 354.52588 | 94.52 | 0.8860 | 9.319 | 1.105 |
-#> |.....................| 0.02516 | 0.7272 | 1.047 | 1.074 |
-#> | F| Forward Diff. | 126.3 | 0.7329 | 1.391 | -95.71 |
-#> |.....................| -26.58 | 0.4812 | -8.528 | -12.76 |
-#> | 5| 352.43362 | 0.9998 | -1.000 | -0.9499 | -0.9392 |
-#> |.....................| -0.9869 | -0.9819 | -0.9719 | -0.9698 |
-#> | U| 352.43362 | 93.08 | -0.1211 | 2.232 | 1.114 |
-#> |.....................| 0.02522 | 0.7271 | 1.048 | 1.077 |
-#> | X| 352.43362 | 93.08 | 0.8859 | 9.317 | 1.114 |
-#> |.....................| 0.02522 | 0.7271 | 1.048 | 1.077 |
-#> | F| Forward Diff. | -88.58 | 0.5971 | 0.9141 | -92.65 |
-#> |.....................| -26.61 | -0.01862 | -8.458 | -12.78 |
-#> | 6| 350.82994 | 1.015 | -1.000 | -0.9501 | -0.9214 |
-#> |.....................| -0.9818 | -0.9819 | -0.9703 | -0.9673 |
-#> | U| 350.82994 | 94.46 | -0.1213 | 2.232 | 1.124 |
-#> |.....................| 0.02528 | 0.7271 | 1.050 | 1.079 |
-#> | X| 350.82994 | 94.46 | 0.8858 | 9.315 | 1.124 |
-#> |.....................| 0.02528 | 0.7271 | 1.050 | 1.079 |
-#> | F| Forward Diff. | 115.7 | 0.7442 | 1.407 | -90.51 |
-#> |.....................| -24.67 | 0.2416 | -8.378 | -12.59 |
-#> | 7| 348.85697 | 1.000 | -1.000 | -0.9503 | -0.9035 |
-#> |.....................| -0.9769 | -0.9819 | -0.9686 | -0.9649 |
-#> | U| 348.85697 | 93.10 | -0.1214 | 2.231 | 1.134 |
-#> |.....................| 0.02534 | 0.7271 | 1.052 | 1.082 |
-#> | X| 348.85697 | 93.10 | 0.8857 | 9.313 | 1.134 |
-#> |.....................| 0.02534 | 0.7271 | 1.052 | 1.082 |
-#> | F| Forward Diff. | -86.89 | 0.6078 | 0.9395 | -87.49 |
-#> |.....................| -24.70 | -0.2033 | -8.301 | -12.59 |
-#> | 8| 347.23757 | 1.014 | -1.001 | -0.9506 | -0.8852 |
-#> |.....................| -0.9717 | -0.9819 | -0.9669 | -0.9622 |
-#> | U| 347.23757 | 94.41 | -0.1215 | 2.231 | 1.144 |
-#> |.....................| 0.02541 | 0.7271 | 1.054 | 1.085 |
-#> | X| 347.23757 | 94.41 | 0.8856 | 9.311 | 1.144 |
-#> |.....................| 0.02541 | 0.7271 | 1.054 | 1.085 |
-#> | F| Forward Diff. | 106.0 | 0.7499 | 1.419 | -85.67 |
-#> |.....................| -22.89 | -0.09812 | -8.213 | -12.39 |
-#> | 9| 345.37317 | 1.000 | -1.001 | -0.9508 | -0.8667 |
-#> |.....................| -0.9667 | -0.9818 | -0.9651 | -0.9596 |
-#> | U| 345.37317 | 93.12 | -0.1217 | 2.231 | 1.154 |
-#> |.....................| 0.02547 | 0.7272 | 1.056 | 1.088 |
-#> | X| 345.37317 | 93.12 | 0.8854 | 9.308 | 1.154 |
-#> |.....................| 0.02547 | 0.7272 | 1.056 | 1.088 |
-#> | F| Forward Diff. | -84.47 | 0.6193 | 0.9668 | -82.72 |
-#> |.....................| -22.87 | -0.2860 | -8.128 | -12.38 |
-#> | 10| 343.77522 | 1.014 | -1.001 | -0.9511 | -0.8479 |
-#> |.....................| -0.9616 | -0.9818 | -0.9633 | -0.9568 |
-#> | U| 343.77522 | 94.37 | -0.1218 | 2.231 | 1.164 |
-#> |.....................| 0.02554 | 0.7272 | 1.057 | 1.091 |
-#> | X| 343.77522 | 94.37 | 0.8853 | 9.306 | 1.164 |
-#> |.....................| 0.02554 | 0.7272 | 1.057 | 1.091 |
-#> | F| Forward Diff. | 98.54 | 0.7582 | 1.440 | -80.80 |
-#> |.....................| -21.11 | -0.2480 | -8.037 | -12.18 |
-#> | 11| 342.01002 | 1.000 | -1.001 | -0.9514 | -0.8290 |
-#> |.....................| -0.9566 | -0.9817 | -0.9614 | -0.9539 |
-#> | U| 342.01002 | 93.14 | -0.1220 | 2.230 | 1.175 |
-#> |.....................| 0.02560 | 0.7273 | 1.059 | 1.094 |
-#> | X| 342.01002 | 93.14 | 0.8852 | 9.303 | 1.175 |
-#> |.....................| 0.02560 | 0.7273 | 1.059 | 1.094 |
-#> | F| Forward Diff. | -81.78 | 0.6281 | 0.9934 | -78.17 |
-#> |.....................| -21.11 | -0.4903 | -7.943 | -12.16 |
-#> | 12| 340.43696 | 1.013 | -1.001 | -0.9517 | -0.8098 |
-#> |.....................| -0.9515 | -0.9816 | -0.9595 | -0.9509 |
-#> | U| 340.43696 | 94.32 | -0.1222 | 2.230 | 1.185 |
-#> |.....................| 0.02566 | 0.7274 | 1.062 | 1.097 |
-#> | X| 340.43696 | 94.32 | 0.8850 | 9.301 | 1.185 |
-#> |.....................| 0.02566 | 0.7274 | 1.062 | 1.097 |
-#> | F| Forward Diff. | 90.87 | 0.7671 | 1.462 | -75.86 |
-#> |.....................| -19.30 | -0.2119 | -7.851 | -11.96 |
-#> | 13| 338.78414 | 1.001 | -1.001 | -0.9520 | -0.7906 |
-#> |.....................| -0.9465 | -0.9815 | -0.9574 | -0.9478 |
-#> | U| 338.78414 | 93.15 | -0.1223 | 2.230 | 1.196 |
-#> |.....................| 0.02572 | 0.7274 | 1.064 | 1.100 |
-#> | X| 338.78414 | 93.15 | 0.8848 | 9.298 | 1.196 |
-#> |.....................| 0.02572 | 0.7274 | 1.064 | 1.100 |
-#> | F| Forward Diff. | -80.47 | 0.6431 | 1.023 | -73.28 |
-#> |.....................| -19.27 | -0.2791 | -7.739 | -11.92 |
-#> | 14| 337.22825 | 1.013 | -1.002 | -0.9523 | -0.7710 |
-#> |.....................| -0.9415 | -0.9814 | -0.9553 | -0.9445 |
-#> | U| 337.22825 | 94.28 | -0.1225 | 2.229 | 1.206 |
-#> |.....................| 0.02579 | 0.7275 | 1.066 | 1.104 |
-#> | X| 337.22825 | 94.28 | 0.8847 | 9.295 | 1.206 |
-#> |.....................| 0.02579 | 0.7275 | 1.066 | 1.104 |
-#> | F| Forward Diff. | 82.17 | 0.7754 | 1.480 | -71.69 |
-#> |.....................| -17.81 | -0.5846 | -7.635 | -11.71 |
-#> | 15| 335.66851 | 1.001 | -1.002 | -0.9527 | -0.7512 |
-#> |.....................| -0.9367 | -0.9812 | -0.9531 | -0.9411 |
-#> | U| 335.66851 | 93.18 | -0.1228 | 2.229 | 1.217 |
-#> |.....................| 0.02585 | 0.7276 | 1.068 | 1.108 |
-#> | X| 335.66851 | 93.18 | 0.8845 | 9.291 | 1.217 |
-#> |.....................| 0.02585 | 0.7276 | 1.068 | 1.108 |
-#> | F| Forward Diff. | -77.03 | 0.6546 | 1.055 | -69.28 |
-#> |.....................| -17.76 | -0.6126 | -7.531 | -11.66 |
-#> | 16| 334.17549 | 1.012 | -1.002 | -0.9531 | -0.7314 |
-#> |.....................| -0.9319 | -0.9810 | -0.9509 | -0.9376 |
-#> | U| 334.17549 | 94.25 | -0.1230 | 2.229 | 1.228 |
-#> |.....................| 0.02591 | 0.7278 | 1.070 | 1.111 |
-#> | X| 334.17549 | 94.25 | 0.8843 | 9.287 | 1.228 |
-#> |.....................| 0.02591 | 0.7278 | 1.070 | 1.111 |
-#> | F| Forward Diff. | 77.34 | 0.7869 | 1.511 | -67.40 |
-#> |.....................| -16.23 | -0.6338 | -7.414 | -11.45 |
-#> | 17| 332.70253 | 1.001 | -1.002 | -0.9536 | -0.7113 |
-#> |.....................| -0.9273 | -0.9807 | -0.9485 | -0.9339 |
-#> | U| 332.70253 | 93.20 | -0.1232 | 2.228 | 1.239 |
-#> |.....................| 0.02597 | 0.7280 | 1.073 | 1.115 |
-#> | X| 332.70253 | 93.20 | 0.8841 | 9.283 | 1.239 |
-#> |.....................| 0.02597 | 0.7280 | 1.073 | 1.115 |
-#> | F| Forward Diff. | -74.42 | 0.6680 | 1.089 | -65.07 |
-#> |.....................| -16.20 | -0.6067 | -7.288 | -11.39 |
-#> | 18| 331.26057 | 1.012 | -1.003 | -0.9540 | -0.6912 |
-#> |.....................| -0.9227 | -0.9804 | -0.9461 | -0.9301 |
-#> | U| 331.26057 | 94.22 | -0.1235 | 2.228 | 1.250 |
-#> |.....................| 0.02602 | 0.7282 | 1.076 | 1.119 |
-#> | X| 331.26057 | 94.22 | 0.8838 | 9.279 | 1.250 |
-#> |.....................| 0.02602 | 0.7282 | 1.076 | 1.119 |
-#> | F| Forward Diff. | 71.33 | 0.7962 | 1.537 | -63.45 |
-#> |.....................| -14.84 | -0.8466 | -7.169 | -11.16 |
-#> | 19| 329.86877 | 1.001 | -1.003 | -0.9546 | -0.6708 |
-#> |.....................| -0.9184 | -0.9799 | -0.9435 | -0.9260 |
-#> | U| 329.86877 | 93.23 | -0.1238 | 2.227 | 1.261 |
-#> |.....................| 0.02608 | 0.7285 | 1.078 | 1.124 |
-#> | X| 329.86877 | 93.23 | 0.8836 | 9.273 | 1.261 |
-#> |.....................| 0.02608 | 0.7285 | 1.078 | 1.124 |
-#> | F| Forward Diff. | -70.96 | 0.6825 | 1.126 | -60.92 |
-#> |.....................| -14.66 | -0.5289 | -7.027 | -11.08 |
-#> | 20| 328.50031 | 1.012 | -1.003 | -0.9552 | -0.6504 |
-#> |.....................| -0.9143 | -0.9795 | -0.9408 | -0.9217 |
-#> | U| 328.50031 | 94.20 | -0.1241 | 2.227 | 1.272 |
-#> |.....................| 0.02613 | 0.7288 | 1.081 | 1.128 |
-#> | X| 328.50031 | 94.20 | 0.8833 | 9.268 | 1.272 |
-#> |.....................| 0.02613 | 0.7288 | 1.081 | 1.128 |
-#> | F| Forward Diff. | 67.86 | 0.8082 | 1.577 | -59.49 |
-#> |.....................| -13.42 | -0.7986 | -6.899 | -10.84 |
-#> | 21| 327.16645 | 1.002 | -1.004 | -0.9559 | -0.6298 |
-#> |.....................| -0.9105 | -0.9791 | -0.9380 | -0.9171 |
-#> | U| 327.16645 | 93.27 | -0.1245 | 2.226 | 1.284 |
-#> |.....................| 0.02618 | 0.7291 | 1.084 | 1.133 |
-#> | X| 327.16645 | 93.27 | 0.8829 | 9.261 | 1.284 |
-#> |.....................| 0.02618 | 0.7291 | 1.084 | 1.133 |
-#> | F| Forward Diff. | -65.39 | 0.6978 | 1.172 | -57.48 |
-#> |.....................| -13.36 | -0.7754 | -6.743 | -10.73 |
-#> | 22| 325.87373 | 1.012 | -1.004 | -0.9567 | -0.6091 |
-#> |.....................| -0.9070 | -0.9785 | -0.9351 | -0.9123 |
-#> | U| 325.87373 | 94.19 | -0.1249 | 2.225 | 1.295 |
-#> |.....................| 0.02622 | 0.7296 | 1.087 | 1.138 |
-#> | X| 325.87373 | 94.19 | 0.8826 | 9.255 | 1.295 |
-#> |.....................| 0.02622 | 0.7296 | 1.087 | 1.138 |
-#> | F| Forward Diff. | 64.00 | 0.8187 | 1.613 | -55.46 |
-#> |.....................| -12.01 | -0.6347 | -6.615 | -10.48 |
-#> | 23| 324.62990 | 1.002 | -1.004 | -0.9576 | -0.5884 |
-#> |.....................| -0.9040 | -0.9780 | -0.9320 | -0.9071 |
-#> | U| 324.6299 | 93.29 | -0.1254 | 2.224 | 1.306 |
-#> |.....................| 0.02626 | 0.7300 | 1.090 | 1.144 |
-#> | X| 324.6299 | 93.29 | 0.8822 | 9.246 | 1.306 |
-#> |.....................| 0.02626 | 0.7300 | 1.090 | 1.144 |
-#> | F| Forward Diff. | -64.25 | 0.7091 | 1.205 | -53.86 |
-#> |.....................| -12.06 | -0.7132 | -6.446 | -10.35 |
-#> | 24| 323.37595 | 1.011 | -1.005 | -0.9586 | -0.5676 |
-#> |.....................| -0.9015 | -0.9774 | -0.9287 | -0.9014 |
-#> | U| 323.37595 | 94.14 | -0.1259 | 2.223 | 1.318 |
-#> |.....................| 0.02629 | 0.7304 | 1.094 | 1.150 |
-#> | X| 323.37595 | 94.14 | 0.8817 | 9.236 | 1.318 |
-#> |.....................| 0.02629 | 0.7304 | 1.094 | 1.150 |
-#> | F| Forward Diff. | 56.04 | 0.8254 | 1.637 | -52.44 |
-#> |.....................| -10.96 | -0.9420 | -6.280 | -10.07 |
-#> | 25| 322.22752 | 1.002 | -1.006 | -0.9598 | -0.5467 |
-#> |.....................| -0.8995 | -0.9764 | -0.9254 | -0.8957 |
-#> | U| 322.22752 | 93.30 | -0.1265 | 2.222 | 1.329 |
-#> |.....................| 0.02631 | 0.7311 | 1.097 | 1.156 |
-#> | X| 322.22752 | 93.30 | 0.8812 | 9.225 | 1.329 |
-#> |.....................| 0.02631 | 0.7311 | 1.097 | 1.156 |
-#> | F| Forward Diff. | -62.58 | 0.7198 | 1.238 | -50.46 |
-#> |.....................| -10.85 | -0.6563 | -6.111 | -9.931 |
-#> | 26| 321.05050 | 1.011 | -1.006 | -0.9612 | -0.5258 |
-#> |.....................| -0.8983 | -0.9755 | -0.9219 | -0.8894 |
-#> | U| 321.0505 | 94.13 | -0.1272 | 2.221 | 1.341 |
-#> |.....................| 0.02633 | 0.7318 | 1.101 | 1.163 |
-#> | X| 321.0505 | 94.13 | 0.8805 | 9.213 | 1.341 |
-#> |.....................| 0.02633 | 0.7318 | 1.101 | 1.163 |
-#> | F| Forward Diff. | 53.55 | 0.8319 | 1.674 | -49.18 |
-#> |.....................| -9.827 | -0.8926 | -5.944 | -9.631 |
-#> | 27| 319.96320 | 1.003 | -1.007 | -0.9629 | -0.5048 |
-#> |.....................| -0.8978 | -0.9744 | -0.9184 | -0.8829 |
-#> | U| 319.9632 | 93.35 | -0.1280 | 2.219 | 1.352 |
-#> |.....................| 0.02633 | 0.7325 | 1.104 | 1.170 |
-#> | X| 319.9632 | 93.35 | 0.8798 | 9.197 | 1.352 |
-#> |.....................| 0.02633 | 0.7325 | 1.104 | 1.170 |
-#> | F| Forward Diff. | -57.14 | 0.7318 | 1.284 | -47.52 |
-#> |.....................| -9.778 | -0.7040 | -5.744 | -9.448 |
-#> | 28| 318.87595 | 1.011 | -1.008 | -0.9647 | -0.4840 |
-#> |.....................| -0.8984 | -0.9733 | -0.9148 | -0.8761 |
-#> | U| 318.87595 | 94.12 | -0.1289 | 2.217 | 1.364 |
-#> |.....................| 0.02633 | 0.7334 | 1.108 | 1.177 |
-#> | X| 318.87595 | 94.12 | 0.8790 | 9.180 | 1.364 |
-#> |.....................| 0.02633 | 0.7334 | 1.108 | 1.177 |
-#> | F| Forward Diff. | 50.84 | 0.8352 | 1.706 | -46.29 |
-#> |.....................| -8.837 | -0.9158 | -5.564 | -9.134 |
-#> | 29| 317.86528 | 1.003 | -1.009 | -0.9669 | -0.4631 |
-#> |.....................| -0.9000 | -0.9719 | -0.9113 | -0.8691 |
-#> | U| 317.86528 | 93.39 | -0.1300 | 2.215 | 1.375 |
-#> |.....................| 0.02631 | 0.7344 | 1.112 | 1.185 |
-#> | X| 317.86528 | 93.39 | 0.8781 | 9.160 | 1.375 |
-#> |.....................| 0.02631 | 0.7344 | 1.112 | 1.185 |
-#> | F| Forward Diff. | -53.64 | 0.7337 | 1.307 | -44.73 |
-#> |.....................| -8.788 | -0.7242 | -5.380 | -8.940 |
-#> | 30| 316.86653 | 1.011 | -1.010 | -0.9694 | -0.4424 |
-#> |.....................| -0.9029 | -0.9703 | -0.9078 | -0.8619 |
-#> | U| 316.86653 | 94.11 | -0.1312 | 2.212 | 1.386 |
-#> |.....................| 0.02627 | 0.7355 | 1.115 | 1.192 |
-#> | X| 316.86653 | 94.11 | 0.8771 | 9.137 | 1.386 |
-#> |.....................| 0.02627 | 0.7355 | 1.115 | 1.192 |
-#> | F| Forward Diff. | 47.91 | 0.8298 | 1.717 | -43.37 |
-#> |.....................| -7.860 | -0.7095 | -5.221 | -8.628 |
-#> | 31| 315.94581 | 1.003 | -1.012 | -0.9723 | -0.4219 |
-#> |.....................| -0.9070 | -0.9693 | -0.9044 | -0.8547 |
-#> | U| 315.94581 | 93.42 | -0.1325 | 2.209 | 1.398 |
-#> |.....................| 0.02622 | 0.7363 | 1.119 | 1.200 |
-#> | X| 315.94581 | 93.42 | 0.8759 | 9.111 | 1.398 |
-#> |.....................| 0.02622 | 0.7363 | 1.119 | 1.200 |
-#> | F| Forward Diff. | -50.84 | 0.7268 | 1.307 | -41.97 |
-#> |.....................| -7.840 | -0.5502 | -5.032 | -8.421 |
-#> | 32| 315.03994 | 1.011 | -1.013 | -0.9754 | -0.4018 |
-#> |.....................| -0.9129 | -0.9687 | -0.9011 | -0.8473 |
-#> | U| 315.03994 | 94.09 | -0.1340 | 2.206 | 1.409 |
-#> |.....................| 0.02615 | 0.7367 | 1.122 | 1.208 |
-#> | X| 315.03994 | 94.09 | 0.8746 | 9.082 | 1.409 |
-#> |.....................| 0.02615 | 0.7367 | 1.122 | 1.208 |
-#> | F| Forward Diff. | 43.50 | 0.8139 | 1.698 | -41.38 |
-#> |.....................| -7.196 | -0.9249 | -4.882 | -8.108 |
-#> | 33| 314.20198 | 1.004 | -1.015 | -0.9788 | -0.3816 |
-#> |.....................| -0.9197 | -0.9671 | -0.8983 | -0.8406 |
-#> | U| 314.20198 | 93.47 | -0.1355 | 2.203 | 1.420 |
-#> |.....................| 0.02606 | 0.7379 | 1.125 | 1.215 |
-#> | X| 314.20198 | 93.47 | 0.8733 | 9.052 | 1.420 |
-#> |.....................| 0.02606 | 0.7379 | 1.125 | 1.215 |
-#> | F| Forward Diff. | -46.04 | 0.7133 | 1.286 | -40.35 |
-#> |.....................| -7.243 | -0.8268 | -4.724 | -7.917 |
-#> | 34| 313.39087 | 1.011 | -1.016 | -0.9822 | -0.3616 |
-#> |.....................| -0.9277 | -0.9641 | -0.8960 | -0.8348 |
-#> | U| 313.39087 | 94.10 | -0.1371 | 2.200 | 1.431 |
-#> |.....................| 0.02596 | 0.7401 | 1.128 | 1.221 |
-#> | X| 313.39087 | 94.10 | 0.8719 | 9.021 | 1.431 |
-#> |.....................| 0.02596 | 0.7401 | 1.128 | 1.221 |
-#> | F| Forward Diff. | 42.44 | 0.7936 | 1.657 | -38.93 |
-#> |.....................| -6.417 | -0.6060 | -4.631 | -7.687 |
-#> | 35| 312.65204 | 1.004 | -1.018 | -0.9857 | -0.3421 |
-#> |.....................| -0.9371 | -0.9626 | -0.8936 | -0.8290 |
-#> | U| 312.65204 | 93.49 | -0.1387 | 2.196 | 1.441 |
-#> |.....................| 0.02584 | 0.7411 | 1.130 | 1.228 |
-#> | X| 312.65204 | 93.49 | 0.8705 | 8.989 | 1.441 |
-#> |.....................| 0.02584 | 0.7411 | 1.130 | 1.228 |
-#> | F| Forward Diff. | -46.74 | 0.6875 | 1.233 | -38.07 |
-#> |.....................| -6.520 | -0.5247 | -4.495 | -7.518 |
-#> | 36| 311.92333 | 1.010 | -1.020 | -0.9894 | -0.3235 |
-#> |.....................| -0.9483 | -0.9627 | -0.8910 | -0.8230 |
-#> | U| 311.92333 | 94.07 | -0.1404 | 2.192 | 1.452 |
-#> |.....................| 0.02570 | 0.7411 | 1.133 | 1.234 |
-#> | X| 311.92333 | 94.07 | 0.8690 | 8.957 | 1.452 |
-#> |.....................| 0.02570 | 0.7411 | 1.133 | 1.234 |
-#> | F| Forward Diff. | 35.63 | 0.7624 | 1.583 | -37.23 |
-#> |.....................| -5.893 | -0.6222 | -4.382 | -7.287 |
-#> | 37| 311.27355 | 1.004 | -1.021 | -0.9929 | -0.3046 |
-#> |.....................| -0.9595 | -0.9623 | -0.8888 | -0.8177 |
-#> | U| 311.27355 | 93.51 | -0.1420 | 2.189 | 1.462 |
-#> |.....................| 0.02556 | 0.7413 | 1.135 | 1.240 |
-#> | X| 311.27355 | 93.51 | 0.8676 | 8.925 | 1.462 |
-#> |.....................| 0.02556 | 0.7413 | 1.135 | 1.240 |
-#> | F| Forward Diff. | -45.98 | 0.6631 | 1.170 | -36.31 |
-#> |.....................| -5.950 | -0.4376 | -4.255 | -7.133 |
-#> | 38| 310.62439 | 1.010 | -1.023 | -0.9963 | -0.2868 |
-#> |.....................| -0.9728 | -0.9625 | -0.8869 | -0.8128 |
-#> | U| 310.62439 | 94.07 | -0.1437 | 2.185 | 1.472 |
-#> |.....................| 0.02539 | 0.7412 | 1.137 | 1.245 |
-#> | X| 310.62439 | 94.07 | 0.8661 | 8.895 | 1.472 |
-#> |.....................| 0.02539 | 0.7412 | 1.137 | 1.245 |
-#> | F| Forward Diff. | 33.19 | 0.7369 | 1.513 | -35.63 |
-#> |.....................| -5.399 | -0.5527 | -4.174 | -6.950 |
-#> | 39| 310.04420 | 1.005 | -1.024 | -0.9995 | -0.2687 |
-#> |.....................| -0.9859 | -0.9628 | -0.8850 | -0.8081 |
-#> | U| 310.0442 | 93.55 | -0.1453 | 2.182 | 1.482 |
-#> |.....................| 0.02523 | 0.7410 | 1.139 | 1.250 |
-#> | X| 310.0442 | 93.55 | 0.8648 | 8.866 | 1.482 |
-#> |.....................| 0.02523 | 0.7410 | 1.139 | 1.250 |
-#> | F| Forward Diff. | -43.63 | 0.6390 | 1.117 | -34.92 |
-#> |.....................| -5.491 | -0.4082 | -4.072 | -6.814 |
-#> | 40| 309.46411 | 1.010 | -1.026 | -1.003 | -0.2518 |
-#> |.....................| -1.001 | -0.9632 | -0.8835 | -0.8040 |
-#> | U| 309.46411 | 94.07 | -0.1468 | 2.179 | 1.491 |
-#> |.....................| 0.02504 | 0.7407 | 1.141 | 1.254 |
-#> | X| 309.46411 | 94.07 | 0.8634 | 8.839 | 1.491 |
-#> |.....................| 0.02504 | 0.7407 | 1.141 | 1.254 |
-#> | F| Forward Diff. | 30.94 | 0.7075 | 1.451 | -34.14 |
-#> |.....................| -4.970 | -0.4915 | -4.021 | -6.668 |
-#> | 41| 308.94397 | 1.005 | -1.027 | -1.005 | -0.2344 |
-#> |.....................| -1.015 | -0.9639 | -0.8817 | -0.7999 |
-#> | U| 308.94397 | 93.57 | -0.1483 | 2.176 | 1.500 |
-#> |.....................| 0.02486 | 0.7402 | 1.143 | 1.259 |
-#> | X| 308.94397 | 93.57 | 0.8622 | 8.814 | 1.500 |
-#> |.....................| 0.02486 | 0.7402 | 1.143 | 1.259 |
-#> | F| Forward Diff. | -43.40 | 0.6150 | 1.062 | -33.15 |
-#> |.....................| -4.981 | -0.1275 | -3.914 | -6.542 |
-#> | 42| 308.42636 | 1.010 | -1.029 | -1.008 | -0.2188 |
-#> |.....................| -1.031 | -0.9663 | -0.8797 | -0.7956 |
-#> | U| 308.42636 | 94.07 | -0.1498 | 2.174 | 1.509 |
-#> |.....................| 0.02466 | 0.7384 | 1.145 | 1.264 |
-#> | X| 308.42636 | 94.07 | 0.8609 | 8.789 | 1.509 |
-#> |.....................| 0.02466 | 0.7384 | 1.145 | 1.264 |
-#> | F| Forward Diff. | 28.94 | 0.6832 | 1.395 | -33.36 |
-#> |.....................| -4.720 | -0.6585 | -3.841 | -6.387 |
-#> | 43| 307.94294 | 1.006 | -1.030 | -1.011 | -0.2019 |
-#> |.....................| -1.047 | -0.9672 | -0.8783 | -0.7922 |
-#> | U| 307.94294 | 93.62 | -0.1511 | 2.171 | 1.518 |
-#> |.....................| 0.02447 | 0.7378 | 1.146 | 1.267 |
-#> | X| 307.94294 | 93.62 | 0.8597 | 8.766 | 1.518 |
-#> |.....................| 0.02447 | 0.7378 | 1.146 | 1.267 |
-#> | F| Forward Diff. | -38.44 | 0.5985 | 1.037 | -32.41 |
-#> |.....................| -4.734 | -0.3663 | -3.762 | -6.284 |
-#> | 44| 307.46797 | 1.011 | -1.032 | -1.013 | -0.1861 |
-#> |.....................| -1.063 | -0.9666 | -0.8774 | -0.7896 |
-#> | U| 307.46797 | 94.11 | -0.1524 | 2.169 | 1.527 |
-#> |.....................| 0.02426 | 0.7383 | 1.147 | 1.270 |
-#> | X| 307.46797 | 94.11 | 0.8586 | 8.746 | 1.527 |
-#> |.....................| 0.02426 | 0.7383 | 1.147 | 1.270 |
-#> | F| Forward Diff. | 31.70 | 0.6652 | 1.367 | -32.07 |
-#> |.....................| -4.364 | -0.4841 | -3.739 | -6.200 |
-#> | 45| 307.02197 | 1.006 | -1.033 | -1.016 | -0.1702 |
-#> |.....................| -1.080 | -0.9671 | -0.8762 | -0.7866 |
-#> | U| 307.02197 | 93.66 | -0.1537 | 2.166 | 1.536 |
-#> |.....................| 0.02405 | 0.7379 | 1.149 | 1.273 |
-#> | X| 307.02197 | 93.66 | 0.8575 | 8.725 | 1.536 |
-#> |.....................| 0.02405 | 0.7379 | 1.149 | 1.273 |
-#> | F| Forward Diff. | -34.81 | 0.5817 | 1.015 | -31.25 |
-#> |.....................| -4.413 | -0.2597 | -3.670 | -6.117 |
-#> | 46| 306.58875 | 1.011 | -1.034 | -1.018 | -0.1551 |
-#> |.....................| -1.097 | -0.9684 | -0.8747 | -0.7833 |
-#> | U| 306.58875 | 94.13 | -0.1549 | 2.164 | 1.544 |
-#> |.....................| 0.02384 | 0.7369 | 1.150 | 1.277 |
-#> | X| 306.58875 | 94.13 | 0.8565 | 8.705 | 1.544 |
-#> |.....................| 0.02384 | 0.7369 | 1.150 | 1.277 |
-#> | F| Forward Diff. | 31.47 | 0.6484 | 1.332 | -31.08 |
-#> |.....................| -4.101 | -0.4354 | -3.617 | -5.999 |
-#> | 47| 306.17343 | 1.006 | -1.035 | -1.020 | -0.1399 |
-#> |.....................| -1.114 | -0.9699 | -0.8732 | -0.7802 |
-#> | U| 306.17343 | 93.70 | -0.1561 | 2.162 | 1.552 |
-#> |.....................| 0.02362 | 0.7358 | 1.152 | 1.280 |
-#> | X| 306.17343 | 93.70 | 0.8554 | 8.686 | 1.552 |
-#> |.....................| 0.02362 | 0.7358 | 1.152 | 1.280 |
-#> | F| Forward Diff. | -31.81 | 0.5683 | 0.9956 | -30.69 |
-#> |.....................| -4.225 | -0.4059 | -3.540 | -5.903 |
-#> | 48| 305.76609 | 1.011 | -1.036 | -1.022 | -0.1248 |
-#> |.....................| -1.132 | -0.9702 | -0.8722 | -0.7778 |
-#> | U| 305.76609 | 94.14 | -0.1573 | 2.160 | 1.560 |
-#> |.....................| 0.02340 | 0.7356 | 1.153 | 1.283 |
-#> | X| 305.76609 | 94.14 | 0.8545 | 8.668 | 1.560 |
-#> |.....................| 0.02340 | 0.7356 | 1.153 | 1.283 |
-#> | F| Forward Diff. | 30.78 | 0.6301 | 1.297 | -30.24 |
-#> |.....................| -3.891 | -0.4278 | -3.502 | -5.825 |
-#> | 49| 305.37620 | 1.007 | -1.037 | -1.024 | -0.1098 |
-#> |.....................| -1.149 | -0.9705 | -0.8714 | -0.7755 |
-#> | U| 305.3762 | 93.72 | -0.1584 | 2.158 | 1.569 |
-#> |.....................| 0.02318 | 0.7354 | 1.154 | 1.285 |
-#> | X| 305.3762 | 93.72 | 0.8535 | 8.651 | 1.569 |
-#> |.....................| 0.02318 | 0.7354 | 1.154 | 1.285 |
-#> | F| Forward Diff. | -32.45 | 0.5512 | 0.9611 | -29.28 |
-#> |.....................| -3.904 | -0.09870 | -3.459 | -5.767 |
-#> | 50| 304.99974 | 1.011 | -1.039 | -1.026 | -0.09561 |
-#> |.....................| -1.167 | -0.9731 | -0.8699 | -0.7723 |
-#> | U| 304.99974 | 94.15 | -0.1595 | 2.156 | 1.576 |
-#> |.....................| 0.02295 | 0.7335 | 1.155 | 1.288 |
-#> | X| 304.99974 | 94.15 | 0.8526 | 8.633 | 1.576 |
-#> |.....................| 0.02295 | 0.7335 | 1.155 | 1.288 |
-#> | F| Forward Diff. | 30.20 | 0.6130 | 1.265 | -28.57 |
-#> |.....................| -3.511 | -0.04200 | -3.403 | -5.652 |
-#> | 51| 304.64794 | 1.007 | -1.040 | -1.028 | -0.08217 |
-#> |.....................| -1.185 | -0.9783 | -0.8678 | -0.7682 |
-#> | U| 304.64794 | 93.75 | -0.1607 | 2.153 | 1.584 |
-#> |.....................| 0.02273 | 0.7297 | 1.157 | 1.293 |
-#> | X| 304.64794 | 93.75 | 0.8516 | 8.614 | 1.584 |
-#> |.....................| 0.02273 | 0.7297 | 1.157 | 1.293 |
-#> | F| Forward Diff. | -30.08 | 0.5385 | 0.9408 | -28.96 |
-#> |.....................| -3.779 | -0.3908 | -3.281 | -5.515 |
-#> | 52| 304.28931 | 1.011 | -1.041 | -1.030 | -0.06828 |
-#> |.....................| -1.203 | -0.9811 | -0.8668 | -0.7655 |
-#> | U| 304.28931 | 94.14 | -0.1618 | 2.151 | 1.591 |
-#> |.....................| 0.02250 | 0.7277 | 1.158 | 1.296 |
-#> | X| 304.28931 | 94.14 | 0.8506 | 8.597 | 1.591 |
-#> |.....................| 0.02250 | 0.7277 | 1.158 | 1.296 |
-#> | 53| 304.03244 | 1.011 | -1.042 | -1.033 | -0.05709 |
-#> |.....................| -1.225 | -0.9843 | -0.8662 | -0.7633 |
-#> | U| 304.03244 | 94.13 | -0.1630 | 2.149 | 1.597 |
-#> |.....................| 0.02223 | 0.7253 | 1.159 | 1.298 |
-#> | X| 304.03244 | 94.13 | 0.8496 | 8.578 | 1.597 |
-#> |.....................| 0.02223 | 0.7253 | 1.159 | 1.298 |
-#> | 54| 302.98899 | 1.011 | -1.047 | -1.041 | -0.01055 |
-#> |.....................| -1.314 | -0.9977 | -0.8638 | -0.7544 |
-#> | U| 302.98899 | 94.10 | -0.1678 | 2.140 | 1.623 |
-#> |.....................| 0.02111 | 0.7156 | 1.161 | 1.308 |
-#> | X| 302.98899 | 94.10 | 0.8455 | 8.503 | 1.623 |
-#> |.....................| 0.02111 | 0.7156 | 1.161 | 1.308 |
-#> | 55| 298.89653 | 1.010 | -1.068 | -1.080 | 0.1944 |
-#> |.....................| -1.708 | -1.057 | -0.8531 | -0.7150 |
-#> | U| 298.89653 | 93.99 | -0.1892 | 2.101 | 1.735 |
-#> |.....................| 0.01618 | 0.6726 | 1.173 | 1.350 |
-#> | X| 298.89653 | 93.99 | 0.8276 | 8.177 | 1.735 |
-#> |.....................| 0.01618 | 0.6726 | 1.173 | 1.350 |
-#> | 56| 292.24425 | 1.012 | -1.205 | -1.331 | 1.218 |
-#> |.....................| -2.997 | -1.313 | -0.8095 | -0.4981 |
-#> | U| 292.24425 | 94.21 | -0.3257 | 1.851 | 2.296 |
-#> |.....................| 5.960e-07 | 0.4863 | 1.218 | 1.582 |
-#> | X| 292.24425 | 94.21 | 0.7221 | 6.365 | 2.296 |
-#> |.....................| 5.960e-07 | 0.4863 | 1.218 | 1.582 |
-#> | F| Forward Diff. | -17.20 | -1.896 | -10.23 | 0.3663 |
-#> |.....................| 0.002021 | -17.85 | 0.1528 | 5.292 |
-#> | 57| 309.71599 | 0.9897 | -1.187 | -0.4357 | 2.442 |
-#> |.....................| -2.997 | 0.5394 | -0.6812 | -0.7129 |
-#> | U| 309.71599 | 92.14 | -0.3076 | 2.746 | 2.966 |
-#> |.....................| 5.960e-07 | 1.833 | 1.352 | 1.352 |
-#> | X| 309.71599 | 92.14 | 0.7352 | 15.58 | 2.966 |
-#> |.....................| 5.960e-07 | 1.833 | 1.352 | 1.352 |
-#> | 58| 292.01474 | 1.005 | -1.198 | -1.013 | 1.651 |
-#> |.....................| -2.997 | -0.6561 | -0.7641 | -0.5745 |
-#> | U| 292.01474 | 93.60 | -0.3191 | 2.168 | 2.533 |
-#> |.....................| 5.960e-07 | 0.9640 | 1.266 | 1.501 |
-#> | X| 292.01474 | 93.60 | 0.7268 | 8.745 | 2.533 |
-#> |.....................| 5.960e-07 | 0.9640 | 1.266 | 1.501 |
-#> | F| Forward Diff. | -172.4 | -2.986 | 3.411 | 4.977 |
-#> |.....................| 0.05585 | 3.841 | 3.028 | 0.3322 |
-#> | 59| 292.30890 | 1.013 | -0.8632 | -1.158 | 1.672 |
-#> |.....................| -2.997 | -0.5770 | -0.9665 | -0.6082 |
-#> | U| 292.3089 | 94.28 | 0.01586 | 2.024 | 2.544 |
-#> |.....................| 5.960e-07 | 1.022 | 1.054 | 1.464 |
-#> | X| 292.3089 | 94.28 | 1.016 | 7.565 | 2.544 |
-#> |.....................| 5.960e-07 | 1.022 | 1.054 | 1.464 |
-#> | 60| 291.20170 | 1.015 | -1.046 | -1.079 | 1.660 |
-#> |.....................| -2.997 | -0.6203 | -0.8561 | -0.5898 |
-#> | U| 291.2017 | 94.51 | -0.1669 | 2.103 | 2.538 |
-#> |.....................| 5.960e-07 | 0.9900 | 1.170 | 1.484 |
-#> | X| 291.2017 | 94.51 | 0.8462 | 8.187 | 2.538 |
-#> |.....................| 5.960e-07 | 0.9900 | 1.170 | 1.484 |
-#> | F| Forward Diff. | 39.51 | 0.9033 | 2.112 | 5.106 |
-#> |.....................| 0.03418 | 2.863 | -2.696 | -0.7695 |
-#> | 61| 291.43833 | 1.017 | -1.033 | -1.136 | 1.600 |
-#> |.....................| -2.997 | -0.6066 | -0.6851 | -0.5537 |
-#> | U| 291.43833 | 94.73 | -0.1542 | 2.046 | 2.505 |
-#> |.....................| 5.960e-07 | 1.000 | 1.348 | 1.523 |
-#> | X| 291.43833 | 94.73 | 0.8571 | 7.739 | 2.505 |
-#> |.....................| 5.960e-07 | 1.000 | 1.348 | 1.523 |
-#> | 62| 290.99248 | 1.014 | -1.041 | -1.101 | 1.637 |
-#> |.....................| -2.997 | -0.6152 | -0.7907 | -0.5760 |
-#> | U| 290.99248 | 94.43 | -0.1621 | 2.081 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9938 | 1.238 | 1.499 |
-#> | X| 290.99248 | 94.43 | 0.8503 | 8.012 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9938 | 1.238 | 1.499 |
-#> | F| Forward Diff. | 14.98 | 1.278 | 1.101 | 4.858 |
-#> |.....................| 0.03639 | 3.021 | 0.9673 | -0.2780 |
-#> | 63| 291.02454 | 1.009 | -1.102 | -1.088 | 1.608 |
-#> |.....................| -2.997 | -0.6330 | -0.7900 | -0.5542 |
-#> | U| 291.02454 | 93.95 | -0.2228 | 2.094 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9808 | 1.239 | 1.522 |
-#> | X| 291.02454 | 93.95 | 0.8003 | 8.118 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9808 | 1.239 | 1.522 |
-#> | 64| 291.12722 | 1.009 | -1.068 | -1.095 | 1.623 |
-#> |.....................| -2.997 | -0.6237 | -0.7906 | -0.5663 |
-#> | U| 291.12722 | 93.94 | -0.1892 | 2.087 | 2.518 |
-#> |.....................| 5.960e-07 | 0.9876 | 1.238 | 1.509 |
-#> | X| 291.12722 | 93.94 | 0.8276 | 8.057 | 2.518 |
-#> |.....................| 5.960e-07 | 0.9876 | 1.238 | 1.509 |
-#> | 65| 291.20836 | 1.009 | -1.048 | -1.100 | 1.633 |
-#> |.....................| -2.997 | -0.6180 | -0.7910 | -0.5738 |
-#> | U| 291.20836 | 93.93 | -0.1686 | 2.082 | 2.523 |
-#> |.....................| 5.960e-07 | 0.9918 | 1.238 | 1.501 |
-#> | X| 291.20836 | 93.93 | 0.8449 | 8.020 | 2.523 |
-#> |.....................| 5.960e-07 | 0.9918 | 1.238 | 1.501 |
-#> | 66| 290.99661 | 1.013 | -1.041 | -1.101 | 1.637 |
-#> |.....................| -2.997 | -0.6156 | -0.7909 | -0.5760 |
-#> | U| 290.99661 | 94.27 | -0.1623 | 2.081 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9935 | 1.238 | 1.499 |
-#> | X| 290.99661 | 94.27 | 0.8502 | 8.011 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9935 | 1.238 | 1.499 |
-#> | 67| 290.98636 | 1.014 | -1.041 | -1.101 | 1.637 |
-#> |.....................| -2.997 | -0.6154 | -0.7908 | -0.5760 |
-#> | U| 290.98636 | 94.36 | -0.1622 | 2.081 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9936 | 1.238 | 1.499 |
-#> | X| 290.98636 | 94.36 | 0.8503 | 8.012 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9936 | 1.238 | 1.499 |
-#> | F| Forward Diff. | -1.956 | 1.256 | 0.9523 | 4.835 |
-#> |.....................| 0.03649 | 3.031 | 0.9657 | -0.2695 |
-#> | 68| 290.98211 | 1.014 | -1.041 | -1.101 | 1.636 |
-#> |.....................| -2.997 | -0.6157 | -0.7909 | -0.5760 |
-#> | U| 290.98211 | 94.38 | -0.1623 | 2.081 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9934 | 1.238 | 1.499 |
-#> | X| 290.98211 | 94.38 | 0.8502 | 8.011 | 2.525 |
-#> |.....................| 5.960e-07 | 0.9934 | 1.238 | 1.499 |
-#> | 69| 290.97746 | 1.014 | -1.042 | -1.101 | 1.635 |
-#> |.....................| -2.997 | -0.6167 | -0.7912 | -0.5759 |
-#> | U| 290.97746 | 94.44 | -0.1627 | 2.081 | 2.524 |
-#> |.....................| 5.960e-07 | 0.9927 | 1.237 | 1.499 |
-#> | X| 290.97746 | 94.44 | 0.8498 | 8.009 | 2.524 |
-#> |.....................| 5.960e-07 | 0.9927 | 1.237 | 1.499 |
-#> | F| Forward Diff. | 17.70 | 1.268 | 1.108 | 4.855 |
-#> |.....................| 0.04257 | 3.066 | 0.9427 | -0.2771 |
-#> | 70| 290.96180 | 1.014 | -1.044 | -1.101 | 1.634 |
-#> |.....................| -2.997 | -0.6175 | -0.7910 | -0.5752 |
-#> | U| 290.9618 | 94.36 | -0.1647 | 2.081 | 2.523 |
-#> |.....................| 5.960e-07 | 0.9921 | 1.238 | 1.500 |
-#> | X| 290.9618 | 94.36 | 0.8481 | 8.013 | 2.523 |
-#> |.....................| 5.960e-07 | 0.9921 | 1.238 | 1.500 |
-#> | F| Forward Diff. | -1.598 | 1.197 | 0.9704 | 4.824 |
-#> |.....................| 0.03731 | 2.941 | 0.9551 | -0.2334 |
-#> | 71| 290.95083 | 1.014 | -1.044 | -1.101 | 1.632 |
-#> |.....................| -2.997 | -0.6188 | -0.7915 | -0.5751 |
-#> | U| 290.95083 | 94.43 | -0.1653 | 2.081 | 2.522 |
-#> |.....................| 5.960e-07 | 0.9912 | 1.237 | 1.500 |
-#> | X| 290.95083 | 94.43 | 0.8477 | 8.010 | 2.522 |
-#> |.....................| 5.960e-07 | 0.9912 | 1.237 | 1.500 |
-#> | F| Forward Diff. | 14.81 | 1.204 | 1.097 | 4.820 |
-#> |.....................| 0.03908 | 3.014 | 0.9116 | -0.2462 |
-#> | 72| 290.93714 | 1.014 | -1.046 | -1.101 | 1.630 |
-#> |.....................| -2.997 | -0.6196 | -0.7913 | -0.5744 |
-#> | U| 290.93714 | 94.36 | -0.1673 | 2.081 | 2.522 |
-#> |.....................| 5.960e-07 | 0.9906 | 1.237 | 1.501 |
-#> | X| 290.93714 | 94.36 | 0.8459 | 8.014 | 2.522 |
-#> |.....................| 5.960e-07 | 0.9906 | 1.237 | 1.501 |
-#> | F| Forward Diff. | -1.943 | 1.135 | 0.9791 | 4.793 |
-#> |.....................| 0.03360 | 3.051 | 0.9080 | -0.2200 |
-#> | 73| 290.92845 | 1.014 | -1.047 | -1.101 | 1.628 |
-#> |.....................| -2.997 | -0.6209 | -0.7917 | -0.5743 |
-#> | U| 290.92845 | 94.44 | -0.1678 | 2.081 | 2.521 |
-#> |.....................| 5.960e-07 | 0.9896 | 1.237 | 1.501 |
-#> | X| 290.92845 | 94.44 | 0.8455 | 8.011 | 2.521 |
-#> |.....................| 5.960e-07 | 0.9896 | 1.237 | 1.501 |
-#> | F| Forward Diff. | 17.70 | 1.147 | 1.134 | 4.752 |
-#> |.....................| 0.02729 | 3.018 | 0.8867 | -0.2229 |
-#> | 74| 290.91300 | 1.014 | -1.049 | -1.100 | 1.627 |
-#> |.....................| -2.997 | -0.6219 | -0.7915 | -0.5737 |
-#> | U| 290.913 | 94.36 | -0.1698 | 2.081 | 2.520 |
-#> |.....................| 5.960e-07 | 0.9889 | 1.237 | 1.501 |
-#> | X| 290.913 | 94.36 | 0.8439 | 8.016 | 2.520 |
-#> |.....................| 5.960e-07 | 0.9889 | 1.237 | 1.501 |
-#> | F| Forward Diff. | -1.940 | 1.078 | 0.9981 | 4.722 |
-#> |.....................| 0.04064 | 3.105 | 0.9143 | -0.1849 |
-#> | 75| 290.90444 | 1.014 | -1.049 | -1.101 | 1.625 |
-#> |.....................| -2.997 | -0.6232 | -0.7919 | -0.5736 |
-#> | U| 290.90444 | 94.44 | -0.1702 | 2.081 | 2.519 |
-#> |.....................| 5.960e-07 | 0.9879 | 1.237 | 1.501 |
-#> | X| 290.90444 | 94.44 | 0.8435 | 8.013 | 2.519 |
-#> |.....................| 5.960e-07 | 0.9879 | 1.237 | 1.501 |
-#> | F| Forward Diff. | 17.76 | 1.091 | 1.153 | 4.713 |
-#> |.....................| 0.03198 | 2.950 | 0.8627 | -0.2001 |
-#> | 76| 290.88905 | 1.014 | -1.051 | -1.100 | 1.624 |
-#> |.....................| -2.997 | -0.6243 | -0.7916 | -0.5732 |
-#> | U| 290.88905 | 94.36 | -0.1722 | 2.082 | 2.518 |
-#> |.....................| 5.960e-07 | 0.9872 | 1.237 | 1.502 |
-#> | X| 290.88905 | 94.36 | 0.8418 | 8.019 | 2.518 |
-#> |.....................| 5.960e-07 | 0.9872 | 1.237 | 1.502 |
-#> | F| Forward Diff. | -2.112 | 1.022 | 1.016 | 4.749 |
-#> |.....................| 0.03990 | 3.117 | 0.8810 | -0.1779 |
-#> | 77| 290.87937 | 1.014 | -1.052 | -1.100 | 1.622 |
-#> |.....................| -2.997 | -0.6257 | -0.7918 | -0.5730 |
-#> | U| 290.87937 | 94.43 | -0.1731 | 2.082 | 2.517 |
-#> |.....................| 5.960e-07 | 0.9861 | 1.237 | 1.502 |
-#> | X| 290.87937 | 94.43 | 0.8411 | 8.018 | 2.517 |
-#> |.....................| 5.960e-07 | 0.9861 | 1.237 | 1.502 |
-#> | F| Forward Diff. | 15.72 | 1.022 | 1.168 | 4.728 |
-#> |.....................| 0.04036 | 3.118 | 0.8621 | -0.1806 |
-#> | 78| 290.86528 | 1.014 | -1.054 | -1.099 | 1.621 |
-#> |.....................| -2.997 | -0.6269 | -0.7915 | -0.5727 |
-#> | U| 290.86528 | 94.36 | -0.1749 | 2.083 | 2.516 |
-#> |.....................| 5.960e-07 | 0.9853 | 1.237 | 1.502 |
-#> | X| 290.86528 | 94.36 | 0.8396 | 8.025 | 2.516 |
-#> |.....................| 5.960e-07 | 0.9853 | 1.237 | 1.502 |
-#> | F| Forward Diff. | -2.089 | 0.9583 | 1.055 | 4.711 |
-#> |.....................| 0.04161 | 3.089 | 0.8790 | -0.1555 |
-#> | 79| 290.85625 | 1.014 | -1.055 | -1.099 | 1.619 |
-#> |.....................| -2.997 | -0.6283 | -0.7918 | -0.5726 |
-#> | U| 290.85625 | 94.44 | -0.1756 | 2.082 | 2.515 |
-#> |.....................| 5.960e-07 | 0.9842 | 1.237 | 1.503 |
-#> | X| 290.85625 | 94.44 | 0.8389 | 8.023 | 2.515 |
-#> |.....................| 5.960e-07 | 0.9842 | 1.237 | 1.503 |
-#> | F| Forward Diff. | 16.77 | 0.9641 | 1.212 | 4.706 |
-#> |.....................| 0.04215 | 3.138 | 0.8554 | -0.1643 |
-#> | 80| 290.84140 | 1.014 | -1.056 | -1.099 | 1.618 |
-#> |.....................| -2.997 | -0.6296 | -0.7915 | -0.5724 |
-#> | U| 290.8414 | 94.36 | -0.1774 | 2.083 | 2.515 |
-#> |.....................| 5.960e-07 | 0.9833 | 1.237 | 1.503 |
-#> | X| 290.8414 | 94.36 | 0.8375 | 8.030 | 2.515 |
-#> |.....................| 5.960e-07 | 0.9833 | 1.237 | 1.503 |
-#> | F| Forward Diff. | -1.641 | 0.9006 | 1.093 | 4.694 |
-#> |.....................| 0.04205 | 3.147 | 0.8775 | -0.1452 |
-#> | 81| 290.83107 | 1.014 | -1.057 | -1.099 | 1.616 |
-#> |.....................| -2.997 | -0.6310 | -0.7919 | -0.5723 |
-#> | U| 290.83107 | 94.43 | -0.1778 | 2.083 | 2.514 |
-#> |.....................| 5.960e-07 | 0.9823 | 1.237 | 1.503 |
-#> | X| 290.83107 | 94.43 | 0.8371 | 8.026 | 2.514 |
-#> |.....................| 5.960e-07 | 0.9823 | 1.237 | 1.503 |
-#> | F| Forward Diff. | 15.22 | 0.9116 | 1.221 | 4.655 |
-#> |.....................| 0.04015 | 3.140 | 0.8393 | -0.1501 |
-#> | 82| 290.81725 | 1.014 | -1.059 | -1.098 | 1.615 |
-#> |.....................| -2.997 | -0.6323 | -0.7916 | -0.5722 |
-#> | U| 290.81725 | 94.36 | -0.1795 | 2.084 | 2.513 |
-#> |.....................| 5.960e-07 | 0.9813 | 1.237 | 1.503 |
-#> | X| 290.81725 | 94.36 | 0.8357 | 8.034 | 2.513 |
-#> |.....................| 5.960e-07 | 0.9813 | 1.237 | 1.503 |
-#> | F| Forward Diff. | -2.105 | 0.8517 | 1.114 | 4.660 |
-#> |.....................| 0.03878 | 3.162 | 0.8666 | -0.1313 |
-#> | 83| 290.80795 | 1.014 | -1.059 | -1.098 | 1.613 |
-#> |.....................| -2.997 | -0.6339 | -0.7918 | -0.5722 |
-#> | U| 290.80795 | 94.43 | -0.1802 | 2.084 | 2.512 |
-#> |.....................| 5.960e-07 | 0.9802 | 1.237 | 1.503 |
-#> | X| 290.80795 | 94.43 | 0.8351 | 8.033 | 2.512 |
-#> |.....................| 5.960e-07 | 0.9802 | 1.237 | 1.503 |
-#> | F| Forward Diff. | 16.11 | 0.8564 | 1.267 | 4.653 |
-#> |.....................| 0.04303 | 3.178 | 0.8469 | -0.1413 |
-#> | 84| 290.79348 | 1.014 | -1.061 | -1.097 | 1.611 |
-#> |.....................| -2.997 | -0.6353 | -0.7914 | -0.5722 |
-#> | U| 290.79348 | 94.36 | -0.1817 | 2.084 | 2.511 |
-#> |.....................| 5.960e-07 | 0.9792 | 1.237 | 1.503 |
-#> | X| 290.79348 | 94.36 | 0.8338 | 8.041 | 2.511 |
-#> |.....................| 5.960e-07 | 0.9792 | 1.237 | 1.503 |
-#> | F| Forward Diff. | -1.840 | 0.7976 | 1.155 | 4.587 |
-#> |.....................| 0.02723 | 3.115 | 0.8603 | -0.1275 |
-#> | 85| 290.78474 | 1.014 | -1.061 | -1.098 | 1.609 |
-#> |.....................| -2.997 | -0.6367 | -0.7918 | -0.5721 |
-#> | U| 290.78474 | 94.44 | -0.1821 | 2.084 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9781 | 1.237 | 1.503 |
-#> | X| 290.78474 | 94.44 | 0.8335 | 8.036 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9781 | 1.237 | 1.503 |
-#> | F| Forward Diff. | 17.19 | 0.8130 | 1.300 | 4.618 |
-#> |.....................| 0.03919 | 3.190 | 0.8345 | -0.1328 |
-#> | 86| 290.76934 | 1.014 | -1.063 | -1.097 | 1.608 |
-#> |.....................| -2.997 | -0.6382 | -0.7915 | -0.5722 |
-#> | U| 290.76934 | 94.36 | -0.1836 | 2.085 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9771 | 1.237 | 1.503 |
-#> | X| 290.76934 | 94.36 | 0.8322 | 8.044 | 2.510 |
-#> |.....................| 5.960e-07 | 0.9771 | 1.237 | 1.503 |
-#> | F| Forward Diff. | -1.203 | 0.7543 | 1.182 | 4.565 |
-#> |.....................| 0.03490 | 3.166 | 0.8589 | -0.1256 |
-#> | 87| 290.75687 | 1.014 | -1.063 | -1.097 | 1.606 |
-#> |.....................| -2.997 | -0.6397 | -0.7919 | -0.5722 |
-#> | U| 290.75687 | 94.41 | -0.1840 | 2.084 | 2.508 |
-#> |.....................| 5.960e-07 | 0.9760 | 1.237 | 1.503 |
-#> | X| 290.75687 | 94.41 | 0.8319 | 8.039 | 2.508 |
-#> |.....................| 5.960e-07 | 0.9760 | 1.237 | 1.503 |
-#> | 88| 290.75123 | 1.015 | -1.063 | -1.098 | 1.604 |
-#> |.....................| -2.997 | -0.6414 | -0.7924 | -0.5721 |
-#> | U| 290.75123 | 94.47 | -0.1844 | 2.084 | 2.507 |
-#> |.....................| 5.960e-07 | 0.9747 | 1.236 | 1.503 |
-#> | X| 290.75123 | 94.47 | 0.8316 | 8.034 | 2.507 |
-#> |.....................| 5.960e-07 | 0.9747 | 1.236 | 1.503 |
-#> | F| Forward Diff. | 26.23 | 0.7709 | 1.374 | 4.560 |
-#> |.....................| 0.04194 | 3.213 | 0.7966 | -0.1353 |
-#> | 89| 290.71744 | 1.014 | -1.067 | -1.096 | 1.601 |
-#> |.....................| -2.997 | -0.6448 | -0.7915 | -0.5726 |
-#> | U| 290.71744 | 94.37 | -0.1875 | 2.086 | 2.506 |
-#> |.....................| 5.960e-07 | 0.9722 | 1.237 | 1.503 |
-#> | X| 290.71744 | 94.37 | 0.8291 | 8.054 | 2.506 |
-#> |.....................| 5.960e-07 | 0.9722 | 1.237 | 1.503 |
-#> | F| Forward Diff. | 0.1928 | 0.6670 | 1.256 | 4.555 |
-#> |.....................| 0.04212 | 3.227 | 0.8436 | -0.1302 |
-#> | 90| 290.68496 | 1.013 | -1.067 | -1.097 | 1.597 |
-#> |.....................| -2.997 | -0.6481 | -0.7924 | -0.5725 |
-#> | U| 290.68496 | 94.35 | -0.1881 | 2.085 | 2.503 |
-#> |.....................| 5.960e-07 | 0.9698 | 1.236 | 1.503 |
-#> | X| 290.68496 | 94.35 | 0.8285 | 8.044 | 2.503 |
-#> |.....................| 5.960e-07 | 0.9698 | 1.236 | 1.503 |
-#> | 91| 290.59496 | 1.013 | -1.069 | -1.101 | 1.583 |
-#> |.....................| -2.997 | -0.6580 | -0.7950 | -0.5721 |
-#> | U| 290.59496 | 94.29 | -0.1902 | 2.081 | 2.496 |
-#> |.....................| 5.960e-07 | 0.9627 | 1.233 | 1.503 |
-#> | X| 290.59496 | 94.29 | 0.8268 | 8.013 | 2.496 |
-#> |.....................| 5.960e-07 | 0.9627 | 1.233 | 1.503 |
-#> | 92| 290.34408 | 1.010 | -1.077 | -1.116 | 1.527 |
-#> |.....................| -2.997 | -0.6974 | -0.8053 | -0.5705 |
-#> | U| 290.34408 | 94.08 | -0.1983 | 2.066 | 2.465 |
-#> |.....................| 5.960e-07 | 0.9340 | 1.223 | 1.505 |
-#> | X| 290.34408 | 94.08 | 0.8201 | 7.891 | 2.465 |
-#> |.....................| 5.960e-07 | 0.9340 | 1.223 | 1.505 |
-#> | F| Forward Diff. | -74.08 | 0.3588 | -0.1794 | 3.803 |
-#> |.....................| 0.04205 | 3.779 | 0.06785 | -0.005437 |
-#> | 93| 289.95778 | 1.012 | -1.081 | -1.068 | 1.490 |
-#> |.....................| -2.997 | -0.7670 | -0.7909 | -0.5845 |
-#> | U| 289.95778 | 94.18 | -0.2020 | 2.114 | 2.445 |
-#> |.....................| 5.960e-07 | 0.8834 | 1.238 | 1.490 |
-#> | X| 289.95778 | 94.18 | 0.8171 | 8.282 | 2.445 |
-#> |.....................| 5.960e-07 | 0.8834 | 1.238 | 1.490 |
-#> | 94| 289.83089 | 1.009 | -1.086 | -1.006 | 1.442 |
-#> |.....................| -2.997 | -0.8563 | -0.7725 | -0.6025 |
-#> | U| 289.83089 | 93.98 | -0.2067 | 2.176 | 2.418 |
-#> |.....................| 5.960e-07 | 0.8185 | 1.257 | 1.470 |
-#> | X| 289.83089 | 93.98 | 0.8132 | 8.812 | 2.418 |
-#> |.....................| 5.960e-07 | 0.8185 | 1.257 | 1.470 |
-#> | F| Forward Diff. | -65.01 | -0.01626 | 4.198 | 3.297 |
-#> |.....................| 0.05097 | 3.562 | 1.909 | -0.3175 |
-#> | 95| 290.63229 | 1.014 | -1.226 | -1.068 | 1.287 |
-#> |.....................| -2.997 | -1.101 | -0.7595 | -0.8853 |
-#> | U| 290.63229 | 94.43 | -0.3467 | 2.113 | 2.333 |
-#> |.....................| 5.960e-07 | 0.6407 | 1.271 | 1.167 |
-#> | X| 290.63229 | 94.43 | 0.7070 | 8.277 | 2.333 |
-#> |.....................| 5.960e-07 | 0.6407 | 1.271 | 1.167 |
-#> | 96| 289.56584 | 1.017 | -1.134 | -1.028 | 1.388 |
-#> |.....................| -2.997 | -0.9416 | -0.7681 | -0.7007 |
-#> | U| 289.56584 | 94.70 | -0.2554 | 2.154 | 2.389 |
-#> |.....................| 5.960e-07 | 0.7564 | 1.261 | 1.365 |
-#> | X| 289.56584 | 94.70 | 0.7746 | 8.619 | 2.389 |
-#> |.....................| 5.960e-07 | 0.7564 | 1.261 | 1.365 |
-#> | F| Forward Diff. | 59.80 | -0.9076 | 3.450 | 2.884 |
-#> |.....................| 0.04168 | 2.247 | 1.868 | -3.338 |
-#> | 97| 289.16078 | 1.017 | -1.094 | -1.010 | 1.317 |
-#> |.....................| -2.997 | -0.9798 | -0.7948 | -0.5837 |
-#> | U| 289.16078 | 94.64 | -0.2152 | 2.172 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7287 | 1.234 | 1.491 |
-#> | X| 289.16078 | 94.64 | 0.8063 | 8.773 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7287 | 1.234 | 1.491 |
-#> | F| Forward Diff. | 50.77 | -0.08196 | 5.132 | 1.948 |
-#> |.....................| 0.04608 | 1.474 | 0.6389 | 0.4459 |
-#> | 98| 290.19527 | 1.002 | -1.018 | -1.037 | 1.157 |
-#> |.....................| -2.997 | -1.195 | -0.7989 | -0.6967 |
-#> | U| 290.19527 | 93.32 | -0.1385 | 2.145 | 2.263 |
-#> |.....................| 5.960e-07 | 0.5724 | 1.229 | 1.370 |
-#> | X| 290.19527 | 93.32 | 0.8707 | 8.542 | 2.263 |
-#> |.....................| 5.960e-07 | 0.5724 | 1.229 | 1.370 |
-#> | 99| 289.65582 | 1.003 | -1.072 | -1.019 | 1.270 |
-#> |.....................| -2.997 | -1.043 | -0.7961 | -0.6170 |
-#> | U| 289.65582 | 93.34 | -0.1926 | 2.163 | 2.324 |
-#> |.....................| 5.960e-07 | 0.6825 | 1.232 | 1.455 |
-#> | X| 289.65582 | 93.34 | 0.8248 | 8.696 | 2.324 |
-#> |.....................| 5.960e-07 | 0.6825 | 1.232 | 1.455 |
-#> | 100| 289.77865 | 1.003 | -1.088 | -1.014 | 1.303 |
-#> |.....................| -2.997 | -0.9984 | -0.7953 | -0.5934 |
-#> | U| 289.77865 | 93.35 | -0.2087 | 2.168 | 2.342 |
-#> |.....................| 5.960e-07 | 0.7151 | 1.233 | 1.480 |
-#> | X| 289.77865 | 93.35 | 0.8116 | 8.742 | 2.342 |
-#> |.....................| 5.960e-07 | 0.7151 | 1.233 | 1.480 |
-#> | 101| 289.23886 | 1.008 | -1.094 | -1.011 | 1.317 |
-#> |.....................| -2.997 | -0.9800 | -0.7949 | -0.5837 |
-#> | U| 289.23886 | 93.87 | -0.2152 | 2.171 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7285 | 1.234 | 1.491 |
-#> | X| 289.23886 | 93.87 | 0.8064 | 8.765 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7285 | 1.234 | 1.491 |
-#> | 102| 289.07165 | 1.013 | -1.094 | -1.010 | 1.317 |
-#> |.....................| -2.997 | -0.9799 | -0.7948 | -0.5837 |
-#> | U| 289.07165 | 94.31 | -0.2152 | 2.171 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7286 | 1.234 | 1.491 |
-#> | X| 289.07165 | 94.31 | 0.8063 | 8.770 | 2.350 |
-#> |.....................| 5.960e-07 | 0.7286 | 1.234 | 1.491 |
-#> | F| Forward Diff. | -0.3607 | -0.1394 | 4.728 | 1.937 |
-#> |.....................| 0.04518 | 1.333 | 0.6601 | 0.3686 |
-#> | 103| 289.05383 | 1.013 | -1.094 | -1.014 | 1.315 |
-#> |.....................| -2.997 | -0.9807 | -0.7952 | -0.5839 |
-#> | U| 289.05383 | 94.33 | -0.2152 | 2.168 | 2.349 |
-#> |.....................| 5.960e-07 | 0.7280 | 1.233 | 1.490 |
-#> | X| 289.05383 | 94.33 | 0.8064 | 8.742 | 2.349 |
-#> |.....................| 5.960e-07 | 0.7280 | 1.233 | 1.490 |
-#> | 104| 289.00706 | 1.014 | -1.094 | -1.023 | 1.312 |
-#> |.....................| -2.997 | -0.9834 | -0.7965 | -0.5847 |
-#> | U| 289.00706 | 94.40 | -0.2149 | 2.159 | 2.347 |
-#> |.....................| 5.960e-07 | 0.7260 | 1.232 | 1.490 |
-#> | X| 289.00706 | 94.40 | 0.8066 | 8.661 | 2.347 |
-#> |.....................| 5.960e-07 | 0.7260 | 1.232 | 1.490 |
-#> | 105| 288.92149 | 1.016 | -1.093 | -1.055 | 1.299 |
-#> |.....................| -2.997 | -0.9924 | -0.8010 | -0.5872 |
-#> | U| 288.92149 | 94.63 | -0.2139 | 2.127 | 2.340 |
-#> |.....................| 5.960e-07 | 0.7195 | 1.227 | 1.487 |
-#> | X| 288.92149 | 94.63 | 0.8074 | 8.388 | 2.340 |
-#> |.....................| 5.960e-07 | 0.7195 | 1.227 | 1.487 |
-#> | F| Forward Diff. | 43.21 | 0.03028 | 3.221 | 1.557 |
-#> |.....................| 0.008151 | 1.175 | 0.2057 | -0.1154 |
-#> | 106| 288.79118 | 1.014 | -1.096 | -1.061 | 1.264 |
-#> |.....................| -2.997 | -1.027 | -0.7973 | -0.5956 |
-#> | U| 288.79118 | 94.43 | -0.2174 | 2.120 | 2.321 |
-#> |.....................| 5.960e-07 | 0.6943 | 1.231 | 1.478 |
-#> | X| 288.79118 | 94.43 | 0.8046 | 8.334 | 2.321 |
-#> |.....................| 5.960e-07 | 0.6943 | 1.231 | 1.478 |
-#> | F| Forward Diff. | 10.81 | -0.06252 | 2.679 | 1.204 |
-#> |.....................| 0.03262 | -0.1240 | 0.4322 | -0.2470 |
-#> | 107| 288.75294 | 1.013 | -1.132 | -1.081 | 1.252 |
-#> |.....................| -2.997 | -1.011 | -0.7930 | -0.5741 |
-#> | U| 288.75294 | 94.35 | -0.2531 | 2.101 | 2.314 |
-#> |.....................| 5.960e-07 | 0.7060 | 1.235 | 1.501 |
-#> | X| 288.75294 | 94.35 | 0.7764 | 8.173 | 2.314 |
-#> |.....................| 5.960e-07 | 0.7060 | 1.235 | 1.501 |
-#> | F| Forward Diff. | -3.091 | -0.8602 | 1.971 | 1.009 |
-#> |.....................| 0.04475 | 0.5130 | 0.7746 | 0.2303 |
-#> | 108| 288.69834 | 1.013 | -1.093 | -1.104 | 1.232 |
-#> |.....................| -2.997 | -1.011 | -0.7973 | -0.5721 |
-#> | U| 288.69834 | 94.27 | -0.2136 | 2.078 | 2.303 |
-#> |.....................| 5.960e-07 | 0.7061 | 1.231 | 1.503 |
-#> | X| 288.69834 | 94.27 | 0.8077 | 7.987 | 2.303 |
-#> |.....................| 5.960e-07 | 0.7061 | 1.231 | 1.503 |
-#> | F| Forward Diff. | -16.61 | 0.06814 | 0.8311 | 0.6184 |
-#> |.....................| 0.03151 | 0.5612 | 0.4558 | 0.3067 |
-#> | 109| 288.67099 | 1.014 | -1.108 | -1.122 | 1.197 |
-#> |.....................| -2.997 | -1.038 | -0.8030 | -0.5758 |
-#> | U| 288.67099 | 94.36 | -0.2285 | 2.060 | 2.284 |
-#> |.....................| 5.960e-07 | 0.6866 | 1.225 | 1.499 |
-#> | X| 288.67099 | 94.36 | 0.7957 | 7.847 | 2.284 |
-#> |.....................| 5.960e-07 | 0.6866 | 1.225 | 1.499 |
-#> | F| Forward Diff. | -4.975 | -0.2154 | 0.1983 | 0.1047 |
-#> |.....................| 0.03564 | -0.4652 | 0.1266 | 0.2269 |
-#> | 110| 288.66432 | 1.014 | -1.097 | -1.128 | 1.196 |
-#> |.....................| -2.997 | -1.027 | -0.8055 | -0.5813 |
-#> | U| 288.66432 | 94.40 | -0.2184 | 2.053 | 2.283 |
-#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 |
-#> | X| 288.66432 | 94.40 | 0.8038 | 7.793 | 2.283 |
-#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 |
-#> | F| Forward Diff. | 0.3927 | 0.02780 | -0.05986 | 0.04997 |
-#> |.....................| 0.03453 | -0.01180 | -0.03408 | 0.03556 |
-#> | 111| 288.66432 | 1.014 | -1.097 | -1.128 | 1.196 |
-#> |.....................| -2.997 | -1.027 | -0.8055 | -0.5813 |
-#> | U| 288.66432 | 94.40 | -0.2184 | 2.053 | 2.283 |
-#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 |
-#> | X| 288.66432 | 94.40 | 0.8038 | 7.793 | 2.283 |
-#> |.....................| 5.960e-07 | 0.6941 | 1.222 | 1.493 |
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#>
Warning: parameter estimate near boundary; covariance not calculated:
+
f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC",
], est
= "saem",
+ control
= saemControl(print
= 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: parameter estimate near boundary; covariance not calculated:
#> "rsd_high"
#> use 'getVarCov' to calculate anyway
#> Warning: gradient problems with initial estimate; see $scaleInfo
#> [1] 468.0781
#> [1] 535.609
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.546 0.379 5.924
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.549 0.41 5.959
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.842 0.338 7.177
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.93 0.367 7.293
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.14 0.971 16.13
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.39 1.223 16.61
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.271 0.123 1.393
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.288 0.09 1.379
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.699 0.341 7.038
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.384 0.092 1.477
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.666 0.38 7.044
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.39 0.093 1.483
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.86 1.172 16.03
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.67 0.529 15.2
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.461 0.404 8.863
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.455 0.377 8.841
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 18.02 0.925 18.94
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.73 0.679 18.41
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.782 0.02 0.803
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.775 0.024 0.799
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.405 8.575
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.386 8.556
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.824 0.024 0.851
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.799 0.044 0.842
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.44 0.876 18.31
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.5 0.646 18.15
#> Temporary DLL for differentials generated and loaded
#> Temporary DLL for differentials generated and loaded
#> Temporary DLL for differentials generated and loaded
#> Constant variance for more than one variable is not supported for est = 'saem'
+#> Changing the error model to 'obs' (variance by observed variable)
#> function ()
+#> {
+#> ini({
+#> parent_0 = 86.5344031312703
+#> eta.parent_0 ~ 4.15825368312402
+#> log_k_parent = -3.20701116105339
+#> eta.log_k_parent ~ 1.51881531595261
+#> log_k_A1 = -4.56730447776105
+#> eta.log_k_A1 ~ 0.560590264281928
+#> f_parent_qlogis = -0.334081143921924
+#> eta.f_parent_qlogis ~ 1.14983591785967
+#> sigma_parent = 4.31472323222676
+#> sigma_A1 = 4.31472323222676
+#> })
+#> model({
+#> parent_0_model = parent_0 + eta.parent_0
+#> parent(0) = parent_0_model
+#> k_parent = exp(log_k_parent + eta.log_k_parent)
+#> k_A1 = exp(log_k_A1 + eta.log_k_A1)
+#> f_parent_to_A1 = expit(f_parent_qlogis + eta.f_parent_qlogis)
+#> d/dt(parent) = -k_parent * parent
+#> d/dt(A1) = +f_parent_to_A1 * k_parent * parent - k_A1 *
+#> A1
+#> parent ~ add(sigma_parent)
+#> A1 ~ add(sigma_A1)
+#> })
+#> }
+#> <environment: 0x5555669693c0>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[2]+THETA[2];
-#> rx_expr_10~exp(rx_expr_7);
-#> d/dt(parent)=-rx_expr_10*parent;
-#> rx_expr_8~ETA[3]+THETA[3];
-#> rx_expr_11~exp(rx_expr_8);
-#> d/dt(A1)=-rx_expr_11*A1+rx_expr_10*parent*f_parent_to_A1;
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_13~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_13+rx_expr_3;
-#> rx_hi_~rx_expr_13+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_9~parent*(rx_expr_2);
-#> rx_expr_14~rx_expr_9*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_14)*(rx_expr_0)+(rx_expr_4+rx_expr_14)*(rx_expr_2)*(rx_expr_1);
-#> rx_expr_12~Rx_pow_di(THETA[5],2);
-#> rx_r_=(rx_expr_0)*rx_expr_12+(rx_expr_2)*(rx_expr_1)*rx_expr_12;
-#> parent_0=THETA[1];
-#> log_k_parent=THETA[2];
-#> log_k_A1=THETA[3];
-#> f_parent_qlogis=THETA[4];
-#> sigma=THETA[5];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_parent=ETA[2];
-#> eta.log_k_A1=ETA[3];
-#> eta.f_parent_qlogis=ETA[4];
-#> parent_0_model=rx_expr_6;
-#> k_parent=rx_expr_10;
-#> k_A1=rx_expr_11;
-#> f_parent=1/(1+exp(-(ETA[4]+THETA[4])));
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.549 0.41 5.959
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[5]+THETA[5];
-#> rx_expr_13~exp(-(rx_expr_8));
-#> rx_expr_15~t*rx_expr_13;
-#> rx_expr_16~1+rx_expr_15;
-#> rx_expr_18~rx_expr_7-(rx_expr_8);
-#> rx_expr_20~exp(rx_expr_18);
-#> d/dt(parent)=-rx_expr_20*parent/(rx_expr_16);
-#> rx_expr_9~ETA[2]+THETA[2];
-#> rx_expr_11~exp(rx_expr_9);
-#> d/dt(A1)=-rx_expr_11*A1+rx_expr_20*parent*f_parent_to_A1/(rx_expr_16);
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_14~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_14+rx_expr_3;
-#> rx_hi_~rx_expr_14+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_10~parent*(rx_expr_2);
-#> rx_expr_17~rx_expr_10*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_17)*(rx_expr_0)+(rx_expr_4+rx_expr_17)*(rx_expr_2)*(rx_expr_1);
-#> rx_expr_12~Rx_pow_di(THETA[6],2);
-#> rx_r_=(rx_expr_0)*rx_expr_12+(rx_expr_2)*(rx_expr_1)*rx_expr_12;
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_alpha=THETA[4];
-#> log_beta=THETA[5];
-#> sigma=THETA[6];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_alpha=ETA[4];
-#> eta.log_beta=ETA[5];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_11;
-#> alpha=exp(rx_expr_7);
-#> beta=exp(rx_expr_8);
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.93 0.367 7.293
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[6]+THETA[6];
-#> rx_expr_9~ETA[5]+THETA[5];
-#> rx_expr_12~exp(rx_expr_7);
-#> rx_expr_13~exp(rx_expr_9);
-#> rx_expr_15~t*rx_expr_12;
-#> rx_expr_16~t*rx_expr_13;
-#> rx_expr_18~exp(-(rx_expr_8));
-#> rx_expr_20~1+rx_expr_18;
-#> rx_expr_25~1/(rx_expr_20);
-#> rx_expr_27~(rx_expr_25);
-#> rx_expr_28~1-rx_expr_27;
-#> d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_20)+exp(rx_expr_9-rx_expr_16)*(rx_expr_28))/(exp(-t*rx_expr_12)/(rx_expr_20)+exp(-t*rx_expr_13)*(rx_expr_28));
-#> rx_expr_10~ETA[2]+THETA[2];
-#> rx_expr_14~exp(rx_expr_10);
-#> d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_20)+exp(rx_expr_9-rx_expr_16)*(rx_expr_28))/(exp(-t*rx_expr_12)/(rx_expr_20)+exp(-t*rx_expr_13)*(rx_expr_28));
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_19~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_19+rx_expr_3;
-#> rx_hi_~rx_expr_19+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_11~parent*(rx_expr_2);
-#> rx_expr_23~rx_expr_11*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_23)*(rx_expr_0)+(rx_expr_4+rx_expr_23)*(rx_expr_2)*(rx_expr_1);
-#> rx_expr_17~Rx_pow_di(THETA[7],2);
-#> rx_r_=(rx_expr_0)*rx_expr_17+(rx_expr_2)*(rx_expr_1)*rx_expr_17;
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_k1=THETA[4];
-#> log_k2=THETA[5];
-#> g_qlogis=THETA[6];
-#> sigma=THETA[7];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_k1=ETA[4];
-#> eta.log_k2=ETA[5];
-#> eta.g_qlogis=ETA[6];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_14;
-#> k1=rx_expr_12;
-#> k2=rx_expr_13;
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> g=1/(rx_expr_20);
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.39 1.223 16.61
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 |log_k_parent | log_k_A1 |f_parent_qlogis |
+#> |.....................| sigma | o1 | o2 | o3 |
+#> |.....................| o4 |...........|...........|...........|
+#> | 1| 756.06625 | 1.000 | -0.9701 | -1.000 | -0.9071 |
+#> |.....................| -0.8050 | -0.8844 | -0.8800 | -0.8744 |
+#> |.....................| -0.8785 |...........|...........|...........|
+#> | U| 756.06625 | 86.53 | -3.207 | -4.567 | -0.3341 |
+#> |.....................| 4.315 | 0.7003 | 0.9008 | 1.156 |
+#> |.....................| 0.9657 |...........|...........|...........|
+#> | X| 756.06625 | 86.53 | 0.04048 | 0.01039 | 0.4172 |
+#> |.....................| 4.315 | 0.7003 | 0.9008 | 1.156 |
+#> |.....................| 0.9657 |...........|...........|...........|
+#> | G| Gill Diff. | 59.54 | 0.01874 | 0.7243 | 0.3705 |
+#> |.....................| -28.18 | 5.148 | 2.958 | -8.197 |
+#> |.....................| -5.917 |...........|...........|...........|
+#> | 2| 3309.1113 | 0.1102 | -0.9704 | -1.011 | -0.9126 |
+#> |.....................| -0.3838 | -0.9613 | -0.9242 | -0.7519 |
+#> |.....................| -0.7901 |...........|...........|...........|
+#> | U| 3309.1113 | 9.535 | -3.207 | -4.578 | -0.3359 |
+#> |.....................| 5.223 | 0.6464 | 0.8610 | 1.297 |
+#> |.....................| 1.051 |...........|...........|...........|
+#> | X| 3309.1113 | 9.535 | 0.04047 | 0.01027 | 0.4168 |
+#> |.....................| 5.223 | 0.6464 | 0.8610 | 1.297 |
+#> |.....................| 1.051 |...........|...........|...........|
+#> | 3| 782.04188 | 0.9110 | -0.9702 | -1.001 | -0.9076 |
+#> |.....................| -0.7629 | -0.8921 | -0.8844 | -0.8621 |
+#> |.....................| -0.8697 |...........|...........|...........|
+#> | U| 782.04188 | 78.83 | -3.207 | -4.568 | -0.3343 |
+#> |.....................| 4.406 | 0.6949 | 0.8968 | 1.170 |
+#> |.....................| 0.9742 |...........|...........|...........|
+#> | X| 782.04188 | 78.83 | 0.04048 | 0.01037 | 0.4172 |
+#> |.....................| 4.406 | 0.6949 | 0.8968 | 1.170 |
+#> |.....................| 0.9742 |...........|...........|...........|
+#> | 4| 755.73406 | 0.9909 | -0.9701 | -1.000 | -0.9071 |
+#> |.....................| -0.8007 | -0.8851 | -0.8804 | -0.8731 |
+#> |.....................| -0.8776 |...........|...........|...........|
+#> | U| 755.73406 | 85.75 | -3.207 | -4.567 | -0.3341 |
+#> |.....................| 4.324 | 0.6997 | 0.9004 | 1.157 |
+#> |.....................| 0.9666 |...........|...........|...........|
+#> | X| 755.73406 | 85.75 | 0.04048 | 0.01038 | 0.4172 |
+#> |.....................| 4.324 | 0.6997 | 0.9004 | 1.157 |
+#> |.....................| 0.9666 |...........|...........|...........|
+#> | F| Forward Diff. | -16.83 | 0.07808 | 0.6495 | 0.3224 |
+#> |.....................| -27.54 | 3.811 | 2.903 | -8.359 |
+#> |.....................| -5.718 |...........|...........|...........|
+#> | 5| 755.49648 | 0.9959 | -0.9702 | -1.000 | -0.9072 |
+#> |.....................| -0.7924 | -0.8863 | -0.8813 | -0.8706 |
+#> |.....................| -0.8759 |...........|...........|...........|
+#> | U| 755.49648 | 86.18 | -3.207 | -4.568 | -0.3341 |
+#> |.....................| 4.342 | 0.6989 | 0.8996 | 1.160 |
+#> |.....................| 0.9682 |...........|...........|...........|
+#> | X| 755.49648 | 86.18 | 0.04048 | 0.01038 | 0.4172 |
+#> |.....................| 4.342 | 0.6989 | 0.8996 | 1.160 |
+#> |.....................| 0.9682 |...........|...........|...........|
+#> | F| Forward Diff. | 25.35 | 0.04484 | 0.6934 | 0.3535 |
+#> |.....................| -25.80 | 4.244 | 2.831 | -8.249 |
+#> |.....................| -5.719 |...........|...........|...........|
+#> | 6| 755.31010 | 0.9891 | -0.9702 | -1.000 | -0.9073 |
+#> |.....................| -0.7855 | -0.8874 | -0.8820 | -0.8684 |
+#> |.....................| -0.8744 |...........|...........|...........|
+#> | U| 755.3101 | 85.59 | -3.207 | -4.568 | -0.3342 |
+#> |.....................| 4.357 | 0.6981 | 0.8989 | 1.163 |
+#> |.....................| 0.9697 |...........|...........|...........|
+#> | X| 755.3101 | 85.59 | 0.04048 | 0.01038 | 0.4172 |
+#> |.....................| 4.357 | 0.6981 | 0.8989 | 1.163 |
+#> |.....................| 0.9697 |...........|...........|...........|
+#> | F| Forward Diff. | -31.39 | 0.08909 | 0.6380 | 0.3185 |
+#> |.....................| -24.71 | 3.519 | 2.751 | -7.972 |
+#> |.....................| -5.525 |...........|...........|...........|
+#> | 7| 755.09582 | 0.9961 | -0.9702 | -1.001 | -0.9074 |
+#> |.....................| -0.7787 | -0.8884 | -0.8828 | -0.8661 |
+#> |.....................| -0.8728 |...........|...........|...........|
+#> | U| 755.09582 | 86.20 | -3.207 | -4.568 | -0.3342 |
+#> |.....................| 4.372 | 0.6974 | 0.8982 | 1.165 |
+#> |.....................| 0.9712 |...........|...........|...........|
+#> | X| 755.09582 | 86.20 | 0.04047 | 0.01038 | 0.4172 |
+#> |.....................| 4.372 | 0.6974 | 0.8982 | 1.165 |
+#> |.....................| 0.9712 |...........|...........|...........|
+#> | F| Forward Diff. | 26.63 | 0.04269 | 0.6973 | 0.3604 |
+#> |.....................| -23.22 | 4.086 | 2.689 | -8.043 |
+#> |.....................| -5.569 |...........|...........|...........|
+#> | 8| 754.90743 | 0.9894 | -0.9702 | -1.001 | -0.9075 |
+#> |.....................| -0.7716 | -0.8897 | -0.8836 | -0.8636 |
+#> |.....................| -0.8711 |...........|...........|...........|
+#> | U| 754.90743 | 85.62 | -3.207 | -4.568 | -0.3342 |
+#> |.....................| 4.387 | 0.6966 | 0.8975 | 1.168 |
+#> |.....................| 0.9729 |...........|...........|...........|
+#> | X| 754.90743 | 85.62 | 0.04047 | 0.01038 | 0.4172 |
+#> |.....................| 4.387 | 0.6966 | 0.8975 | 1.168 |
+#> |.....................| 0.9729 |...........|...........|...........|
+#> | F| Forward Diff. | -27.88 | 0.08581 | 0.6437 | 0.3265 |
+#> |.....................| -22.15 | 3.354 | 2.606 | -7.748 |
+#> |.....................| -5.369 |...........|...........|...........|
+#> | 9| 754.70769 | 0.9959 | -0.9702 | -1.001 | -0.9076 |
+#> |.....................| -0.7645 | -0.8908 | -0.8845 | -0.8610 |
+#> |.....................| -0.8693 |...........|...........|...........|
+#> | U| 754.70769 | 86.18 | -3.207 | -4.568 | -0.3343 |
+#> |.....................| 4.402 | 0.6958 | 0.8967 | 1.171 |
+#> |.....................| 0.9747 |...........|...........|...........|
+#> | X| 754.70769 | 86.18 | 0.04047 | 0.01037 | 0.4172 |
+#> |.....................| 4.402 | 0.6958 | 0.8967 | 1.171 |
+#> |.....................| 0.9747 |...........|...........|...........|
+#> | F| Forward Diff. | 25.01 | 0.04305 | 0.6984 | 0.3661 |
+#> |.....................| -20.67 | 3.871 | 2.535 | -7.809 |
+#> |.....................| -5.388 |...........|...........|...........|
+#> | 10| 754.52507 | 0.9898 | -0.9703 | -1.001 | -0.9078 |
+#> |.....................| -0.7574 | -0.8922 | -0.8854 | -0.8580 |
+#> |.....................| -0.8672 |...........|...........|...........|
+#> | U| 754.52507 | 85.65 | -3.207 | -4.569 | -0.3343 |
+#> |.....................| 4.417 | 0.6948 | 0.8958 | 1.175 |
+#> |.....................| 0.9766 |...........|...........|...........|
+#> | X| 754.52507 | 85.65 | 0.04047 | 0.01037 | 0.4172 |
+#> |.....................| 4.417 | 0.6948 | 0.8958 | 1.175 |
+#> |.....................| 0.9766 |...........|...........|...........|
+#> | F| Forward Diff. | -24.90 | 0.08308 | 0.6490 | 0.3352 |
+#> |.....................| -19.59 | 3.181 | 2.445 | -7.663 |
+#> |.....................| -5.179 |...........|...........|...........|
+#> | 11| 754.34076 | 0.9957 | -0.9703 | -1.002 | -0.9079 |
+#> |.....................| -0.7502 | -0.8935 | -0.8864 | -0.8548 |
+#> |.....................| -0.8650 |...........|...........|...........|
+#> | U| 754.34076 | 86.16 | -3.207 | -4.569 | -0.3344 |
+#> |.....................| 4.433 | 0.6939 | 0.8950 | 1.178 |
+#> |.....................| 0.9787 |...........|...........|...........|
+#> | X| 754.34076 | 86.16 | 0.04047 | 0.01037 | 0.4172 |
+#> |.....................| 4.433 | 0.6939 | 0.8950 | 1.178 |
+#> |.....................| 0.9787 |...........|...........|...........|
+#> | F| Forward Diff. | 23.15 | 0.04366 | 0.6990 | 0.3728 |
+#> |.....................| -18.16 | 3.647 | 2.362 | -7.534 |
+#> |.....................| -5.170 |...........|...........|...........|
+#> | 12| 754.16941 | 0.9900 | -0.9703 | -1.002 | -0.9081 |
+#> |.....................| -0.7432 | -0.8951 | -0.8875 | -0.8512 |
+#> |.....................| -0.8626 |...........|...........|...........|
+#> | U| 754.16941 | 85.67 | -3.207 | -4.569 | -0.3344 |
+#> |.....................| 4.448 | 0.6928 | 0.8940 | 1.182 |
+#> |.....................| 0.9811 |...........|...........|...........|
+#> | X| 754.16941 | 85.67 | 0.04047 | 0.01036 | 0.4172 |
+#> |.....................| 4.448 | 0.6928 | 0.8940 | 1.182 |
+#> |.....................| 0.9811 |...........|...........|...........|
+#> | F| Forward Diff. | -22.36 | 0.07996 | 0.6524 | 0.3446 |
+#> |.....................| -17.12 | 3.002 | 2.262 | -7.362 |
+#> |.....................| -4.949 |...........|...........|...........|
+#> | 13| 754.00081 | 0.9955 | -0.9704 | -1.002 | -0.9083 |
+#> |.....................| -0.7363 | -0.8967 | -0.8886 | -0.8472 |
+#> |.....................| -0.8599 |...........|...........|...........|
+#> | U| 754.00081 | 86.14 | -3.207 | -4.570 | -0.3345 |
+#> |.....................| 4.463 | 0.6916 | 0.8930 | 1.187 |
+#> |.....................| 0.9836 |...........|...........|...........|
+#> | X| 754.00081 | 86.14 | 0.04047 | 0.01036 | 0.4171 |
+#> |.....................| 4.463 | 0.6916 | 0.8930 | 1.187 |
+#> |.....................| 0.9836 |...........|...........|...........|
+#> | F| Forward Diff. | 21.00 | 0.04440 | 0.6979 | 0.3804 |
+#> |.....................| -15.79 | 3.414 | 2.168 | -7.205 |
+#> |.....................| -4.903 |...........|...........|...........|
+#> | 14| 753.84435 | 0.9903 | -0.9704 | -1.003 | -0.9086 |
+#> |.....................| -0.7296 | -0.8985 | -0.8898 | -0.8427 |
+#> |.....................| -0.8570 |...........|...........|...........|
+#> | U| 753.84435 | 85.70 | -3.207 | -4.570 | -0.3346 |
+#> |.....................| 4.477 | 0.6903 | 0.8919 | 1.192 |
+#> |.....................| 0.9865 |...........|...........|...........|
+#> | X| 753.84435 | 85.70 | 0.04047 | 0.01036 | 0.4171 |
+#> |.....................| 4.477 | 0.6903 | 0.8919 | 1.192 |
+#> |.....................| 0.9865 |...........|...........|...........|
+#> | F| Forward Diff. | -19.93 | 0.07681 | 0.6538 | 0.3555 |
+#> |.....................| -14.84 | 2.820 | 2.056 | -6.999 |
+#> |.....................| -4.662 |...........|...........|...........|
+#> | 15| 753.69372 | 0.9952 | -0.9704 | -1.003 | -0.9089 |
+#> |.....................| -0.7234 | -0.9005 | -0.8911 | -0.8377 |
+#> |.....................| -0.8537 |...........|...........|...........|
+#> | U| 753.69372 | 86.12 | -3.207 | -4.571 | -0.3347 |
+#> |.....................| 4.491 | 0.6890 | 0.8908 | 1.198 |
+#> |.....................| 0.9897 |...........|...........|...........|
+#> | X| 753.69372 | 86.12 | 0.04046 | 0.01035 | 0.4171 |
+#> |.....................| 4.491 | 0.6890 | 0.8908 | 1.198 |
+#> |.....................| 0.9897 |...........|...........|...........|
+#> | F| Forward Diff. | 18.81 | 0.04462 | 0.6942 | 0.3896 |
+#> |.....................| -13.66 | 3.180 | 1.953 | -6.807 |
+#> |.....................| -4.573 |...........|...........|...........|
+#> | 16| 753.55534 | 0.9906 | -0.9705 | -1.004 | -0.9093 |
+#> |.....................| -0.7176 | -0.9027 | -0.8924 | -0.8322 |
+#> |.....................| -0.8502 |...........|...........|...........|
+#> | U| 753.55534 | 85.72 | -3.207 | -4.571 | -0.3348 |
+#> |.....................| 4.503 | 0.6875 | 0.8896 | 1.204 |
+#> |.....................| 0.9931 |...........|...........|...........|
+#> | X| 753.55534 | 85.72 | 0.04046 | 0.01034 | 0.4171 |
+#> |.....................| 4.503 | 0.6875 | 0.8896 | 1.204 |
+#> |.....................| 0.9931 |...........|...........|...........|
+#> | F| Forward Diff. | -17.61 | 0.07313 | 0.6517 | 0.3679 |
+#> |.....................| -12.86 | 2.639 | 1.835 | -6.564 |
+#> |.....................| -4.309 |...........|...........|...........|
+#> | 17| 753.42478 | 0.9950 | -0.9706 | -1.005 | -0.9097 |
+#> |.....................| -0.7124 | -0.9049 | -0.8937 | -0.8262 |
+#> |.....................| -0.8464 |...........|...........|...........|
+#> | U| 753.42478 | 86.11 | -3.207 | -4.572 | -0.3350 |
+#> |.....................| 4.515 | 0.6859 | 0.8884 | 1.211 |
+#> |.....................| 0.9967 |...........|...........|...........|
+#> | X| 753.42478 | 86.11 | 0.04046 | 0.01034 | 0.4170 |
+#> |.....................| 4.515 | 0.6859 | 0.8884 | 1.211 |
+#> |.....................| 0.9967 |...........|...........|...........|
+#> | F| Forward Diff. | 16.74 | 0.04433 | 0.6853 | 0.4002 |
+#> |.....................| -11.89 | 2.952 | 1.729 | -6.336 |
+#> |.....................| -4.181 |...........|...........|...........|
+#> | 18| 753.30602 | 0.9909 | -0.9706 | -1.006 | -0.9103 |
+#> |.....................| -0.7078 | -0.9075 | -0.8949 | -0.8197 |
+#> |.....................| -0.8425 |...........|...........|...........|
+#> | U| 753.30602 | 85.74 | -3.207 | -4.573 | -0.3352 |
+#> |.....................| 4.525 | 0.6841 | 0.8873 | 1.219 |
+#> |.....................| 1.001 |...........|...........|...........|
+#> | X| 753.30602 | 85.74 | 0.04046 | 0.01033 | 0.4170 |
+#> |.....................| 4.525 | 0.6841 | 0.8873 | 1.219 |
+#> |.....................| 1.001 |...........|...........|...........|
+#> | F| Forward Diff. | -15.54 | 0.06924 | 0.6430 | 0.3812 |
+#> |.....................| -11.26 | 2.462 | 1.618 | -6.066 |
+#> |.....................| -3.903 |...........|...........|...........|
+#> | 19| 753.19508 | 0.9949 | -0.9707 | -1.007 | -0.9109 |
+#> |.....................| -0.7036 | -0.9102 | -0.8961 | -0.8129 |
+#> |.....................| -0.8385 |...........|...........|...........|
+#> | U| 753.19508 | 86.09 | -3.208 | -4.574 | -0.3354 |
+#> |.....................| 4.533 | 0.6822 | 0.8862 | 1.227 |
+#> |.....................| 1.004 |...........|...........|...........|
+#> | X| 753.19508 | 86.09 | 0.04045 | 0.01032 | 0.4169 |
+#> |.....................| 4.533 | 0.6822 | 0.8862 | 1.227 |
+#> |.....................| 1.004 |...........|...........|...........|
+#> | F| Forward Diff. | 14.90 | 0.04352 | 0.6689 | 0.4113 |
+#> |.....................| -10.49 | 2.732 | 1.522 | -5.813 |
+#> |.....................| -3.751 |...........|...........|...........|
+#> | 20| 753.09443 | 0.9911 | -0.9708 | -1.008 | -0.9117 |
+#> |.....................| -0.7001 | -0.9132 | -0.8972 | -0.8058 |
+#> |.....................| -0.8346 |...........|...........|...........|
+#> | U| 753.09443 | 85.77 | -3.208 | -4.575 | -0.3356 |
+#> |.....................| 4.541 | 0.6801 | 0.8852 | 1.235 |
+#> |.....................| 1.008 |...........|...........|...........|
+#> | X| 753.09443 | 85.77 | 0.04045 | 0.01031 | 0.4169 |
+#> |.....................| 4.541 | 0.6801 | 0.8852 | 1.235 |
+#> |.....................| 1.008 |...........|...........|...........|
+#> | F| Forward Diff. | -13.80 | 0.06521 | 0.6240 | 0.3942 |
+#> |.....................| -10.02 | 2.285 | 1.423 | -5.526 |
+#> |.....................| -3.476 |...........|...........|...........|
+#> | 21| 753.00021 | 0.9948 | -0.9709 | -1.009 | -0.9127 |
+#> |.....................| -0.6968 | -0.9163 | -0.8982 | -0.7985 |
+#> |.....................| -0.8307 |...........|...........|...........|
+#> | U| 753.00021 | 86.08 | -3.208 | -4.576 | -0.3360 |
+#> |.....................| 4.548 | 0.6779 | 0.8843 | 1.243 |
+#> |.....................| 1.012 |...........|...........|...........|
+#> | X| 753.00021 | 86.08 | 0.04045 | 0.01029 | 0.4168 |
+#> |.....................| 4.548 | 0.6779 | 0.8843 | 1.243 |
+#> |.....................| 1.012 |...........|...........|...........|
+#> | F| Forward Diff. | 13.31 | 0.04216 | 0.6406 | 0.4217 |
+#> |.....................| -9.402 | 2.517 | 1.347 | -5.262 |
+#> |.....................| -3.321 |...........|...........|...........|
+#> | 22| 752.91432 | 0.9914 | -0.9710 | -1.010 | -0.9139 |
+#> |.....................| -0.6939 | -0.9197 | -0.8991 | -0.7911 |
+#> |.....................| -0.8272 |...........|...........|...........|
+#> | U| 752.91432 | 85.79 | -3.208 | -4.578 | -0.3364 |
+#> |.....................| 4.555 | 0.6755 | 0.8835 | 1.252 |
+#> |.....................| 1.015 |...........|...........|...........|
+#> | X| 752.91432 | 85.79 | 0.04044 | 0.01028 | 0.4167 |
+#> |.....................| 4.555 | 0.6755 | 0.8835 | 1.252 |
+#> |.....................| 1.015 |...........|...........|...........|
+#> | F| Forward Diff. | -12.35 | 0.06128 | 0.5909 | 0.4053 |
+#> |.....................| -9.027 | 2.101 | 1.271 | -4.717 |
+#> |.....................| -3.067 |...........|...........|...........|
+#> | 23| 752.83200 | 0.9948 | -0.9711 | -1.012 | -0.9155 |
+#> |.....................| -0.6906 | -0.9238 | -0.9000 | -0.7843 |
+#> |.....................| -0.8235 |...........|...........|...........|
+#> | U| 752.832 | 86.09 | -3.208 | -4.580 | -0.3369 |
+#> |.....................| 4.561 | 0.6727 | 0.8827 | 1.260 |
+#> |.....................| 1.019 |...........|...........|...........|
+#> | X| 752.832 | 86.09 | 0.04044 | 0.01026 | 0.4166 |
+#> |.....................| 4.561 | 0.6727 | 0.8827 | 1.260 |
+#> |.....................| 1.019 |...........|...........|...........|
+#> | F| Forward Diff. | 12.74 | 0.03978 | 0.5956 | 0.4312 |
+#> |.....................| -8.422 | 2.296 | 1.202 | -4.471 |
+#> |.....................| -2.914 |...........|...........|...........|
+#> | 24| 752.75140 | 0.9918 | -0.9713 | -1.014 | -0.9179 |
+#> |.....................| -0.6872 | -0.9288 | -0.9011 | -0.7785 |
+#> |.....................| -0.8198 |...........|...........|...........|
+#> | U| 752.7514 | 85.82 | -3.208 | -4.582 | -0.3377 |
+#> |.....................| 4.569 | 0.6692 | 0.8818 | 1.266 |
+#> |.....................| 1.022 |...........|...........|...........|
+#> | X| 752.7514 | 85.82 | 0.04043 | 0.01024 | 0.4164 |
+#> |.....................| 4.569 | 0.6692 | 0.8818 | 1.266 |
+#> |.....................| 1.022 |...........|...........|...........|
+#> | F| Forward Diff. | -10.02 | 0.05546 | 0.5361 | 0.4172 |
+#> |.....................| -7.958 | 1.872 | 1.117 | -4.424 |
+#> |.....................| -2.664 |...........|...........|...........|
+#> | 25| 752.68235 | 0.9947 | -0.9715 | -1.016 | -0.9205 |
+#> |.....................| -0.6845 | -0.9329 | -0.9018 | -0.7712 |
+#> |.....................| -0.8173 |...........|...........|...........|
+#> | U| 752.68235 | 86.07 | -3.208 | -4.584 | -0.3386 |
+#> |.....................| 4.575 | 0.6663 | 0.8811 | 1.275 |
+#> |.....................| 1.025 |...........|...........|...........|
+#> | X| 752.68235 | 86.07 | 0.04042 | 0.01022 | 0.4162 |
+#> |.....................| 4.575 | 0.6663 | 0.8811 | 1.275 |
+#> |.....................| 1.025 |...........|...........|...........|
+#> | F| Forward Diff. | 10.53 | 0.03715 | 0.5273 | 0.4360 |
+#> |.....................| -7.447 | 2.014 | 1.063 | -3.990 |
+#> |.....................| -2.556 |...........|...........|...........|
+#> | 26| 752.62160 | 0.9918 | -0.9717 | -1.019 | -0.9237 |
+#> |.....................| -0.6821 | -0.9370 | -0.9025 | -0.7637 |
+#> |.....................| -0.8151 |...........|...........|...........|
+#> | U| 752.6216 | 85.83 | -3.209 | -4.586 | -0.3397 |
+#> |.....................| 4.580 | 0.6635 | 0.8804 | 1.284 |
+#> |.....................| 1.027 |...........|...........|...........|
+#> | X| 752.6216 | 85.83 | 0.04042 | 0.01020 | 0.4159 |
+#> |.....................| 4.580 | 0.6635 | 0.8804 | 1.284 |
+#> |.....................| 1.027 |...........|...........|...........|
+#> | F| Forward Diff. | -10.27 | 0.05173 | 0.4657 | 0.4178 |
+#> |.....................| -7.153 | 1.648 | 1.004 | -3.701 |
+#> |.....................| -2.385 |...........|...........|...........|
+#> | 27| 752.55758 | 0.9944 | -0.9719 | -1.021 | -0.9287 |
+#> |.....................| -0.6786 | -0.9418 | -0.9036 | -0.7591 |
+#> |.....................| -0.8121 |...........|...........|...........|
+#> | U| 752.55758 | 86.05 | -3.209 | -4.588 | -0.3413 |
+#> |.....................| 4.587 | 0.6600 | 0.8795 | 1.289 |
+#> |.....................| 1.030 |...........|...........|...........|
+#> | X| 752.55758 | 86.05 | 0.04040 | 0.01017 | 0.4155 |
+#> |.....................| 4.587 | 0.6600 | 0.8795 | 1.289 |
+#> |.....................| 1.030 |...........|...........|...........|
+#> | F| Forward Diff. | 7.976 | 0.03464 | 0.4539 | 0.4351 |
+#> |.....................| -6.545 | 1.728 | 0.9236 | -3.536 |
+#> |.....................| -2.257 |...........|...........|...........|
+#> | 28| 752.50465 | 0.9921 | -0.9722 | -1.023 | -0.9345 |
+#> |.....................| -0.6755 | -0.9456 | -0.9043 | -0.7539 |
+#> |.....................| -0.8090 |...........|...........|...........|
+#> | U| 752.50465 | 85.85 | -3.209 | -4.590 | -0.3432 |
+#> |.....................| 4.594 | 0.6574 | 0.8788 | 1.295 |
+#> |.....................| 1.033 |...........|...........|...........|
+#> | X| 752.50465 | 85.85 | 0.04039 | 0.01015 | 0.4150 |
+#> |.....................| 4.594 | 0.6574 | 0.8788 | 1.295 |
+#> |.....................| 1.033 |...........|...........|...........|
+#> | F| Forward Diff. | -8.947 | 0.04577 | 0.4043 | 0.4205 |
+#> |.....................| -6.122 | 1.399 | 0.8644 | -3.339 |
+#> |.....................| -2.062 |...........|...........|...........|
+#> | 29| 752.46010 | 0.9944 | -0.9724 | -1.024 | -0.9405 |
+#> |.....................| -0.6742 | -0.9477 | -0.9048 | -0.7467 |
+#> |.....................| -0.8068 |...........|...........|...........|
+#> | U| 752.4601 | 86.05 | -3.209 | -4.591 | -0.3452 |
+#> |.....................| 4.597 | 0.6559 | 0.8784 | 1.303 |
+#> |.....................| 1.035 |...........|...........|...........|
+#> | X| 752.4601 | 86.05 | 0.04039 | 0.01014 | 0.4145 |
+#> |.....................| 4.597 | 0.6559 | 0.8784 | 1.303 |
+#> |.....................| 1.035 |...........|...........|...........|
+#> | F| Forward Diff. | 6.603 | 0.03134 | 0.3976 | 0.4307 |
+#> |.....................| -5.878 | 1.523 | 0.8347 | -3.098 |
+#> |.....................| -1.971 |...........|...........|...........|
+#> | 30| 752.42045 | 0.9923 | -0.9726 | -1.025 | -0.9478 |
+#> |.....................| -0.6717 | -0.9497 | -0.9056 | -0.7410 |
+#> |.....................| -0.8056 |...........|...........|...........|
+#> | U| 752.42045 | 85.87 | -3.210 | -4.593 | -0.3477 |
+#> |.....................| 4.602 | 0.6545 | 0.8777 | 1.310 |
+#> |.....................| 1.036 |...........|...........|...........|
+#> | X| 752.42045 | 85.87 | 0.04038 | 0.01013 | 0.4139 |
+#> |.....................| 4.602 | 0.6545 | 0.8777 | 1.310 |
+#> |.....................| 1.036 |...........|...........|...........|
+#> | F| Forward Diff. | -7.567 | 0.04074 | 0.3551 | 0.4112 |
+#> |.....................| -5.553 | 1.278 | 0.7625 | -2.890 |
+#> |.....................| -1.881 |...........|...........|...........|
+#> | 31| 752.38271 | 0.9943 | -0.9729 | -1.026 | -0.9563 |
+#> |.....................| -0.6682 | -0.9523 | -0.9058 | -0.7392 |
+#> |.....................| -0.8032 |...........|...........|...........|
+#> | U| 752.38271 | 86.04 | -3.210 | -4.594 | -0.3505 |
+#> |.....................| 4.610 | 0.6527 | 0.8775 | 1.312 |
+#> |.....................| 1.038 |...........|...........|...........|
+#> | X| 752.38271 | 86.04 | 0.04037 | 0.01012 | 0.4133 |
+#> |.....................| 4.610 | 0.6527 | 0.8775 | 1.312 |
+#> |.....................| 1.038 |...........|...........|...........|
+#> | F| Forward Diff. | 5.602 | 0.02847 | 0.3641 | 0.4189 |
+#> |.....................| -5.001 | 1.344 | 0.7516 | -2.828 |
+#> |.....................| -1.805 |...........|...........|...........|
+#> | 32| 752.35435 | 0.9925 | -0.9730 | -1.028 | -0.9633 |
+#> |.....................| -0.6679 | -0.9545 | -0.9069 | -0.7341 |
+#> |.....................| -0.7988 |...........|...........|...........|
+#> | U| 752.35435 | 85.89 | -3.210 | -4.595 | -0.3529 |
+#> |.....................| 4.611 | 0.6511 | 0.8766 | 1.318 |
+#> |.....................| 1.043 |...........|...........|...........|
+#> | X| 752.35435 | 85.89 | 0.04036 | 0.01010 | 0.4127 |
+#> |.....................| 4.611 | 0.6511 | 0.8766 | 1.318 |
+#> |.....................| 1.043 |...........|...........|...........|
+#> | F| Forward Diff. | -6.571 | 0.03612 | 0.3357 | 0.4086 |
+#> |.....................| -4.992 | 1.118 | 0.6605 | -2.632 |
+#> |.....................| -1.560 |...........|...........|...........|
+#> | 33| 752.32772 | 0.9943 | -0.9732 | -1.029 | -0.9711 |
+#> |.....................| -0.6669 | -0.9557 | -0.9071 | -0.7282 |
+#> |.....................| -0.7989 |...........|...........|...........|
+#> | U| 752.32772 | 86.04 | -3.210 | -4.596 | -0.3555 |
+#> |.....................| 4.613 | 0.6503 | 0.8764 | 1.325 |
+#> |.....................| 1.043 |...........|...........|...........|
+#> | X| 752.32772 | 86.04 | 0.04035 | 0.01009 | 0.4121 |
+#> |.....................| 4.613 | 0.6503 | 0.8764 | 1.325 |
+#> |.....................| 1.043 |...........|...........|...........|
+#> | F| Forward Diff. | 5.212 | 0.02538 | 0.3153 | 0.4089 |
+#> |.....................| -4.808 | 1.231 | 0.6502 | -2.445 |
+#> |.....................| -1.583 |...........|...........|...........|
+#> | 34| 752.30453 | 0.9927 | -0.9733 | -1.030 | -0.9795 |
+#> |.....................| -0.6622 | -0.9567 | -0.9058 | -0.7271 |
+#> |.....................| -0.8012 |...........|...........|...........|
+#> | U| 752.30453 | 85.90 | -3.210 | -4.598 | -0.3583 |
+#> |.....................| 4.623 | 0.6496 | 0.8775 | 1.326 |
+#> |.....................| 1.040 |...........|...........|...........|
+#> | X| 752.30453 | 85.90 | 0.04035 | 0.01008 | 0.4114 |
+#> |.....................| 4.623 | 0.6496 | 0.8775 | 1.326 |
+#> |.....................| 1.040 |...........|...........|...........|
+#> | F| Forward Diff. | -5.777 | 0.03360 | 0.2795 | 0.3849 |
+#> |.....................| -4.177 | 1.041 | 0.7583 | -2.411 |
+#> |.....................| -1.694 |...........|...........|...........|
+#> | 35| 752.28211 | 0.9943 | -0.9735 | -1.030 | -0.9865 |
+#> |.....................| -0.6621 | -0.9586 | -0.9093 | -0.7251 |
+#> |.....................| -0.7954 |...........|...........|...........|
+#> | U| 752.28211 | 86.04 | -3.210 | -4.598 | -0.3606 |
+#> |.....................| 4.623 | 0.6483 | 0.8743 | 1.328 |
+#> |.....................| 1.046 |...........|...........|...........|
+#> | X| 752.28211 | 86.04 | 0.04034 | 0.01008 | 0.4108 |
+#> |.....................| 4.623 | 0.6483 | 0.8743 | 1.328 |
+#> |.....................| 1.046 |...........|...........|...........|
+#> | F| Forward Diff. | 4.685 | 0.02318 | 0.3105 | 0.3984 |
+#> |.....................| -4.118 | 1.106 | 0.4577 | -2.335 |
+#> |.....................| -1.438 |...........|...........|...........|
+#> | 36| 752.26507 | 0.9926 | -0.9736 | -1.031 | -0.9930 |
+#> |.....................| -0.6630 | -0.9604 | -0.9091 | -0.7199 |
+#> |.....................| -0.7902 |...........|...........|...........|
+#> | U| 752.26507 | 85.89 | -3.210 | -4.598 | -0.3628 |
+#> |.....................| 4.621 | 0.6470 | 0.8745 | 1.334 |
+#> |.....................| 1.051 |...........|...........|...........|
+#> | X| 752.26507 | 85.89 | 0.04034 | 0.01007 | 0.4103 |
+#> |.....................| 4.621 | 0.6470 | 0.8745 | 1.334 |
+#> |.....................| 1.051 |...........|...........|...........|
+#> | F| Forward Diff. | -6.810 | 0.03096 | 0.2910 | 0.3899 |
+#> |.....................| -4.283 | 0.8991 | 0.4756 | -2.130 |
+#> |.....................| -1.153 |...........|...........|...........|
+#> | 37| 752.24597 | 0.9942 | -0.9737 | -1.033 | -1.000 |
+#> |.....................| -0.6608 | -0.9614 | -0.9045 | -0.7160 |
+#> |.....................| -0.7919 |...........|...........|...........|
+#> | U| 752.24597 | 86.03 | -3.211 | -4.600 | -0.3653 |
+#> |.....................| 4.626 | 0.6463 | 0.8787 | 1.339 |
+#> |.....................| 1.049 |...........|...........|...........|
+#> | X| 752.24597 | 86.03 | 0.04033 | 0.01005 | 0.4097 |
+#> |.....................| 4.626 | 0.6463 | 0.8787 | 1.339 |
+#> |.....................| 1.049 |...........|...........|...........|
+#> | F| Forward Diff. | 3.512 | 0.02244 | 0.2659 | 0.3868 |
+#> |.....................| -3.943 | 0.9821 | 0.8784 | -2.032 |
+#> |.....................| -1.263 |...........|...........|...........|
+#> | 38| 752.22949 | 0.9926 | -0.9738 | -1.034 | -1.007 |
+#> |.....................| -0.6572 | -0.9618 | -0.9098 | -0.7144 |
+#> |.....................| -0.7948 |...........|...........|...........|
+#> | U| 752.22949 | 85.90 | -3.211 | -4.601 | -0.3676 |
+#> |.....................| 4.634 | 0.6461 | 0.8739 | 1.341 |
+#> |.....................| 1.047 |...........|...........|...........|
+#> | X| 752.22949 | 85.90 | 0.04033 | 0.01004 | 0.4091 |
+#> |.....................| 4.634 | 0.6461 | 0.8739 | 1.341 |
+#> |.....................| 1.047 |...........|...........|...........|
+#> | F| Forward Diff. | -6.652 | 0.02915 | 0.2261 | 0.3631 |
+#> |.....................| -3.474 | 0.8493 | 0.4224 | -1.980 |
+#> |.....................| -1.394 |...........|...........|...........|
+#> | 39| 752.21433 | 0.9945 | -0.9739 | -1.034 | -1.016 |
+#> |.....................| -0.6569 | -0.9629 | -0.9144 | -0.7124 |
+#> |.....................| -0.7922 |...........|...........|...........|
+#> | U| 752.21433 | 86.05 | -3.211 | -4.601 | -0.3704 |
+#> |.....................| 4.634 | 0.6453 | 0.8697 | 1.343 |
+#> |.....................| 1.049 |...........|...........|...........|
+#> | X| 752.21433 | 86.05 | 0.04032 | 0.01004 | 0.4085 |
+#> |.....................| 4.634 | 0.6453 | 0.8697 | 1.343 |
+#> |.....................| 1.049 |...........|...........|...........|
+#> | F| Forward Diff. | 5.271 | 0.01812 | 0.2470 | 0.3694 |
+#> |.....................| -3.388 | 0.9655 | 0.02976 | -1.920 |
+#> |.....................| -1.299 |...........|...........|...........|
+#> | 40| 752.19821 | 0.9933 | -0.9740 | -1.034 | -1.022 |
+#> |.....................| -0.6566 | -0.9648 | -0.9096 | -0.7099 |
+#> |.....................| -0.7872 |...........|...........|...........|
+#> | U| 752.19821 | 85.95 | -3.211 | -4.602 | -0.3726 |
+#> |.....................| 4.635 | 0.6440 | 0.8741 | 1.346 |
+#> |.....................| 1.054 |...........|...........|...........|
+#> | X| 752.19821 | 85.95 | 0.04032 | 0.01004 | 0.4079 |
+#> |.....................| 4.635 | 0.6440 | 0.8741 | 1.346 |
+#> |.....................| 1.054 |...........|...........|...........|
+#> | F| Forward Diff. | -2.667 | 0.02369 | 0.2481 | 0.3640 |
+#> |.....................| -3.371 | 0.7751 | 0.4401 | -1.801 |
+#> |.....................| -1.045 |...........|...........|...........|
+#> | 41| 752.18532 | 0.9951 | -0.9741 | -1.036 | -1.031 |
+#> |.....................| -0.6545 | -0.9659 | -0.9070 | -0.7062 |
+#> |.....................| -0.7858 |...........|...........|...........|
+#> | U| 752.18532 | 86.11 | -3.211 | -4.603 | -0.3754 |
+#> |.....................| 4.639 | 0.6432 | 0.8764 | 1.350 |
+#> |.....................| 1.055 |...........|...........|...........|
+#> | X| 752.18532 | 86.11 | 0.04032 | 0.01002 | 0.4072 |
+#> |.....................| 4.639 | 0.6432 | 0.8764 | 1.350 |
+#> |.....................| 1.055 |...........|...........|...........|
+#> | F| Forward Diff. | 8.833 | 0.01368 | 0.2421 | 0.3674 |
+#> |.....................| -3.039 | 0.8770 | 0.6679 | -1.687 |
+#> |.....................| -1.010 |...........|...........|...........|
+#> | 42| 752.16831 | 0.9936 | -0.9742 | -1.037 | -1.039 |
+#> |.....................| -0.6539 | -0.9664 | -0.9110 | -0.7027 |
+#> |.....................| -0.7873 |...........|...........|...........|
+#> | U| 752.16831 | 85.98 | -3.211 | -4.605 | -0.3782 |
+#> |.....................| 4.641 | 0.6428 | 0.8728 | 1.354 |
+#> |.....................| 1.054 |...........|...........|...........|
+#> | X| 752.16831 | 85.98 | 0.04031 | 0.01001 | 0.4066 |
+#> |.....................| 4.641 | 0.6428 | 0.8728 | 1.354 |
+#> |.....................| 1.054 |...........|...........|...........|
+#> | F| Forward Diff. | -0.7512 | 0.02003 | 0.1902 | 0.3449 |
+#> |.....................| -2.985 | 0.7407 | 0.3269 | -1.581 |
+#> |.....................| -1.064 |...........|...........|...........|
+#> | 43| 752.14828 | 0.9957 | -0.9743 | -1.038 | -1.040 |
+#> |.....................| -0.6457 | -0.9684 | -0.9119 | -0.6984 |
+#> |.....................| -0.7843 |...........|...........|...........|
+#> | U| 752.14828 | 86.16 | -3.211 | -4.605 | -0.3785 |
+#> |.....................| 4.658 | 0.6414 | 0.8720 | 1.359 |
+#> |.....................| 1.057 |...........|...........|...........|
+#> | X| 752.14828 | 86.16 | 0.04031 | 0.01000 | 0.4065 |
+#> |.....................| 4.658 | 0.6414 | 0.8720 | 1.359 |
+#> |.....................| 1.057 |...........|...........|...........|
+#> | F| Forward Diff. | 12.68 | 0.008742 | 0.2033 | 0.3626 |
+#> |.....................| -1.835 | 0.8163 | 0.2532 | -1.452 |
+#> |.....................| -0.9466 |...........|...........|...........|
+#> | 44| 752.12689 | 0.9938 | -0.9744 | -1.038 | -1.049 |
+#> |.....................| -0.6468 | -0.9706 | -0.9116 | -0.6946 |
+#> |.....................| -0.7819 |...........|...........|...........|
+#> | U| 752.12689 | 86.00 | -3.211 | -4.606 | -0.3814 |
+#> |.....................| 4.656 | 0.6399 | 0.8723 | 1.363 |
+#> |.....................| 1.059 |...........|...........|...........|
+#> | X| 752.12689 | 86.00 | 0.04030 | 0.009996 | 0.4058 |
+#> |.....................| 4.656 | 0.6399 | 0.8723 | 1.363 |
+#> |.....................| 1.059 |...........|...........|...........|
+#> | F| Forward Diff. | -0.08747 | 0.01751 | 0.1808 | 0.3434 |
+#> |.....................| -2.013 | 0.5634 | 0.2760 | -1.320 |
+#> |.....................| -0.7971 |...........|...........|...........|
+#> | 45| 752.10460 | 0.9941 | -0.9745 | -1.039 | -1.050 |
+#> |.....................| -0.6390 | -0.9728 | -0.9127 | -0.6895 |
+#> |.....................| -0.7788 |...........|...........|...........|
+#> | U| 752.1046 | 86.03 | -3.211 | -4.606 | -0.3818 |
+#> |.....................| 4.673 | 0.6383 | 0.8713 | 1.369 |
+#> |.....................| 1.062 |...........|...........|...........|
+#> | X| 752.1046 | 86.03 | 0.04030 | 0.009989 | 0.4057 |
+#> |.....................| 4.673 | 0.6383 | 0.8713 | 1.369 |
+#> |.....................| 1.062 |...........|...........|...........|
+#> | 46| 752.09051 | 0.9947 | -0.9746 | -1.040 | -1.052 |
+#> |.....................| -0.6247 | -0.9768 | -0.9147 | -0.6801 |
+#> |.....................| -0.7732 |...........|...........|...........|
+#> | U| 752.09051 | 86.08 | -3.211 | -4.608 | -0.3827 |
+#> |.....................| 4.704 | 0.6355 | 0.8695 | 1.380 |
+#> |.....................| 1.067 |...........|...........|...........|
+#> | X| 752.09051 | 86.08 | 0.04030 | 0.009976 | 0.4055 |
+#> |.....................| 4.704 | 0.6355 | 0.8695 | 1.380 |
+#> |.....................| 1.067 |...........|...........|...........|
+#> | F| Forward Diff. | 5.771 | 0.01029 | 0.1542 | 0.3620 |
+#> |.....................| 0.8997 | 0.2873 | 0.01810 | -0.9019 |
+#> |.....................| -0.3639 |...........|...........|...........|
+#> | 47| 752.06630 | 0.9944 | -0.9751 | -1.045 | -1.068 |
+#> |.....................| -0.6300 | -0.9815 | -0.9184 | -0.6573 |
+#> |.....................| -0.7726 |...........|...........|...........|
+#> | U| 752.0663 | 86.05 | -3.212 | -4.613 | -0.3878 |
+#> |.....................| 4.692 | 0.6323 | 0.8661 | 1.407 |
+#> |.....................| 1.068 |...........|...........|...........|
+#> | X| 752.0663 | 86.05 | 0.04028 | 0.009926 | 0.4043 |
+#> |.....................| 4.692 | 0.6323 | 0.8661 | 1.407 |
+#> |.....................| 1.068 |...........|...........|...........|
+#> | F| Forward Diff. | 3.128 | 0.007908 | 0.004436 | 0.3353 |
+#> |.....................| 0.2209 | 0.1645 | -0.3029 | -0.2852 |
+#> |.....................| -0.2419 |...........|...........|...........|
+#> | 48| 752.06241 | 0.9926 | -0.9758 | -1.042 | -1.095 |
+#> |.....................| -0.6306 | -0.9841 | -0.9113 | -0.6557 |
+#> |.....................| -0.7685 |...........|...........|...........|
+#> | U| 752.06241 | 85.89 | -3.213 | -4.609 | -0.3969 |
+#> |.....................| 4.691 | 0.6304 | 0.8725 | 1.408 |
+#> |.....................| 1.072 |...........|...........|...........|
+#> | X| 752.06241 | 85.89 | 0.04025 | 0.009958 | 0.4021 |
+#> |.....................| 4.691 | 0.6304 | 0.8725 | 1.408 |
+#> |.....................| 1.072 |...........|...........|...........|
+#> | F| Forward Diff. | -8.924 | 0.01284 | 0.1020 | 0.2919 |
+#> |.....................| 0.1011 | -0.08995 | 0.3194 | -0.2130 |
+#> |.....................| -0.05120 |...........|...........|...........|
+#> | 49| 752.04768 | 0.9941 | -0.9763 | -1.043 | -1.124 |
+#> |.....................| -0.6313 | -0.9862 | -0.9116 | -0.6566 |
+#> |.....................| -0.7644 |...........|...........|...........|
+#> | U| 752.04768 | 86.02 | -3.213 | -4.611 | -0.4065 |
+#> |.....................| 4.690 | 0.6289 | 0.8723 | 1.407 |
+#> |.....................| 1.076 |...........|...........|...........|
+#> | X| 752.04768 | 86.02 | 0.04023 | 0.009946 | 0.3998 |
+#> |.....................| 4.690 | 0.6289 | 0.8723 | 1.407 |
+#> |.....................| 1.076 |...........|...........|...........|
+#> | F| Forward Diff. | 0.04447 | 0.001311 | 0.1345 | 0.2729 |
+#> |.....................| 0.05334 | -0.06694 | 0.2984 | -0.1966 |
+#> |.....................| 0.06514 |...........|...........|...........|
+#> | 50| 752.04768 | 0.9941 | -0.9763 | -1.043 | -1.124 |
+#> |.....................| -0.6313 | -0.9862 | -0.9116 | -0.6566 |
+#> |.....................| -0.7644 |...........|...........|...........|
+#> | U| 752.04768 | 86.02 | -3.213 | -4.611 | -0.4065 |
+#> |.....................| 4.690 | 0.6289 | 0.8723 | 1.407 |
+#> |.....................| 1.076 |...........|...........|...........|
+#> | X| 752.04768 | 86.02 | 0.04023 | 0.009946 | 0.3998 |
+#> |.....................| 4.690 | 0.6289 | 0.8723 | 1.407 |
+#> |.....................| 1.076 |...........|...........|...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_alpha |
+#> |.....................| log_beta | sigma | o1 | o2 |
+#> |.....................| o3 | o4 | o5 |...........|
+#> | 1| 491.68697 | 1.000 | -1.000 | -0.9113 | -0.8954 |
+#> |.....................| -0.8491 | -0.8582 | -0.8760 | -0.8739 |
+#> |.....................| -0.8673 | -0.8694 | -0.8683 |...........|
+#> | U| 491.68697 | 94.21 | -5.416 | -0.9966 | -0.2046 |
+#> |.....................| 2.098 | 1.647 | 0.7612 | 0.8665 |
+#> |.....................| 1.192 | 1.089 | 1.144 |...........|
+#> | X| 491.68697 | 94.21 | 0.004447 | 0.2696 | 0.8150 |
+#> |.....................| 8.153 | 1.647 | 0.7612 | 0.8665 |
+#> |.....................| 1.192 | 1.089 | 1.144 |...........|
+#> | G| Gill Diff. | 19.86 | 1.831 | -0.1132 | -0.03447 |
+#> |.....................| -0.1365 | -48.08 | 10.28 | 8.952 |
+#> |.....................| -12.04 | -8.764 | -10.61 |...........|
+#> | 2| 1105.9428 | 0.6506 | -1.032 | -0.9093 | -0.8948 |
+#> |.....................| -0.8467 | -0.01215 | -1.057 | -1.031 |
+#> |.....................| -0.6554 | -0.7152 | -0.6817 |...........|
+#> | U| 1105.9428 | 61.29 | -5.448 | -0.9946 | -0.2040 |
+#> |.....................| 2.101 | 2.344 | 0.6235 | 0.7300 |
+#> |.....................| 1.445 | 1.256 | 1.357 |...........|
+#> | X| 1105.9428 | 61.29 | 0.004306 | 0.2700 | 0.8155 |
+#> |.....................| 8.173 | 2.344 | 0.6235 | 0.7300 |
+#> |.....................| 1.445 | 1.256 | 1.357 |...........|
+#> | 3| 499.02505 | 0.9651 | -1.003 | -0.9111 | -0.8953 |
+#> |.....................| -0.8489 | -0.7736 | -0.8941 | -0.8896 |
+#> |.....................| -0.8462 | -0.8540 | -0.8497 |...........|
+#> | U| 499.02505 | 90.91 | -5.419 | -0.9964 | -0.2045 |
+#> |.....................| 2.099 | 1.717 | 0.7475 | 0.8529 |
+#> |.....................| 1.217 | 1.105 | 1.165 |...........|
+#> | X| 499.02505 | 90.91 | 0.004433 | 0.2696 | 0.8150 |
+#> |.....................| 8.155 | 1.717 | 0.7475 | 0.8529 |
+#> |.....................| 1.217 | 1.105 | 1.165 |...........|
+#> | 4| 491.11153 | 0.9924 | -1.001 | -0.9112 | -0.8954 |
+#> |.....................| -0.8491 | -0.8397 | -0.8799 | -0.8773 |
+#> |.....................| -0.8627 | -0.8661 | -0.8642 |...........|
+#> | U| 491.11153 | 93.49 | -5.416 | -0.9966 | -0.2046 |
+#> |.....................| 2.098 | 1.663 | 0.7582 | 0.8635 |
+#> |.....................| 1.198 | 1.092 | 1.148 |...........|
+#> | X| 491.11153 | 93.49 | 0.004444 | 0.2696 | 0.8150 |
+#> |.....................| 8.154 | 1.663 | 0.7582 | 0.8635 |
+#> |.....................| 1.198 | 1.092 | 1.148 |...........|
+#> | F| Forward Diff. | -141.0 | 1.761 | -0.2309 | -0.1084 |
+#> |.....................| -0.3671 | -44.06 | 11.23 | 7.698 |
+#> |.....................| -11.77 | -8.480 | -10.17 |...........|
+#> | 5| 489.72110 | 1.001 | -1.001 | -0.9112 | -0.8954 |
+#> |.....................| -0.8490 | -0.8217 | -0.8840 | -0.8806 |
+#> |.....................| -0.8581 | -0.8627 | -0.8602 |...........|
+#> | U| 489.7211 | 94.29 | -5.417 | -0.9965 | -0.2046 |
+#> |.....................| 2.099 | 1.678 | 0.7552 | 0.8607 |
+#> |.....................| 1.203 | 1.096 | 1.153 |...........|
+#> | X| 489.7211 | 94.29 | 0.004441 | 0.2696 | 0.8150 |
+#> |.....................| 8.154 | 1.678 | 0.7552 | 0.8607 |
+#> |.....................| 1.203 | 1.096 | 1.153 |...........|
+#> | F| Forward Diff. | 37.99 | 1.786 | -0.09663 | -0.03934 |
+#> |.....................| -0.1210 | -40.49 | 9.520 | 7.642 |
+#> |.....................| -11.65 | -8.313 | -10.04 |...........|
+#> | 6| 488.87741 | 0.9957 | -1.002 | -0.9111 | -0.8953 |
+#> |.....................| -0.8490 | -0.8027 | -0.8883 | -0.8842 |
+#> |.....................| -0.8530 | -0.8591 | -0.8558 |...........|
+#> | U| 488.87741 | 93.80 | -5.418 | -0.9965 | -0.2045 |
+#> |.....................| 2.099 | 1.693 | 0.7519 | 0.8576 |
+#> |.....................| 1.209 | 1.100 | 1.158 |...........|
+#> | X| 488.87741 | 93.80 | 0.004437 | 0.2696 | 0.8150 |
+#> |.....................| 8.155 | 1.693 | 0.7519 | 0.8576 |
+#> |.....................| 1.209 | 1.100 | 1.158 |...........|
+#> | F| Forward Diff. | -68.52 | 1.732 | -0.1791 | -0.08434 |
+#> |.....................| -0.2775 | -36.72 | 9.505 | 7.234 |
+#> |.....................| -11.37 | -8.098 | -9.790 |...........|
+#> | 7| 487.98842 | 1.002 | -1.003 | -0.9111 | -0.8953 |
+#> |.....................| -0.8489 | -0.7841 | -0.8926 | -0.8878 |
+#> |.....................| -0.8478 | -0.8553 | -0.8512 |...........|
+#> | U| 487.98842 | 94.37 | -5.418 | -0.9964 | -0.2045 |
+#> |.....................| 2.099 | 1.708 | 0.7486 | 0.8545 |
+#> |.....................| 1.215 | 1.104 | 1.163 |...........|
+#> | X| 487.98842 | 94.37 | 0.004434 | 0.2697 | 0.8150 |
+#> |.....................| 8.156 | 1.708 | 0.7486 | 0.8545 |
+#> |.....................| 1.215 | 1.104 | 1.163 |...........|
+#> | F| Forward Diff. | 53.83 | 1.743 | -0.07921 | -0.03701 |
+#> |.....................| -0.09401 | -33.22 | 8.823 | 7.101 |
+#> |.....................| -11.24 | -7.914 | -9.621 |...........|
+#> | 8| 487.18834 | 0.9967 | -1.004 | -0.9110 | -0.8953 |
+#> |.....................| -0.8488 | -0.7657 | -0.8973 | -0.8916 |
+#> |.....................| -0.8421 | -0.8512 | -0.8463 |...........|
+#> | U| 487.18834 | 93.89 | -5.419 | -0.9963 | -0.2045 |
+#> |.....................| 2.099 | 1.724 | 0.7451 | 0.8512 |
+#> |.....................| 1.222 | 1.108 | 1.169 |...........|
+#> | X| 487.18834 | 93.89 | 0.004430 | 0.2697 | 0.8151 |
+#> |.....................| 8.156 | 1.724 | 0.7451 | 0.8512 |
+#> |.....................| 1.222 | 1.108 | 1.169 |...........|
+#> | F| Forward Diff. | -47.29 | 1.692 | -0.1608 | -0.08286 |
+#> |.....................| -0.2512 | -29.89 | 8.493 | 6.629 |
+#> |.....................| -10.92 | -7.677 | -9.350 |...........|
+#> | 9| 486.46922 | 1.002 | -1.005 | -0.9109 | -0.8952 |
+#> |.....................| -0.8487 | -0.7480 | -0.9022 | -0.8958 |
+#> |.....................| -0.8355 | -0.8466 | -0.8406 |...........|
+#> | U| 486.46922 | 94.36 | -5.420 | -0.9963 | -0.2045 |
+#> |.....................| 2.099 | 1.738 | 0.7413 | 0.8476 |
+#> |.....................| 1.230 | 1.113 | 1.175 |...........|
+#> | X| 486.46922 | 94.36 | 0.004425 | 0.2697 | 0.8151 |
+#> |.....................| 8.157 | 1.738 | 0.7413 | 0.8476 |
+#> |.....................| 1.230 | 1.113 | 1.175 |...........|
+#> | F| Forward Diff. | 49.83 | 1.694 | -0.07480 | -0.03429 |
+#> |.....................| -0.09436 | -26.68 | 8.123 | 6.503 |
+#> |.....................| -10.68 | -7.439 | -9.119 |...........|
+#> | 10| 485.78721 | 0.9968 | -1.006 | -0.9109 | -0.8952 |
+#> |.....................| -0.8486 | -0.7319 | -0.9078 | -0.9005 |
+#> |.....................| -0.8277 | -0.8412 | -0.8339 |...........|
+#> | U| 485.78721 | 93.91 | -5.422 | -0.9962 | -0.2044 |
+#> |.....................| 2.099 | 1.752 | 0.7370 | 0.8435 |
+#> |.....................| 1.239 | 1.119 | 1.183 |...........|
+#> | X| 485.78721 | 93.91 | 0.004420 | 0.2697 | 0.8151 |
+#> |.....................| 8.158 | 1.752 | 0.7370 | 0.8435 |
+#> |.....................| 1.239 | 1.119 | 1.183 |...........|
+#> | F| Forward Diff. | -42.45 | 1.646 | -0.1526 | -0.07491 |
+#> |.....................| -0.2510 | -24.12 | 7.576 | 5.974 |
+#> |.....................| -10.35 | -7.128 | -8.768 |...........|
+#> | 11| 485.17009 | 1.001 | -1.008 | -0.9107 | -0.8952 |
+#> |.....................| -0.8484 | -0.7183 | -0.9141 | -0.9058 |
+#> |.....................| -0.8180 | -0.8347 | -0.8257 |...........|
+#> | U| 485.17009 | 94.32 | -5.423 | -0.9961 | -0.2044 |
+#> |.....................| 2.099 | 1.763 | 0.7322 | 0.8389 |
+#> |.....................| 1.251 | 1.126 | 1.192 |...........|
+#> | X| 485.17009 | 94.32 | 0.004413 | 0.2697 | 0.8152 |
+#> |.....................| 8.160 | 1.763 | 0.7322 | 0.8389 |
+#> |.....................| 1.251 | 1.126 | 1.192 |...........|
+#> | 12| 484.56759 | 1.002 | -1.010 | -0.9106 | -0.8951 |
+#> |.....................| -0.8481 | -0.7038 | -0.9212 | -0.9119 |
+#> |.....................| -0.8067 | -0.8272 | -0.8163 |...........|
+#> | U| 484.56759 | 94.37 | -5.425 | -0.9959 | -0.2043 |
+#> |.....................| 2.099 | 1.775 | 0.7268 | 0.8336 |
+#> |.....................| 1.264 | 1.134 | 1.203 |...........|
+#> | X| 484.56759 | 94.37 | 0.004404 | 0.2697 | 0.8152 |
+#> |.....................| 8.162 | 1.775 | 0.7268 | 0.8336 |
+#> |.....................| 1.264 | 1.134 | 1.203 |...........|
+#> | 13| 483.17982 | 1.003 | -1.015 | -0.9102 | -0.8949 |
+#> |.....................| -0.8475 | -0.6634 | -0.9410 | -0.9287 |
+#> |.....................| -0.7754 | -0.8064 | -0.7900 |...........|
+#> | U| 483.17982 | 94.51 | -5.431 | -0.9956 | -0.2042 |
+#> |.....................| 2.100 | 1.808 | 0.7117 | 0.8190 |
+#> |.....................| 1.302 | 1.157 | 1.233 |...........|
+#> | X| 483.17982 | 94.51 | 0.004381 | 0.2698 | 0.8153 |
+#> |.....................| 8.167 | 1.808 | 0.7117 | 0.8190 |
+#> |.....................| 1.302 | 1.157 | 1.233 |...........|
+#> | F| Forward Diff. | 68.60 | 1.559 | 0.008498 | -0.01857 |
+#> |.....................| -0.01950 | -13.38 | 5.413 | 4.461 |
+#> |.....................| -8.084 | -5.202 | -6.751 |...........|
+#> | 14| 482.50435 | 0.9937 | -1.034 | -0.9105 | -0.8944 |
+#> |.....................| -0.8462 | -0.6947 | -0.9713 | -0.9553 |
+#> |.....................| -0.7043 | -0.7694 | -0.7343 |...........|
+#> | U| 482.50435 | 93.61 | -5.449 | -0.9958 | -0.2036 |
+#> |.....................| 2.101 | 1.782 | 0.6887 | 0.7959 |
+#> |.....................| 1.386 | 1.197 | 1.297 |...........|
+#> | X| 482.50435 | 93.61 | 0.004300 | 0.2698 | 0.8158 |
+#> |.....................| 8.177 | 1.782 | 0.6887 | 0.7959 |
+#> |.....................| 1.386 | 1.197 | 1.297 |...........|
+#> | F| Forward Diff. | -85.62 | 1.442 | -0.1650 | -0.08233 |
+#> |.....................| -0.3434 | -17.31 | 3.930 | 3.048 |
+#> |.....................| -4.934 | -3.045 | -4.080 |...........|
+#> | 15| 481.97261 | 1.003 | -1.090 | -0.9106 | -0.8929 |
+#> |.....................| -0.8403 | -0.7109 | -0.9936 | -0.9798 |
+#> |.....................| -0.6305 | -0.7595 | -0.6850 |...........|
+#> | U| 481.97261 | 94.53 | -5.505 | -0.9959 | -0.2021 |
+#> |.....................| 2.107 | 1.769 | 0.6717 | 0.7747 |
+#> |.....................| 1.474 | 1.208 | 1.353 |...........|
+#> | X| 481.97261 | 94.53 | 0.004066 | 0.2697 | 0.8170 |
+#> |.....................| 8.226 | 1.769 | 0.6717 | 0.7747 |
+#> |.....................| 1.474 | 1.208 | 1.353 |...........|
+#> | F| Forward Diff. | 56.89 | 1.274 | 0.1237 | 0.02279 |
+#> |.....................| 0.2367 | -19.64 | 1.923 | 2.281 |
+#> |.....................| -1.663 | -2.419 | -1.870 |...........|
+#> | 16| 481.06506 | 1.001 | -1.169 | -0.9152 | -0.8919 |
+#> |.....................| -0.8407 | -0.6475 | -0.9528 | -0.9773 |
+#> |.....................| -0.6368 | -0.7786 | -0.6952 |...........|
+#> | U| 481.06506 | 94.29 | -5.585 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.821 | 0.7028 | 0.7769 |
+#> |.....................| 1.467 | 1.187 | 1.341 |...........|
+#> | X| 481.06506 | 94.29 | 0.003755 | 0.2688 | 0.8179 |
+#> |.....................| 8.223 | 1.821 | 0.7028 | 0.7769 |
+#> |.....................| 1.467 | 1.187 | 1.341 |...........|
+#> | F| Forward Diff. | 24.24 | 0.9898 | -0.1087 | 0.01886 |
+#> |.....................| 0.1247 | -10.78 | 3.743 | 2.188 |
+#> |.....................| -2.085 | -3.507 | -2.452 |...........|
+#> | 17| 481.22982 | 0.9921 | -1.212 | -0.9099 | -0.8928 |
+#> |.....................| -0.8459 | -0.6315 | -1.015 | -0.9814 |
+#> |.....................| -0.6906 | -0.7213 | -0.7106 |...........|
+#> | U| 481.22982 | 93.46 | -5.628 | -0.9952 | -0.2020 |
+#> |.....................| 2.102 | 1.834 | 0.6553 | 0.7733 |
+#> |.....................| 1.403 | 1.250 | 1.324 |...........|
+#> | X| 481.22982 | 93.46 | 0.003596 | 0.2699 | 0.8171 |
+#> |.....................| 8.180 | 1.834 | 0.6553 | 0.7733 |
+#> |.....................| 1.403 | 1.250 | 1.324 |...........|
+#> | 18| 481.29798 | 0.9919 | -1.186 | -0.9131 | -0.8922 |
+#> |.....................| -0.8428 | -0.6388 | -0.9780 | -0.9794 |
+#> |.....................| -0.6574 | -0.7554 | -0.7007 |...........|
+#> | U| 481.29798 | 93.44 | -5.602 | -0.9984 | -0.2014 |
+#> |.....................| 2.105 | 1.828 | 0.6836 | 0.7751 |
+#> |.....................| 1.442 | 1.213 | 1.335 |...........|
+#> | X| 481.29798 | 93.44 | 0.003691 | 0.2693 | 0.8176 |
+#> |.....................| 8.206 | 1.828 | 0.6836 | 0.7751 |
+#> |.....................| 1.442 | 1.213 | 1.335 |...........|
+#> | 19| 481.41397 | 0.9918 | -1.173 | -0.9147 | -0.8919 |
+#> |.....................| -0.8412 | -0.6424 | -0.9596 | -0.9784 |
+#> |.....................| -0.6408 | -0.7724 | -0.6957 |...........|
+#> | U| 481.41397 | 93.43 | -5.589 | -1.000 | -0.2012 |
+#> |.....................| 2.106 | 1.825 | 0.6976 | 0.7759 |
+#> |.....................| 1.462 | 1.194 | 1.341 |...........|
+#> | X| 481.41397 | 93.43 | 0.003739 | 0.2689 | 0.8178 |
+#> |.....................| 8.219 | 1.825 | 0.6976 | 0.7759 |
+#> |.....................| 1.462 | 1.194 | 1.341 |...........|
+#> | 20| 481.05031 | 0.9977 | -1.169 | -0.9152 | -0.8919 |
+#> |.....................| -0.8407 | -0.6461 | -0.9533 | -0.9776 |
+#> |.....................| -0.6366 | -0.7782 | -0.6949 |...........|
+#> | U| 481.05031 | 93.99 | -5.585 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.822 | 0.7024 | 0.7766 |
+#> |.....................| 1.467 | 1.188 | 1.342 |...........|
+#> | X| 481.05031 | 93.99 | 0.003754 | 0.2688 | 0.8179 |
+#> |.....................| 8.223 | 1.822 | 0.7024 | 0.7766 |
+#> |.....................| 1.467 | 1.188 | 1.342 |...........|
+#> | F| Forward Diff. | -27.42 | 0.9768 | -0.2107 | -0.01109 |
+#> |.....................| -0.02839 | -10.63 | 3.585 | 2.076 |
+#> |.....................| -2.082 | -3.487 | -2.432 |...........|
+#> | 21| 481.00693 | 0.9997 | -1.170 | -0.9150 | -0.8919 |
+#> |.....................| -0.8408 | -0.6450 | -0.9548 | -0.9778 |
+#> |.....................| -0.6377 | -0.7765 | -0.6951 |...........|
+#> | U| 481.00693 | 94.18 | -5.586 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.823 | 0.7012 | 0.7764 |
+#> |.....................| 1.466 | 1.190 | 1.342 |...........|
+#> | X| 481.00693 | 94.18 | 0.003750 | 0.2689 | 0.8178 |
+#> |.....................| 8.222 | 1.823 | 0.7012 | 0.7764 |
+#> |.....................| 1.466 | 1.190 | 1.342 |...........|
+#> | F| Forward Diff. | 5.549 | 0.9801 | -0.1366 | 0.007724 |
+#> |.....................| 0.06864 | -10.47 | 3.736 | 2.095 |
+#> |.....................| -2.145 | -3.386 | -2.439 |...........|
+#> | 22| 480.97727 | 0.9982 | -1.171 | -0.9150 | -0.8919 |
+#> |.....................| -0.8408 | -0.6422 | -0.9558 | -0.9784 |
+#> |.....................| -0.6371 | -0.7756 | -0.6944 |...........|
+#> | U| 480.97727 | 94.04 | -5.586 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.825 | 0.7005 | 0.7760 |
+#> |.....................| 1.466 | 1.191 | 1.342 |...........|
+#> | X| 480.97727 | 94.04 | 0.003749 | 0.2689 | 0.8178 |
+#> |.....................| 8.222 | 1.825 | 0.7005 | 0.7760 |
+#> |.....................| 1.466 | 1.191 | 1.342 |...........|
+#> | F| Forward Diff. | -18.22 | 0.9728 | -0.1820 | -0.005388 |
+#> |.....................| -0.004679 | -10.15 | 3.348 | 1.956 |
+#> |.....................| -2.141 | -3.348 | -2.415 |...........|
+#> | 23| 480.94781 | 0.9999 | -1.172 | -0.9148 | -0.8919 |
+#> |.....................| -0.8410 | -0.6410 | -0.9575 | -0.9785 |
+#> |.....................| -0.6383 | -0.7738 | -0.6946 |...........|
+#> | U| 480.94781 | 94.20 | -5.587 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.826 | 0.6992 | 0.7758 |
+#> |.....................| 1.465 | 1.193 | 1.342 |...........|
+#> | X| 480.94781 | 94.20 | 0.003745 | 0.2689 | 0.8178 |
+#> |.....................| 8.220 | 1.826 | 0.6992 | 0.7758 |
+#> |.....................| 1.465 | 1.193 | 1.342 |...........|
+#> | F| Forward Diff. | 8.568 | 0.9740 | -0.1199 | 0.009837 |
+#> |.....................| 0.07469 | -9.926 | 3.371 | 0.7973 |
+#> |.....................| -2.181 | -3.230 | -2.408 |...........|
+#> | 24| 480.92664 | 0.9984 | -1.173 | -0.9147 | -0.8919 |
+#> |.....................| -0.8411 | -0.6390 | -0.9589 | -0.9778 |
+#> |.....................| -0.6386 | -0.7721 | -0.6942 |...........|
+#> | U| 480.92664 | 94.06 | -5.588 | -1.000 | -0.2011 |
+#> |.....................| 2.107 | 1.828 | 0.6981 | 0.7765 |
+#> |.....................| 1.465 | 1.195 | 1.343 |...........|
+#> | X| 480.92664 | 94.06 | 0.003741 | 0.2689 | 0.8178 |
+#> |.....................| 8.219 | 1.828 | 0.6981 | 0.7765 |
+#> |.....................| 1.465 | 1.195 | 1.343 |...........|
+#> | F| Forward Diff. | -15.24 | 0.9644 | -0.1632 | -0.002739 |
+#> |.....................| -0.008738 | -9.656 | 3.177 | 0.7945 |
+#> |.....................| -2.140 | -3.159 | -2.407 |...........|
+#> | 25| 480.90633 | 0.9999 | -1.174 | -0.9146 | -0.8920 |
+#> |.....................| -0.8412 | -0.6376 | -0.9602 | -0.9760 |
+#> |.....................| -0.6390 | -0.7705 | -0.6939 |...........|
+#> | U| 480.90633 | 94.20 | -5.589 | -0.9999 | -0.2012 |
+#> |.....................| 2.106 | 1.829 | 0.6971 | 0.7780 |
+#> |.....................| 1.464 | 1.196 | 1.343 |...........|
+#> | X| 480.90633 | 94.20 | 0.003737 | 0.2690 | 0.8178 |
+#> |.....................| 8.219 | 1.829 | 0.6971 | 0.7780 |
+#> |.....................| 1.464 | 1.196 | 1.343 |...........|
+#> | F| Forward Diff. | 8.878 | 0.9654 | -0.1149 | 0.008298 |
+#> |.....................| 0.06381 | -9.456 | 3.199 | 2.165 |
+#> |.....................| -2.158 | -3.035 | -2.359 |...........|
+#> | 26| 480.88677 | 0.9984 | -1.175 | -0.9145 | -0.8920 |
+#> |.....................| -0.8413 | -0.6358 | -0.9617 | -0.9757 |
+#> |.....................| -0.6395 | -0.7687 | -0.6936 |...........|
+#> | U| 480.88677 | 94.05 | -5.591 | -0.9998 | -0.2012 |
+#> |.....................| 2.106 | 1.831 | 0.6960 | 0.7783 |
+#> |.....................| 1.464 | 1.198 | 1.343 |...........|
+#> | X| 480.88677 | 94.05 | 0.003733 | 0.2690 | 0.8178 |
+#> |.....................| 8.218 | 1.831 | 0.6960 | 0.7783 |
+#> |.....................| 1.464 | 1.198 | 1.343 |...........|
+#> | F| Forward Diff. | -15.55 | 0.9550 | -0.1566 | -0.004027 |
+#> |.....................| -0.01529 | -9.334 | 3.082 | 0.8457 |
+#> |.....................| -2.216 | -2.967 | -2.371 |...........|
+#> | 27| 480.86430 | 0.9998 | -1.177 | -0.9143 | -0.8920 |
+#> |.....................| -0.8414 | -0.6346 | -0.9633 | -0.9749 |
+#> |.....................| -0.6404 | -0.7668 | -0.6935 |...........|
+#> | U| 480.8643 | 94.19 | -5.592 | -0.9996 | -0.2012 |
+#> |.....................| 2.106 | 1.832 | 0.6948 | 0.7790 |
+#> |.....................| 1.463 | 1.200 | 1.343 |...........|
+#> | X| 480.8643 | 94.19 | 0.003727 | 0.2690 | 0.8177 |
+#> |.....................| 8.217 | 1.832 | 0.6948 | 0.7790 |
+#> |.....................| 1.463 | 1.200 | 1.343 |...........|
+#> | F| Forward Diff. | 6.756 | 0.9537 | -0.1079 | 0.006011 |
+#> |.....................| 0.04748 | -9.023 | 3.021 | 2.222 |
+#> |.....................| -2.227 | -2.836 | -2.339 |...........|
+#> | 28| 480.84403 | 0.9982 | -1.178 | -0.9142 | -0.8920 |
+#> |.....................| -0.8415 | -0.6324 | -0.9646 | -0.9751 |
+#> |.....................| -0.6405 | -0.7653 | -0.6931 |...........|
+#> | U| 480.84403 | 94.04 | -5.593 | -0.9995 | -0.2012 |
+#> |.....................| 2.106 | 1.833 | 0.6938 | 0.7788 |
+#> |.....................| 1.462 | 1.202 | 1.344 |...........|
+#> | X| 480.84403 | 94.04 | 0.003723 | 0.2690 | 0.8177 |
+#> |.....................| 8.216 | 1.833 | 0.6938 | 0.7788 |
+#> |.....................| 1.462 | 1.202 | 1.344 |...........|
+#> | F| Forward Diff. | -17.74 | 0.9443 | -0.1486 | -0.005686 |
+#> |.....................| -0.02964 | -8.905 | 2.905 | 2.091 |
+#> |.....................| -2.264 | -2.753 | -2.319 |...........|
+#> | 29| 480.81486 | 0.9998 | -1.179 | -0.9140 | -0.8921 |
+#> |.....................| -0.8417 | -0.6315 | -0.9657 | -0.9770 |
+#> |.....................| -0.6415 | -0.7640 | -0.6932 |...........|
+#> | U| 480.81486 | 94.18 | -5.595 | -0.9993 | -0.2013 |
+#> |.....................| 2.106 | 1.834 | 0.6930 | 0.7772 |
+#> |.....................| 1.461 | 1.203 | 1.344 |...........|
+#> | X| 480.81486 | 94.18 | 0.003718 | 0.2691 | 0.8177 |
+#> |.....................| 8.215 | 1.834 | 0.6930 | 0.7772 |
+#> |.....................| 1.461 | 1.203 | 1.344 |...........|
+#> | F| Forward Diff. | 6.172 | 0.9439 | -0.09077 | 0.005496 |
+#> |.....................| 0.04002 | -8.557 | 3.060 | 0.8688 |
+#> |.....................| -2.237 | -2.681 | -2.329 |...........|
+#> | 30| 480.79675 | 0.9982 | -1.180 | -0.9139 | -0.8921 |
+#> |.....................| -0.8418 | -0.6292 | -0.9672 | -0.9770 |
+#> |.....................| -0.6415 | -0.7628 | -0.6927 |...........|
+#> | U| 480.79675 | 94.04 | -5.596 | -0.9992 | -0.2013 |
+#> |.....................| 2.106 | 1.836 | 0.6918 | 0.7772 |
+#> |.....................| 1.461 | 1.205 | 1.344 |...........|
+#> | X| 480.79675 | 94.04 | 0.003714 | 0.2691 | 0.8177 |
+#> |.....................| 8.214 | 1.836 | 0.6918 | 0.7772 |
+#> |.....................| 1.461 | 1.205 | 1.344 |...........|
+#> | F| Forward Diff. | -18.05 | 0.9344 | -0.1333 | -0.006636 |
+#> |.....................| -0.03697 | -8.406 | 2.763 | 0.7695 |
+#> |.....................| -2.291 | -2.623 | -2.307 |...........|
+#> | 31| 480.77804 | 0.9997 | -1.182 | -0.9138 | -0.8921 |
+#> |.....................| -0.8419 | -0.6281 | -0.9686 | -0.9750 |
+#> |.....................| -0.6417 | -0.7615 | -0.6923 |...........|
+#> | U| 480.77804 | 94.18 | -5.597 | -0.9991 | -0.2013 |
+#> |.....................| 2.106 | 1.837 | 0.6907 | 0.7789 |
+#> |.....................| 1.461 | 1.206 | 1.345 |...........|
+#> | X| 480.77804 | 94.18 | 0.003708 | 0.2691 | 0.8176 |
+#> |.....................| 8.213 | 1.837 | 0.6907 | 0.7789 |
+#> |.....................| 1.461 | 1.206 | 1.345 |...........|
+#> | F| Forward Diff. | 5.466 | 0.9331 | -0.08875 | 0.003744 |
+#> |.....................| 0.02543 | -8.171 | 2.670 | 2.155 |
+#> |.....................| -2.279 | -2.534 | -2.278 |...........|
+#> | 32| 480.75892 | 0.9982 | -1.183 | -0.9137 | -0.8921 |
+#> |.....................| -0.8419 | -0.6258 | -0.9698 | -0.9756 |
+#> |.....................| -0.6414 | -0.7603 | -0.6917 |...........|
+#> | U| 480.75892 | 94.03 | -5.598 | -0.9991 | -0.2014 |
+#> |.....................| 2.106 | 1.839 | 0.6899 | 0.7784 |
+#> |.....................| 1.461 | 1.207 | 1.346 |...........|
+#> | X| 480.75892 | 94.03 | 0.003704 | 0.2691 | 0.8176 |
+#> |.....................| 8.212 | 1.839 | 0.6899 | 0.7784 |
+#> |.....................| 1.461 | 1.207 | 1.346 |...........|
+#> | F| Forward Diff. | -18.29 | 0.9240 | -0.1279 | -0.008301 |
+#> |.....................| -0.04619 | -7.961 | 2.584 | 0.8229 |
+#> |.....................| -2.311 | -2.476 | -2.253 |...........|
+#> | 33| 480.73432 | 0.9997 | -1.185 | -0.9136 | -0.8922 |
+#> |.....................| -0.8421 | -0.6250 | -0.9708 | -0.9758 |
+#> |.....................| -0.6420 | -0.7587 | -0.6914 |...........|
+#> | U| 480.73432 | 94.18 | -5.601 | -0.9989 | -0.2014 |
+#> |.....................| 2.105 | 1.840 | 0.6891 | 0.7782 |
+#> |.....................| 1.461 | 1.209 | 1.346 |...........|
+#> | X| 480.73432 | 94.18 | 0.003695 | 0.2692 | 0.8176 |
+#> |.....................| 8.211 | 1.840 | 0.6891 | 0.7782 |
+#> |.....................| 1.461 | 1.209 | 1.346 |...........|
+#> | F| Forward Diff. | 5.056 | 0.9202 | -0.07575 | 0.002374 |
+#> |.....................| 0.02179 | -7.789 | 2.502 | 2.101 |
+#> |.....................| -2.273 | -2.370 | -2.217 |...........|
+#> | 34| 480.71449 | 0.9983 | -1.187 | -0.9135 | -0.8922 |
+#> |.....................| -0.8422 | -0.6227 | -0.9719 | -0.9765 |
+#> |.....................| -0.6416 | -0.7575 | -0.6908 |...........|
+#> | U| 480.71449 | 94.05 | -5.602 | -0.9988 | -0.2014 |
+#> |.....................| 2.105 | 1.841 | 0.6883 | 0.7776 |
+#> |.....................| 1.461 | 1.210 | 1.347 |...........|
+#> | X| 480.71449 | 94.05 | 0.003690 | 0.2692 | 0.8175 |
+#> |.....................| 8.210 | 1.841 | 0.6883 | 0.7776 |
+#> |.....................| 1.461 | 1.210 | 1.347 |...........|
+#> | F| Forward Diff. | -16.10 | 0.9104 | -0.1099 | -0.008208 |
+#> |.....................| -0.04557 | -7.571 | 2.606 | 1.992 |
+#> |.....................| -2.295 | -2.312 | -2.196 |...........|
+#> | 35| 480.68777 | 0.9997 | -1.189 | -0.9134 | -0.8923 |
+#> |.....................| -0.8423 | -0.6220 | -0.9726 | -0.9789 |
+#> |.....................| -0.6421 | -0.7569 | -0.6908 |...........|
+#> | U| 480.68777 | 94.18 | -5.604 | -0.9987 | -0.2015 |
+#> |.....................| 2.105 | 1.842 | 0.6877 | 0.7755 |
+#> |.....................| 1.461 | 1.211 | 1.347 |...........|
+#> | X| 480.68777 | 94.18 | 0.003683 | 0.2692 | 0.8175 |
+#> |.....................| 8.209 | 1.842 | 0.6877 | 0.7755 |
+#> |.....................| 1.461 | 1.211 | 1.347 |...........|
+#> | F| Forward Diff. | 4.858 | 0.9091 | -0.06076 | 0.001972 |
+#> |.....................| 0.01464 | -7.318 | 2.391 | 0.7174 |
+#> |.....................| -2.245 | -2.255 | -2.188 |...........|
+#> | 36| 480.67297 | 0.9982 | -1.190 | -0.9134 | -0.8923 |
+#> |.....................| -0.8424 | -0.6196 | -0.9738 | -0.9789 |
+#> |.....................| -0.6415 | -0.7559 | -0.6900 |...........|
+#> | U| 480.67297 | 94.03 | -5.605 | -0.9987 | -0.2015 |
+#> |.....................| 2.105 | 1.844 | 0.6868 | 0.7755 |
+#> |.....................| 1.461 | 1.212 | 1.348 |...........|
+#> | X| 480.67297 | 94.03 | 0.003678 | 0.2692 | 0.8175 |
+#> |.....................| 8.209 | 1.844 | 0.6868 | 0.7755 |
+#> |.....................| 1.461 | 1.212 | 1.348 |...........|
+#> | F| Forward Diff. | -18.29 | 0.8994 | -0.1037 | -0.01039 |
+#> |.....................| -0.05604 | -7.086 | 2.324 | 0.6431 |
+#> |.....................| -2.272 | -2.229 | -2.170 |...........|
+#> | 37| 480.65610 | 0.9996 | -1.192 | -0.9134 | -0.8923 |
+#> |.....................| -0.8424 | -0.6187 | -0.9745 | -0.9768 |
+#> |.....................| -0.6410 | -0.7549 | -0.6892 |...........|
+#> | U| 480.6561 | 94.17 | -5.607 | -0.9987 | -0.2015 |
+#> |.....................| 2.105 | 1.845 | 0.6862 | 0.7773 |
+#> |.....................| 1.462 | 1.213 | 1.348 |...........|
+#> | X| 480.6561 | 94.17 | 0.003671 | 0.2692 | 0.8175 |
+#> |.....................| 8.208 | 1.845 | 0.6862 | 0.7773 |
+#> |.....................| 1.462 | 1.213 | 1.348 |...........|
+#> | F| Forward Diff. | 3.523 | 0.8967 | -0.06519 |-0.0005238 |
+#> |.....................| 0.007306 | -6.938 | 2.250 | 0.8205 |
+#> |.....................| -2.209 | -2.143 | -2.109 |...........|
+#> | 38| 480.63930 | 0.9982 | -1.192 | -0.9133 | -0.8923 |
+#> |.....................| -0.8425 | -0.6159 | -0.9754 | -0.9772 |
+#> |.....................| -0.6401 | -0.7540 | -0.6884 |...........|
+#> | U| 480.6393 | 94.04 | -5.608 | -0.9987 | -0.2015 |
+#> |.....................| 2.105 | 1.847 | 0.6856 | 0.7770 |
+#> |.....................| 1.463 | 1.214 | 1.349 |...........|
+#> | X| 480.6393 | 94.04 | 0.003670 | 0.2692 | 0.8175 |
+#> |.....................| 8.208 | 1.847 | 0.6856 | 0.7770 |
+#> |.....................| 1.463 | 1.214 | 1.349 |...........|
+#> | F| Forward Diff. | -17.45 | 0.8903 | -0.1044 | -0.01155 |
+#> |.....................| -0.05881 | -6.641 | 2.195 | 1.966 |
+#> |.....................| -2.207 | -2.119 | -2.090 |...........|
+#> | 39| 480.61554 | 0.9996 | -1.195 | -0.9133 | -0.8924 |
+#> |.....................| -0.8426 | -0.6153 | -0.9757 | -0.9778 |
+#> |.....................| -0.6400 | -0.7531 | -0.6877 |...........|
+#> | U| 480.61554 | 94.16 | -5.611 | -0.9986 | -0.2016 |
+#> |.....................| 2.105 | 1.848 | 0.6853 | 0.7765 |
+#> |.....................| 1.463 | 1.215 | 1.350 |...........|
+#> | X| 480.61554 | 94.16 | 0.003659 | 0.2692 | 0.8174 |
+#> |.....................| 8.207 | 1.848 | 0.6853 | 0.7765 |
+#> |.....................| 1.463 | 1.215 | 1.350 |...........|
+#> | F| Forward Diff. | 2.395 | 0.8850 | -0.05988 | -0.001937 |
+#> |.....................| 0.0008548 | -6.531 | 2.145 | 0.7341 |
+#> |.....................| -2.178 | -2.045 | -2.040 |...........|
+#> | 40| 480.59501 | 0.9985 | -1.195 | -0.9132 | -0.8924 |
+#> |.....................| -0.8426 | -0.6124 | -0.9766 | -0.9781 |
+#> |.....................| -0.6390 | -0.7522 | -0.6868 |...........|
+#> | U| 480.59501 | 94.06 | -5.611 | -0.9986 | -0.2016 |
+#> |.....................| 2.105 | 1.850 | 0.6846 | 0.7762 |
+#> |.....................| 1.464 | 1.216 | 1.351 |...........|
+#> | X| 480.59501 | 94.06 | 0.003658 | 0.2692 | 0.8174 |
+#> |.....................| 8.207 | 1.850 | 0.6846 | 0.7762 |
+#> |.....................| 1.464 | 1.216 | 1.351 |...........|
+#> | F| Forward Diff. | -13.20 | 0.8797 | -0.08878 | -0.01245 |
+#> |.....................| -0.05202 | -6.149 | 2.097 | 1.936 |
+#> |.....................| -2.128 | -2.007 | -2.021 |...........|
+#> | 41| 480.57374 | 0.9995 | -1.198 | -0.9132 | -0.8924 |
+#> |.....................| -0.8426 | -0.6117 | -0.9768 | -0.9794 |
+#> |.....................| -0.6387 | -0.7515 | -0.6862 |...........|
+#> | U| 480.57374 | 94.16 | -5.614 | -0.9986 | -0.2016 |
+#> |.....................| 2.105 | 1.851 | 0.6845 | 0.7751 |
+#> |.....................| 1.464 | 1.217 | 1.352 |...........|
+#> | X| 480.57374 | 94.16 | 0.003647 | 0.2692 | 0.8174 |
+#> |.....................| 8.207 | 1.851 | 0.6845 | 0.7751 |
+#> |.....................| 1.464 | 1.217 | 1.352 |...........|
+#> | 42| 480.55656 | 0.9993 | -1.203 | -0.9133 | -0.8924 |
+#> |.....................| -0.8427 | -0.6115 | -0.9767 | -0.9815 |
+#> |.....................| -0.6386 | -0.7506 | -0.6853 |...........|
+#> | U| 480.55656 | 94.14 | -5.619 | -0.9986 | -0.2016 |
+#> |.....................| 2.105 | 1.851 | 0.6846 | 0.7733 |
+#> |.....................| 1.465 | 1.218 | 1.353 |...........|
+#> | X| 480.55656 | 94.14 | 0.003629 | 0.2692 | 0.8174 |
+#> |.....................| 8.206 | 1.851 | 0.6846 | 0.7733 |
+#> |.....................| 1.465 | 1.218 | 1.353 |...........|
+#> | 43| 480.48642 | 0.9984 | -1.228 | -0.9134 | -0.8925 |
+#> |.....................| -0.8432 | -0.6102 | -0.9761 | -0.9914 |
+#> |.....................| -0.6380 | -0.7463 | -0.6812 |...........|
+#> | U| 480.48642 | 94.05 | -5.643 | -0.9987 | -0.2017 |
+#> |.....................| 2.104 | 1.852 | 0.6850 | 0.7647 |
+#> |.....................| 1.465 | 1.223 | 1.357 |...........|
+#> | X| 480.48642 | 94.05 | 0.003541 | 0.2692 | 0.8174 |
+#> |.....................| 8.202 | 1.852 | 0.6850 | 0.7647 |
+#> |.....................| 1.465 | 1.223 | 1.357 |...........|
+#> | 44| 480.43193 | 0.9946 | -1.325 | -0.9138 | -0.8928 |
+#> |.....................| -0.8452 | -0.6054 | -0.9741 | -1.031 |
+#> |.....................| -0.6354 | -0.7292 | -0.6649 |...........|
+#> | U| 480.43193 | 93.70 | -5.741 | -0.9991 | -0.2020 |
+#> |.....................| 2.102 | 1.856 | 0.6866 | 0.7303 |
+#> |.....................| 1.469 | 1.241 | 1.376 |...........|
+#> | X| 480.43193 | 93.70 | 0.003212 | 0.2691 | 0.8171 |
+#> |.....................| 8.185 | 1.856 | 0.6866 | 0.7303 |
+#> |.....................| 1.469 | 1.241 | 1.376 |...........|
+#> | F| Forward Diff. | -73.68 | 0.5532 | -0.05170 | -0.03792 |
+#> |.....................| -0.2632 | -4.949 | 2.751 | -2.063 |
+#> |.....................| -2.027 | -0.5538 | -1.006 |...........|
+#> | 45| 480.12037 | 0.9986 | -1.465 | -0.9157 | -0.8935 |
+#> |.....................| -0.8478 | -0.6011 | -0.9922 | -1.022 |
+#> |.....................| -0.6184 | -0.7143 | -0.6451 |...........|
+#> | U| 480.12037 | 94.07 | -5.880 | -1.001 | -0.2027 |
+#> |.....................| 2.100 | 1.859 | 0.6728 | 0.7378 |
+#> |.....................| 1.489 | 1.257 | 1.399 |...........|
+#> | X| 480.12037 | 94.07 | 0.002795 | 0.2687 | 0.8166 |
+#> |.....................| 8.164 | 1.859 | 0.6728 | 0.7378 |
+#> |.....................| 1.489 | 1.257 | 1.399 |...........|
+#> | F| Forward Diff. | -14.31 | 0.1919 | -0.006458 | -0.005637 |
+#> |.....................| -0.1500 | -5.088 | 0.6605 | -0.1467 |
+#> |.....................| -1.672 | 0.02074 | -0.4009 |...........|
+#> | 46| 480.21684 | 0.9998 | -1.532 | -0.9143 | -0.8951 |
+#> |.....................| -0.8360 | -0.5884 | -0.9862 | -1.032 |
+#> |.....................| -0.5071 | -0.7680 | -0.6684 |...........|
+#> | U| 480.21684 | 94.19 | -5.947 | -0.9996 | -0.2043 |
+#> |.....................| 2.112 | 1.870 | 0.6773 | 0.7298 |
+#> |.....................| 1.621 | 1.199 | 1.372 |...........|
+#> | X| 480.21684 | 94.19 | 0.002613 | 0.2690 | 0.8152 |
+#> |.....................| 8.261 | 1.870 | 0.6773 | 0.7298 |
+#> |.....................| 1.621 | 1.199 | 1.372 |...........|
+#> | 47| 480.06028 | 1.000 | -1.489 | -0.9152 | -0.8941 |
+#> |.....................| -0.8435 | -0.5961 | -0.9901 | -1.026 |
+#> |.....................| -0.5774 | -0.7340 | -0.6536 |...........|
+#> | U| 480.06028 | 94.21 | -5.905 | -1.000 | -0.2033 |
+#> |.....................| 2.104 | 1.863 | 0.6744 | 0.7349 |
+#> |.....................| 1.538 | 1.236 | 1.389 |...........|
+#> | X| 480.06028 | 94.21 | 0.002726 | 0.2688 | 0.8161 |
+#> |.....................| 8.200 | 1.863 | 0.6744 | 0.7349 |
+#> |.....................| 1.538 | 1.236 | 1.389 |...........|
+#> | F| Forward Diff. | 6.437 | 0.1507 | 0.07551 | -0.008836 |
+#> |.....................| 0.08632 | -3.858 | 0.8547 | 0.1963 |
+#> |.....................| 0.4591 | -0.8475 | -0.5830 |...........|
+#> | 48| 480.03665 | 0.9987 | -1.532 | -0.9229 | -0.8934 |
+#> |.....................| -0.8415 | -0.5884 | -1.015 | -1.029 |
+#> |.....................| -0.5816 | -0.7442 | -0.6445 |...........|
+#> | U| 480.03665 | 94.09 | -5.948 | -1.008 | -0.2026 |
+#> |.....................| 2.106 | 1.870 | 0.6552 | 0.7323 |
+#> |.....................| 1.533 | 1.225 | 1.399 |...........|
+#> | X| 480.03665 | 94.09 | 0.002612 | 0.2673 | 0.8166 |
+#> |.....................| 8.216 | 1.870 | 0.6552 | 0.7323 |
+#> |.....................| 1.533 | 1.225 | 1.399 |...........|
+#> | F| Forward Diff. | -11.33 | 0.04720 | -0.3576 | -0.009993 |
+#> |.....................| 0.09366 | -3.049 | -0.8552 | 2.379 |
+#> |.....................| 0.07272 | -1.673 | -0.4189 |...........|
+#> | 49| 480.00388 | 0.9997 | -1.574 | -0.9191 | -0.8927 |
+#> |.....................| -0.8426 | -0.5789 | -1.009 | -1.024 |
+#> |.....................| -0.5828 | -0.7165 | -0.6339 |...........|
+#> | U| 480.00388 | 94.18 | -5.990 | -1.004 | -0.2019 |
+#> |.....................| 2.105 | 1.878 | 0.6600 | 0.7361 |
+#> |.....................| 1.531 | 1.255 | 1.412 |...........|
+#> | X| 480.00388 | 94.18 | 0.002504 | 0.2681 | 0.8172 |
+#> |.....................| 8.207 | 1.878 | 0.6600 | 0.7361 |
+#> |.....................| 1.531 | 1.255 | 1.412 |...........|
+#> | F| Forward Diff. | 1.604 | -0.07853 | -0.1199 | 0.02191 |
+#> |.....................| 0.1056 | -1.650 | -0.4080 | 0.6580 |
+#> |.....................| 0.2834 | 0.2201 | 0.3460 |...........|
+#> | 50| 480.03472 | 1.000 | -1.551 | -0.8873 | -0.8972 |
+#> |.....................| -0.8660 | -0.5703 | -1.019 | -1.030 |
+#> |.....................| -0.5914 | -0.7201 | -0.6545 |...........|
+#> | U| 480.03472 | 94.21 | -5.967 | -0.9727 | -0.2064 |
+#> |.....................| 2.082 | 1.885 | 0.6528 | 0.7314 |
+#> |.....................| 1.521 | 1.251 | 1.388 |...........|
+#> | X| 480.03472 | 94.21 | 0.002563 | 0.2743 | 0.8135 |
+#> |.....................| 8.017 | 1.885 | 0.6528 | 0.7314 |
+#> |.....................| 1.521 | 1.251 | 1.388 |...........|
+#> | 51| 480.00362 | 0.9987 | -1.569 | -0.9113 | -0.8938 |
+#> |.....................| -0.8484 | -0.5757 | -1.011 | -1.026 |
+#> |.....................| -0.5851 | -0.7175 | -0.6392 |...........|
+#> | U| 480.00362 | 94.09 | -5.984 | -0.9966 | -0.2030 |
+#> |.....................| 2.099 | 1.880 | 0.6585 | 0.7346 |
+#> |.....................| 1.528 | 1.254 | 1.406 |...........|
+#> | X| 480.00362 | 94.09 | 0.002519 | 0.2696 | 0.8163 |
+#> |.....................| 8.160 | 1.880 | 0.6585 | 0.7346 |
+#> |.....................| 1.528 | 1.254 | 1.406 |...........|
+#> | F| Forward Diff. | -11.27 | -0.06004 | 0.2734 | -0.003181 |
+#> |.....................| -0.1459 | -1.804 | -0.6958 | 0.2356 |
+#> |.....................| -0.08489 | -0.1057 | -0.1437 |...........|
+#> | 52| 479.99564 | 1.000 | -1.563 | -0.9133 | -0.8943 |
+#> |.....................| -0.8490 | -0.5744 | -1.010 | -1.027 |
+#> |.....................| -0.5870 | -0.7192 | -0.6381 |...........|
+#> | U| 479.99564 | 94.21 | -5.979 | -0.9986 | -0.2035 |
+#> |.....................| 2.099 | 1.881 | 0.6592 | 0.7342 |
+#> |.....................| 1.526 | 1.252 | 1.407 |...........|
+#> | X| 479.99564 | 94.21 | 0.002532 | 0.2692 | 0.8159 |
+#> |.....................| 8.155 | 1.881 | 0.6592 | 0.7342 |
+#> |.....................| 1.526 | 1.252 | 1.407 |...........|
+#> | F| Forward Diff. | 5.442 | -0.04353 | 0.2015 | -0.005586 |
+#> |.....................| -0.1078 | -1.130 | -0.4765 | -0.6210 |
+#> |.....................| 0.09560 | 0.04932 | 0.1423 |...........|
+#> | 53| 479.99256 | 0.9995 | -1.560 | -0.9178 | -0.8945 |
+#> |.....................| -0.8473 | -0.5732 | -1.008 | -1.026 |
+#> |.....................| -0.5881 | -0.7196 | -0.6366 |...........|
+#> | U| 479.99256 | 94.16 | -5.975 | -1.003 | -0.2037 |
+#> |.....................| 2.100 | 1.882 | 0.6609 | 0.7344 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99256 | 94.16 | 0.002541 | 0.2683 | 0.8157 |
+#> |.....................| 8.169 | 1.882 | 0.6609 | 0.7344 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | F| Forward Diff. | -1.663 | -0.03616 | -0.04918 | -0.01811 |
+#> |.....................| -0.07323 | -1.616 | -0.5475 | -0.9126 |
+#> |.....................| -0.2713 | -0.2260 | -0.04317 |...........|
+#> | 54| 479.99337 | 0.9995 | -1.558 | -0.9178 | -0.8940 |
+#> |.....................| -0.8453 | -0.5718 | -1.004 | -1.025 |
+#> |.....................| -0.5887 | -0.7198 | -0.6325 |...........|
+#> | U| 479.99337 | 94.16 | -5.974 | -1.003 | -0.2032 |
+#> |.....................| 2.102 | 1.883 | 0.6641 | 0.7358 |
+#> |.....................| 1.524 | 1.251 | 1.413 |...........|
+#> | X| 479.99337 | 94.16 | 0.002545 | 0.2683 | 0.8161 |
+#> |.....................| 8.185 | 1.883 | 0.6641 | 0.7358 |
+#> |.....................| 1.524 | 1.251 | 1.413 |...........|
+#> | 55| 479.99257 | 0.9996 | -1.559 | -0.9178 | -0.8942 |
+#> |.....................| -0.8464 | -0.5725 | -1.006 | -1.026 |
+#> |.....................| -0.5884 | -0.7197 | -0.6348 |...........|
+#> | U| 479.99257 | 94.17 | -5.975 | -1.003 | -0.2035 |
+#> |.....................| 2.101 | 1.883 | 0.6623 | 0.7351 |
+#> |.....................| 1.525 | 1.252 | 1.411 |...........|
+#> | X| 479.99257 | 94.17 | 0.002543 | 0.2683 | 0.8159 |
+#> |.....................| 8.175 | 1.883 | 0.6623 | 0.7351 |
+#> |.....................| 1.525 | 1.252 | 1.411 |...........|
+#> | 56| 479.99255 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99255 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99255 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | C| Central Diff. | 1.014 | -0.03924 | -0.07311 | -0.03520 |
+#> |.....................| -0.07193 | -1.047 | -0.3482 | -0.6653 |
+#> |.....................| -0.001386 | 0.002313 | -0.01832 |...........|
+#> | 57| 479.99382 | 0.9993 | -1.559 | -0.9177 | -0.8943 |
+#> |.....................| -0.8469 | -0.5723 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99382 | 94.14 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6617 | 0.7350 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99382 | 94.14 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6617 | 0.7350 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 58| 479.99260 | 0.9996 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5726 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.9926 | 94.17 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.9926 | 94.17 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 59| 479.99255 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99255 | 94.17 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99255 | 94.17 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 60| 479.99254 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99254 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99254 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | C| Central Diff. | 0.7083 | -0.03937 | -0.07377 | -0.03537 |
+#> |.....................| -0.07427 | -1.038 | -0.3482 | -0.6698 |
+#> |.....................| -0.009774 | 0.01032 | -0.01719 |...........|
+#> | 61| 479.99255 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99255 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99255 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 62| 479.99264 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99264 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99264 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 63| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 64| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 65| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 66| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 67| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 68| 479.99259 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99259 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99259 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 69| 479.99258 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99258 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99258 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 70| 479.99258 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99258 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99258 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | 71| 479.99258 | 0.9997 | -1.559 | -0.9178 | -0.8944 |
+#> |.....................| -0.8469 | -0.5727 | -1.007 | -1.026 |
+#> |.....................| -0.5882 | -0.7196 | -0.6358 |...........|
+#> | U| 479.99258 | 94.18 | -5.975 | -1.003 | -0.2036 |
+#> |.....................| 2.101 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> | X| 479.99258 | 94.18 | 0.002542 | 0.2683 | 0.8158 |
+#> |.....................| 8.172 | 1.883 | 0.6616 | 0.7348 |
+#> |.....................| 1.525 | 1.252 | 1.409 |...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_k1 |
+#> |.....................| log_k2 | g_qlogis | sigma | o1 |
+#> |.....................| o2 | o3 | o4 | o5 |
+#> |.....................| o6 |...........|...........|...........|
+#> | 1| 514.27068 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 514.27068 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 514.27068 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | G| Gill Diff. | 26.19 | 1.724 | -0.1273 | 0.01210 |
+#> |.....................| -0.2599 | 0.04964 | -46.10 | 17.02 |
+#> |.....................| 9.682 | -11.00 | -4.182 | 3.869 |
+#> |.....................| -10.57 |...........|...........|...........|
+#> | 2| 1072.3430 | 0.5548 | -1.029 | -0.9091 | -0.9298 |
+#> |.....................| -0.9733 | -0.8898 | -0.07504 | -1.166 |
+#> |.....................| -1.039 | -0.6809 | -0.8005 | -0.9394 |
+#> |.....................| -0.6887 |...........|...........|...........|
+#> | U| 1072.343 | 52.05 | -5.403 | -0.9690 | -1.880 |
+#> |.....................| -4.266 | 0.1355 | 2.292 | 0.5199 |
+#> |.....................| 0.7209 | 1.403 | 1.065 | 0.8339 |
+#> |.....................| 1.368 |...........|...........|...........|
+#> | X| 1072.343 | 52.05 | 0.004504 | 0.2751 | 0.1526 |
+#> |.....................| 0.01403 | 0.5338 | 2.292 | 0.5199 |
+#> |.....................| 0.7209 | 1.403 | 1.065 | 0.8339 |
+#> |.....................| 1.368 |...........|...........|...........|
+#> | 3| 539.25377 | 0.9555 | -1.003 | -0.9110 | -0.9296 |
+#> |.....................| -0.9773 | -0.8890 | -0.7801 | -0.9058 |
+#> |.....................| -0.8907 | -0.8491 | -0.8645 | -0.8802 |
+#> |.....................| -0.8503 |...........|...........|...........|
+#> | U| 539.25377 | 89.63 | -5.376 | -0.9709 | -1.880 |
+#> |.....................| -4.270 | 0.1356 | 1.712 | 0.7103 |
+#> |.....................| 0.8487 | 1.204 | 1.001 | 0.8867 |
+#> |.....................| 1.181 |...........|...........|...........|
+#> | X| 539.25377 | 89.63 | 0.004625 | 0.2747 | 0.1526 |
+#> |.....................| 0.01398 | 0.5339 | 1.712 | 0.7103 |
+#> |.....................| 0.8487 | 1.204 | 1.001 | 0.8867 |
+#> |.....................| 1.181 |...........|...........|...........|
+#> | 4| 527.20532 | 0.9955 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9777 | -0.8889 | -0.8506 | -0.8798 |
+#> |.....................| -0.8759 | -0.8659 | -0.8709 | -0.8743 |
+#> |.....................| -0.8665 |...........|...........|...........|
+#> | U| 527.20532 | 93.39 | -5.374 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.654 | 0.7293 |
+#> |.....................| 0.8615 | 1.184 | 0.9947 | 0.8920 |
+#> |.....................| 1.162 |...........|...........|...........|
+#> | X| 527.20532 | 93.39 | 0.004637 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.654 | 0.7293 |
+#> |.....................| 0.8615 | 1.184 | 0.9947 | 0.8920 |
+#> |.....................| 1.162 |...........|...........|...........|
+#> | 5| 527.55150 | 0.9996 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8576 | -0.8772 |
+#> |.....................| -0.8744 | -0.8676 | -0.8715 | -0.8737 |
+#> |.....................| -0.8681 |...........|...........|...........|
+#> | U| 527.5515 | 93.77 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.648 | 0.7312 |
+#> |.....................| 0.8628 | 1.182 | 0.9941 | 0.8925 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.5515 | 93.77 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.648 | 0.7312 |
+#> |.....................| 0.8628 | 1.182 | 0.9941 | 0.8925 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 6| 527.60332 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8743 | -0.8678 | -0.8716 | -0.8737 |
+#> |.....................| -0.8682 |...........|...........|...........|
+#> | U| 527.60332 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60332 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 7| 527.60868 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60868 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60868 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 8| 527.60932 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60932 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60932 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 9| 527.60939 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60939 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60939 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 10| 527.60940 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.6094 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.6094 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 11| 527.60940 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.6094 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.6094 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 12| 527.60940 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.6094 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.6094 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 13| 527.60941 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60941 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60941 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 14| 527.60941 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60941 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60941 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 15| 527.60941 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60941 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60941 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 16| 527.60941 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60941 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60941 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | 17| 527.60941 | 1.000 | -1.000 | -0.9112 | -0.9296 |
+#> |.....................| -0.9778 | -0.8889 | -0.8584 | -0.8769 |
+#> |.....................| -0.8742 | -0.8678 | -0.8716 | -0.8736 |
+#> |.....................| -0.8683 |...........|...........|...........|
+#> | U| 527.60941 | 93.81 | -5.373 | -0.9711 | -1.880 |
+#> |.....................| -4.271 | 0.1356 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> | X| 527.60941 | 93.81 | 0.004638 | 0.2747 | 0.1526 |
+#> |.....................| 0.01397 | 0.5339 | 1.647 | 0.7314 |
+#> |.....................| 0.8629 | 1.182 | 0.9940 | 0.8926 |
+#> |.....................| 1.160 |...........|...........|...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.288 0.09 1.379
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[5]+THETA[5];
-#> rx_expr_12~exp(-(rx_expr_8));
-#> rx_expr_14~t*rx_expr_12;
-#> rx_expr_15~1+rx_expr_14;
-#> rx_expr_17~rx_expr_7-(rx_expr_8);
-#> rx_expr_19~exp(rx_expr_17);
-#> d/dt(parent)=-rx_expr_19*parent/(rx_expr_15);
-#> rx_expr_9~ETA[2]+THETA[2];
-#> rx_expr_11~exp(rx_expr_9);
-#> d/dt(A1)=-rx_expr_11*A1+rx_expr_19*parent*f_parent_to_A1/(rx_expr_15);
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_13~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_13+rx_expr_3;
-#> rx_hi_~rx_expr_13+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_10~parent*(rx_expr_2);
-#> rx_expr_16~rx_expr_10*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1);
-#> rx_r_=(rx_expr_0)*Rx_pow_di(THETA[7],2)+(rx_expr_2)*(rx_expr_1)*Rx_pow_di(THETA[6],2);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_alpha=THETA[4];
-#> log_beta=THETA[5];
-#> sigma_parent=THETA[6];
-#> sigma_A1=THETA[7];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_alpha=ETA[4];
-#> eta.log_beta=ETA[5];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_11;
-#> alpha=exp(rx_expr_7);
-#> beta=exp(rx_expr_8);
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.666 0.38 7.044
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.39 0.093 1.483
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[6]+THETA[6];
-#> rx_expr_9~ETA[5]+THETA[5];
-#> rx_expr_12~exp(rx_expr_7);
-#> rx_expr_13~exp(rx_expr_9);
-#> rx_expr_15~t*rx_expr_12;
-#> rx_expr_16~t*rx_expr_13;
-#> rx_expr_17~exp(-(rx_expr_8));
-#> rx_expr_19~1+rx_expr_17;
-#> rx_expr_24~1/(rx_expr_19);
-#> rx_expr_26~(rx_expr_24);
-#> rx_expr_27~1-rx_expr_26;
-#> d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));
-#> rx_expr_10~ETA[2]+THETA[2];
-#> rx_expr_14~exp(rx_expr_10);
-#> d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_18~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_18+rx_expr_3;
-#> rx_hi_~rx_expr_18+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_11~parent*(rx_expr_2);
-#> rx_expr_22~rx_expr_11*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1);
-#> rx_r_=(rx_expr_0)*Rx_pow_di(THETA[8],2)+(rx_expr_2)*(rx_expr_1)*Rx_pow_di(THETA[7],2);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_k1=THETA[4];
-#> log_k2=THETA[5];
-#> g_qlogis=THETA[6];
-#> sigma_parent=THETA[7];
-#> sigma_A1=THETA[8];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_k1=ETA[4];
-#> eta.log_k2=ETA[5];
-#> eta.g_qlogis=ETA[6];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_14;
-#> k1=rx_expr_12;
-#> k2=rx_expr_13;
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> g=1/(rx_expr_19);
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.67 0.529 15.2
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.6104 -5.6552 -0.1308 2.1755 -1.1174 2.9315 1.6064 0.6616 0.5897 0.4753 9.7765 10.2253
+#> 2: 93.8838 -5.6936 -0.1062 2.2361 -1.0529 2.7849 1.5260 0.6285 0.5602 0.4515 7.9206 5.2721
+#> 3: 93.9304 -5.7260 -0.0940 2.2480 -1.0317 2.6457 1.4889 0.5971 0.5322 0.4290 7.5051 3.6573
+#> 4: 93.6107 -5.7914 -0.0929 2.2382 -1.0171 2.5134 2.0027 0.5676 0.5056 0.4075 7.3763 3.1438
+#> 5: 93.7262 -5.7517 -0.0926 2.2365 -1.0306 2.3877 1.9026 0.5679 0.4803 0.3871 7.2914 3.0275
+#> 6: 93.7261 -5.7719 -0.0823 2.2625 -1.0391 2.2683 2.1168 0.5638 0.4563 0.3678 7.0857 2.8196
+#> 7: 93.5991 -5.8553 -0.0917 2.2659 -1.0146 2.1549 2.3708 0.5618 0.4335 0.3494 6.9413 2.7447
+#> 8: 93.4288 -5.8969 -0.0885 2.2757 -1.0253 2.1183 2.4324 0.5615 0.4118 0.3319 7.2269 2.6781
+#> 9: 93.4049 -6.1188 -0.0863 2.2841 -1.0154 2.0124 3.0090 0.5633 0.3912 0.3153 7.2084 2.7464
+#> 10: 93.4773 -6.1940 -0.0816 2.2893 -1.0174 1.9958 3.6308 0.5540 0.3716 0.2996 7.2414 2.8980
+#> 11: 93.5334 -6.1739 -0.0772 2.2901 -1.0479 2.2841 3.4492 0.5567 0.3531 0.2846 7.0567 2.8159
+#> 12: 93.5824 -6.3716 -0.0875 2.2706 -1.0452 2.1699 4.3087 0.5505 0.3354 0.2704 7.2970 2.3790
+#> 13: 93.8528 -6.3302 -0.0846 2.2564 -1.0302 2.0614 4.6014 0.5475 0.3186 0.2568 7.3901 2.1942
+#> 14: 94.0343 -6.1408 -0.0887 2.2666 -1.0280 1.9995 4.3714 0.5202 0.3027 0.2440 7.1696 2.0730
+#> 15: 94.1712 -6.3900 -0.0759 2.2825 -1.0112 1.8995 5.0913 0.5358 0.2876 0.2318 7.2155 2.0259
+#> 16: 93.9481 -6.1284 -0.0798 2.2707 -1.0264 1.8046 4.8368 0.5501 0.2732 0.2202 7.2731 2.0912
+#> 17: 93.7828 -6.2736 -0.0852 2.2870 -1.0249 1.7143 4.5949 0.5408 0.2595 0.2092 7.0213 2.0417
+#> 18: 93.8758 -6.3616 -0.0851 2.2713 -1.0157 1.8699 4.9132 0.5349 0.2465 0.1987 7.0613 1.8601
+#> 19: 93.7565 -6.5413 -0.0866 2.2695 -1.0166 2.5251 5.9754 0.5312 0.2547 0.1888 7.2555 1.7947
+#> 20: 93.7233 -6.3942 -0.0970 2.2620 -1.0195 2.3989 5.6766 0.5484 0.2576 0.1794 7.0292 1.8687
+#> 21: 93.8298 -6.2619 -0.0974 2.2570 -1.0118 2.2789 5.3928 0.5497 0.2545 0.1704 6.7138 1.8157
+#> 22: 93.9520 -6.1633 -0.0874 2.2777 -1.0274 2.1650 5.1232 0.5437 0.2641 0.1622 6.8254 1.8443
+#> 23: 93.8442 -6.3255 -0.0855 2.2568 -1.0151 2.1243 4.9615 0.5334 0.2885 0.1556 6.8049 1.8073
+#> 24: 93.9659 -6.5470 -0.0855 2.2572 -1.0178 2.0788 6.2156 0.5425 0.2834 0.1583 6.9598 1.8686
+#> 25: 94.3004 -6.4881 -0.0920 2.2371 -1.0187 3.2507 5.9048 0.5367 0.2872 0.1609 6.8709 1.8839
+#> 26: 94.1750 -6.4437 -0.0964 2.2337 -1.0301 3.1136 5.6096 0.5307 0.2820 0.1611 6.5948 1.8742
+#> 27: 94.6007 -6.3072 -0.0750 2.2936 -1.0343 3.9844 5.3291 0.5042 0.2679 0.1695 6.7524 1.8335
+#> 28: 94.4915 -6.1389 -0.0826 2.2730 -1.0223 3.7852 5.0626 0.4998 0.2590 0.1812 6.4646 1.8937
+#> 29: 94.1900 -6.1516 -0.0836 2.2680 -1.0287 3.7861 4.8095 0.4976 0.2612 0.1875 6.4674 1.8998
+#> 30: 94.6632 -6.0574 -0.0773 2.2637 -1.0280 3.5968 4.5690 0.4948 0.2525 0.2040 6.5945 1.9022
+#> 31: 94.3460 -6.1684 -0.0761 2.2677 -1.0276 3.4170 4.3406 0.4901 0.2690 0.2038 6.9918 1.8446
+#> 32: 94.4385 -5.9347 -0.0751 2.2893 -1.0146 3.3283 4.1235 0.4882 0.2576 0.2002 6.7622 1.7754
+#> 33: 94.7021 -5.9329 -0.0787 2.2987 -1.0108 3.3485 3.9174 0.4859 0.2640 0.1941 6.9648 1.8014
+#> 34: 94.4058 -6.0311 -0.0692 2.2980 -1.0125 3.1811 3.7215 0.4994 0.2676 0.1936 6.9791 1.7561
+#> 35: 94.4503 -6.0470 -0.0692 2.2950 -1.0100 3.5600 3.7611 0.4994 0.2637 0.1928 6.8010 1.7890
+#> 36: 94.3400 -6.0339 -0.0792 2.2960 -1.0204 3.3820 3.5731 0.4822 0.2638 0.1887 6.6462 1.6763
+#> 37: 94.1497 -6.0221 -0.0879 2.2653 -1.0073 3.2129 3.3944 0.4979 0.2506 0.1793 6.4853 1.7911
+#> 38: 94.1574 -5.8638 -0.0884 2.2752 -1.0156 3.0523 3.2247 0.4992 0.2435 0.1772 6.4329 1.7707
+#> 39: 94.1680 -5.9558 -0.0948 2.2535 -1.0205 2.8997 3.0635 0.5065 0.2448 0.1819 6.4462 1.8100
+#> 40: 94.0516 -6.0814 -0.0881 2.2531 -1.0356 2.7547 3.4976 0.4949 0.2515 0.1827 6.4734 1.8133
+#> 41: 94.1522 -6.1880 -0.0849 2.2618 -1.0230 2.6170 4.1610 0.5129 0.2389 0.1797 6.4165 1.7782
+#> 42: 94.2178 -6.1829 -0.0854 2.2791 -1.0325 2.8092 4.1174 0.5052 0.2288 0.1853 6.4332 1.7883
+#> 43: 93.9083 -6.1600 -0.0831 2.2860 -1.0350 2.9631 3.9116 0.4914 0.2310 0.1826 6.4865 1.8449
+#> 44: 93.9636 -6.1494 -0.0824 2.2903 -1.0150 2.8149 3.7221 0.4921 0.2214 0.1805 6.4818 1.9385
+#> 45: 93.9937 -6.2329 -0.0895 2.2832 -1.0157 4.2815 4.5622 0.5075 0.2250 0.1796 6.4098 1.8355
+#> 46: 93.8001 -6.1784 -0.0944 2.2664 -1.0212 4.0674 4.3341 0.5023 0.2274 0.1795 6.5539 1.7875
+#> 47: 93.8997 -6.3400 -0.0945 2.2627 -1.0183 3.8641 4.9860 0.5017 0.2312 0.1834 6.5497 1.7838
+#> 48: 93.7861 -6.3496 -0.0944 2.2713 -1.0255 3.6709 5.3403 0.5025 0.2197 0.1839 6.1766 1.9080
+#> 49: 93.7128 -6.3914 -0.0944 2.2752 -1.0137 3.4873 5.6007 0.5051 0.2198 0.1788 6.3050 1.8320
+#> 50: 94.1645 -6.3056 -0.0945 2.2755 -1.0062 3.3130 5.3207 0.4998 0.2176 0.1781 6.4998 1.8516
+#> 51: 93.9897 -6.1556 -0.1026 2.2633 -1.0097 3.1473 5.0547 0.4853 0.2439 0.1796 6.3184 1.7981
+#> 52: 93.7604 -6.2264 -0.1068 2.2485 -0.9936 2.9899 4.8209 0.4887 0.2542 0.1793 6.5076 1.7916
+#> 53: 93.8821 -6.5447 -0.1049 2.2546 -1.0020 2.8404 6.5603 0.4701 0.2556 0.1789 6.5735 1.7763
+#> 54: 93.8865 -6.4028 -0.1081 2.2507 -1.0162 2.6984 6.2323 0.4724 0.2576 0.1846 6.3607 1.8295
+#> 55: 94.0120 -6.5455 -0.0986 2.2728 -1.0119 2.5635 6.3983 0.4550 0.2686 0.1773 6.6815 1.7869
+#> 56: 94.1921 -6.6581 -0.0953 2.2713 -1.0151 2.4353 8.2169 0.4478 0.2675 0.1763 6.6257 1.7873
+#> 57: 93.8812 -6.4499 -0.1081 2.2447 -1.0182 2.3136 7.8060 0.4683 0.2562 0.1804 6.2421 1.8455
+#> 58: 93.9830 -6.5112 -0.1092 2.2436 -1.0136 2.1979 7.4157 0.4695 0.2569 0.1762 6.3196 1.8224
+#> 59: 93.8537 -6.6528 -0.1105 2.2390 -1.0089 2.0880 9.0039 0.4689 0.2534 0.1692 6.3735 1.8049
+#> 60: 93.7399 -6.4780 -0.1212 2.2263 -0.9979 1.9836 8.5537 0.4565 0.2445 0.1696 6.4748 1.8439
+#> 61: 93.8180 -6.4608 -0.1243 2.2275 -1.0039 1.8844 8.1260 0.4630 0.2414 0.1693 6.3936 1.7653
+#> 62: 93.5774 -6.3127 -0.1298 2.2250 -1.0022 1.7902 7.7197 0.4711 0.2452 0.1708 6.5708 1.8014
+#> 63: 93.5731 -6.2060 -0.1327 2.2213 -1.0031 1.7007 7.3337 0.4685 0.2426 0.1712 6.4933 1.8318
+#> 64: 93.3587 -6.2299 -0.1316 2.2290 -1.0004 1.6302 6.9671 0.4694 0.2460 0.1710 6.2584 1.8361
+#> 65: 93.2982 -6.1900 -0.1354 2.2341 -0.9963 1.5487 6.6187 0.4685 0.2482 0.1750 6.0950 1.8341
+#> 66: 93.4532 -6.2107 -0.1251 2.2254 -0.9786 1.4713 6.2878 0.4822 0.2489 0.1701 6.3732 1.7951
+#> 67: 93.5878 -6.1823 -0.1208 2.2455 -0.9766 1.3977 5.9734 0.4860 0.2407 0.1668 6.4456 1.8371
+#> 68: 93.5819 -5.9209 -0.1200 2.2599 -0.9792 1.3278 5.6747 0.4793 0.2412 0.1686 6.5728 1.8144
+#> 69: 93.4002 -6.1142 -0.1242 2.2542 -0.9878 1.4433 5.3910 0.4730 0.2511 0.1830 6.3888 1.7900
+#> 70: 93.2631 -6.1875 -0.1271 2.2639 -0.9844 1.5244 5.1214 0.4711 0.2444 0.1770 6.5093 1.7117
+#> 71: 93.2629 -6.2944 -0.1275 2.2418 -0.9805 1.4481 4.8654 0.4612 0.2522 0.1748 6.4659 1.8500
+#> 72: 93.0324 -6.2727 -0.1332 2.2421 -0.9766 1.3757 5.1467 0.4519 0.2524 0.1673 6.3452 1.8054
+#> 73: 93.0174 -6.4402 -0.1391 2.2320 -0.9795 1.3069 6.1963 0.4480 0.2563 0.1637 6.3915 1.8506
+#> 74: 93.0073 -6.4286 -0.1450 2.2241 -0.9962 1.2416 6.0011 0.4510 0.2461 0.1682 6.6924 1.8302
+#> 75: 93.2607 -6.5056 -0.1379 2.2233 -0.9926 1.1795 6.0508 0.4573 0.2540 0.1669 6.4813 1.7896
+#> 76: 93.2937 -6.1637 -0.1404 2.2228 -0.9970 1.1205 5.7483 0.4588 0.2529 0.1656 6.3781 1.7976
+#> 77: 93.2223 -6.1702 -0.1381 2.2200 -0.9858 1.4369 5.4609 0.4633 0.2585 0.1697 6.3510 1.8749
+#> 78: 93.3189 -6.1924 -0.1355 2.2238 -0.9944 1.3651 5.1878 0.4608 0.2631 0.1612 6.1888 1.7669
+#> 79: 93.2417 -6.6345 -0.1335 2.2340 -0.9865 1.2968 7.3486 0.4570 0.2564 0.1532 6.0902 1.7505
+#> 80: 93.3476 -6.3069 -0.1305 2.2319 -0.9880 1.6281 6.9812 0.4649 0.2525 0.1514 6.0659 1.7582
+#> 81: 93.4798 -6.3145 -0.1253 2.2468 -0.9989 1.9108 6.6321 0.4447 0.2583 0.1579 6.0843 1.7959
+#> 82: 93.2745 -6.2461 -0.1184 2.2529 -0.9937 1.8153 6.3005 0.4439 0.2602 0.1691 6.2826 1.7896
+#> 83: 93.4628 -6.3953 -0.1189 2.2640 -0.9880 1.7245 6.1094 0.4430 0.2612 0.1709 6.4474 1.6820
+#> 84: 93.3664 -6.2885 -0.1105 2.2675 -0.9875 1.6383 6.1170 0.4498 0.2689 0.1719 6.4847 1.6731
+#> 85: 93.5090 -6.3029 -0.1095 2.2709 -0.9898 1.6666 6.1406 0.4365 0.2693 0.1710 6.2452 1.6594
+#> 86: 93.5097 -6.2256 -0.1106 2.2701 -0.9928 1.5833 6.2468 0.4365 0.2749 0.1632 6.2007 1.7178
+#> 87: 93.5165 -6.3038 -0.1046 2.2731 -0.9877 1.5041 5.9345 0.4398 0.2667 0.1603 6.3928 1.7003
+#> 88: 93.3766 -6.2723 -0.1071 2.2771 -0.9881 1.4289 5.6378 0.4241 0.2538 0.1598 6.1043 1.6772
+#> 89: 93.4448 -6.0430 -0.1102 2.2781 -0.9725 1.3575 5.3559 0.4187 0.2915 0.1518 6.0153 1.7593
+#> 90: 93.2843 -6.1065 -0.1089 2.2866 -0.9705 1.5362 5.0881 0.4203 0.2844 0.1656 5.9235 1.6631
+#> 91: 93.4159 -6.0210 -0.1095 2.2879 -0.9798 2.1371 4.8337 0.4245 0.2857 0.1573 5.9182 1.7482
+#> 92: 93.3198 -6.2526 -0.1075 2.2919 -0.9791 2.0303 4.7352 0.4159 0.2918 0.1590 6.0853 1.6755
+#> 93: 93.3269 -6.1838 -0.1173 2.2809 -0.9999 1.9287 4.4985 0.4211 0.2893 0.1684 6.1189 1.6734
+#> 94: 93.2077 -6.1086 -0.1148 2.2890 -0.9918 2.1061 4.2736 0.4230 0.2802 0.1662 5.9328 1.7116
+#> 95: 93.0207 -6.1510 -0.1170 2.2665 -0.9791 2.1360 4.0630 0.4199 0.2937 0.1734 6.1415 1.6737
+#> 96: 93.2134 -6.1614 -0.1152 2.2861 -0.9711 2.5372 4.1579 0.4211 0.2790 0.1647 6.1575 1.6338
+#> 97: 93.1425 -6.2333 -0.1140 2.2912 -0.9665 2.4103 4.4551 0.4136 0.2835 0.1645 6.0790 1.6652
+#> 98: 92.9412 -6.2651 -0.1167 2.2847 -0.9738 2.2898 4.7233 0.4095 0.2882 0.1836 5.9305 1.6158
+#> 99: 92.9087 -6.1870 -0.1177 2.2833 -0.9744 2.1753 4.4872 0.4142 0.2913 0.1876 5.9838 1.7003
+#> 100: 92.7788 -6.2113 -0.1146 2.2928 -0.9939 2.0665 4.4195 0.4109 0.2945 0.1866 6.0195 1.7275
+#> 101: 92.8783 -6.0718 -0.1080 2.2959 -0.9968 1.9632 4.1985 0.4142 0.2966 0.1778 6.2542 1.6844
+#> 102: 93.0451 -6.3706 -0.1086 2.2894 -0.9974 1.8650 5.2121 0.4135 0.3030 0.1769 6.2204 1.6281
+#> 103: 93.2901 -6.4069 -0.1066 2.2943 -0.9896 1.7718 5.7453 0.4152 0.2879 0.1818 6.0239 1.7299
+#> 104: 93.3437 -6.3694 -0.1063 2.2769 -0.9914 1.6832 5.8903 0.4210 0.2884 0.1855 6.1116 1.7415
+#> 105: 93.4609 -6.2767 -0.1060 2.2751 -1.0157 1.5990 5.5958 0.4214 0.2865 0.1841 6.1287 1.7322
+#> 106: 93.5833 -6.2340 -0.1006 2.2879 -1.0084 1.8669 5.3160 0.4272 0.2982 0.1829 6.0211 1.6726
+#> 107: 93.7800 -6.1505 -0.0948 2.2685 -1.0219 1.7735 5.0502 0.4325 0.2841 0.1753 5.8556 1.7636
+#> 108: 93.8532 -6.3744 -0.0938 2.2650 -1.0210 2.0297 5.7080 0.4307 0.2836 0.1701 6.0669 1.6804
+#> 109: 93.8994 -6.3544 -0.0829 2.2862 -1.0287 1.9282 5.4226 0.4184 0.3113 0.1789 6.2343 1.6667
+#> 110: 94.0150 -6.5609 -0.0905 2.2821 -1.0088 2.1118 6.8121 0.4276 0.3275 0.1845 6.1640 1.6706
+#> 111: 93.7887 -6.0185 -0.0925 2.2831 -1.0097 2.0062 6.4715 0.4209 0.3255 0.1852 6.2823 1.6301
+#> 112: 93.9709 -6.0918 -0.0934 2.2857 -1.0067 2.2032 6.1479 0.4207 0.3285 0.1817 6.1718 1.6494
+#> 113: 93.8761 -6.3434 -0.0955 2.2919 -1.0223 2.5209 5.8405 0.4259 0.3293 0.1842 6.0377 1.6431
+#> 114: 93.6959 -6.2312 -0.0934 2.2782 -1.0154 2.3949 5.5485 0.4237 0.3460 0.1814 6.2225 1.6229
+#> 115: 93.5487 -6.0915 -0.0971 2.2836 -1.0083 2.2751 5.2711 0.4199 0.3557 0.1783 6.5929 1.6479
+#> 116: 93.5953 -6.1479 -0.1013 2.2760 -1.0018 2.1614 5.0075 0.4163 0.3399 0.1794 6.1822 1.6222
+#> 117: 93.3508 -6.1730 -0.1076 2.2632 -0.9953 2.0533 4.7571 0.4057 0.3303 0.1803 6.3444 1.7106
+#> 118: 93.4462 -5.9724 -0.1177 2.2557 -0.9963 2.0318 4.5193 0.3956 0.3349 0.1920 6.0439 1.7146
+#> 119: 93.5841 -6.0400 -0.1151 2.2480 -1.0035 1.9956 4.2933 0.3968 0.3448 0.1929 6.0754 1.6750
+#> 120: 93.4891 -6.0937 -0.1175 2.2499 -1.0006 1.8958 4.0786 0.3927 0.3392 0.1927 6.1654 1.6495
+#> 121: 93.4611 -6.1371 -0.1217 2.2538 -1.0067 1.8011 3.8747 0.3864 0.3549 0.1851 5.9558 1.6940
+#> 122: 93.4636 -6.1015 -0.1243 2.2564 -1.0002 1.7414 3.6810 0.3840 0.3557 0.1860 6.0583 1.6629
+#> 123: 93.2988 -5.9318 -0.1243 2.2601 -0.9989 2.2063 3.4969 0.3840 0.3543 0.1833 5.9686 1.5966
+#> 124: 93.4200 -5.9847 -0.1231 2.2594 -0.9991 2.0959 3.3221 0.3846 0.3544 0.1787 6.1292 1.5957
+#> 125: 93.3727 -6.1217 -0.1239 2.2584 -1.0082 1.9911 3.6395 0.3838 0.3577 0.1782 6.2794 1.6262
+#> 126: 93.4956 -6.0529 -0.1244 2.2482 -1.0096 1.8916 3.4576 0.3847 0.3505 0.1753 6.1181 1.6347
+#> 127: 93.6265 -5.9360 -0.1298 2.2342 -1.0075 1.7970 3.2847 0.3887 0.3367 0.1691 6.2315 1.7051
+#> 128: 93.4446 -6.0523 -0.1337 2.2453 -1.0079 1.7072 3.1205 0.3840 0.3302 0.1759 6.2082 1.6705
+#> 129: 93.4470 -6.0065 -0.1321 2.2321 -1.0015 1.6636 2.9644 0.3853 0.3303 0.1671 6.1479 1.6733
+#> 130: 93.3205 -5.9628 -0.1290 2.2252 -0.9954 2.0336 2.9210 0.3879 0.3284 0.1634 6.0582 1.6372
+#> 131: 93.3836 -5.8919 -0.1358 2.2375 -0.9930 2.1392 2.7749 0.3801 0.3202 0.1644 5.9972 1.6837
+#> 132: 93.1041 -5.9265 -0.1203 2.2552 -0.9929 2.0323 2.8741 0.3831 0.3353 0.1755 6.0648 1.5934
+#> 133: 93.1617 -6.0668 -0.1175 2.2538 -0.9963 1.9306 3.6825 0.3846 0.3187 0.1790 6.0732 1.5684
+#> 134: 93.1503 -6.1208 -0.1232 2.2644 -0.9851 2.3429 3.8026 0.3788 0.3296 0.1737 5.8807 1.5722
+#> 135: 92.8629 -5.9726 -0.1197 2.2650 -0.9761 2.2257 3.6124 0.3802 0.3407 0.1765 5.8408 1.5446
+#> 136: 93.1460 -6.0654 -0.1227 2.2661 -0.9736 2.1144 3.4583 0.3770 0.3434 0.1700 5.7690 1.5561
+#> 137: 93.1243 -6.2350 -0.1274 2.2472 -0.9811 2.0087 4.3526 0.3733 0.3670 0.1615 5.9377 1.5224
+#> 138: 93.1203 -6.1704 -0.1283 2.2472 -0.9891 1.9083 4.1557 0.3788 0.3671 0.1641 5.8765 1.5525
+#> 139: 93.2841 -6.0586 -0.1366 2.2404 -0.9894 1.8129 4.3184 0.3718 0.3693 0.1630 6.1854 1.6388
+#> 140: 93.4239 -6.2398 -0.1382 2.2459 -0.9713 1.7241 4.5903 0.3713 0.3627 0.1548 6.0737 1.5826
+#> 141: 93.4149 -6.1972 -0.1388 2.2605 -0.9686 2.2179 4.5557 0.3701 0.3675 0.1486 6.0793 1.5603
+#> 142: 93.4404 -5.8955 -0.1203 2.2682 -0.9706 2.1070 4.3279 0.3830 0.3719 0.1581 5.9534 1.6189
+#> 143: 93.3108 -5.8069 -0.1142 2.2835 -0.9672 2.0194 4.1115 0.3787 0.3924 0.1592 5.9410 1.5521
+#> 144: 93.3953 -5.7456 -0.1154 2.2891 -0.9553 2.2741 3.9059 0.3787 0.3849 0.1633 6.0163 1.5640
+#> 145: 93.3322 -5.8301 -0.1100 2.2926 -0.9595 2.1604 3.7106 0.3687 0.3754 0.1657 5.8968 1.5844
+#> 146: 93.0844 -5.8926 -0.1084 2.2870 -0.9605 2.0524 3.5251 0.3649 0.3713 0.1646 6.1960 1.5691
+#> 147: 93.2106 -6.0084 -0.1074 2.2931 -0.9654 1.9498 3.5341 0.3646 0.3669 0.1641 6.0548 1.5230
+#> 148: 93.2005 -6.1989 -0.1065 2.2924 -0.9740 1.8523 4.4855 0.3631 0.3660 0.1759 5.9600 1.5194
+#> 149: 93.0788 -6.2470 -0.1108 2.2861 -0.9836 2.1348 4.7630 0.3597 0.3815 0.1815 5.9584 1.5227
+#> 150: 93.2241 -6.2660 -0.1126 2.2847 -0.9912 2.1149 5.0574 0.3656 0.3788 0.1781 5.7213 1.5379
+#> 151: 93.0046 -6.5379 -0.1164 2.2757 -0.9845 2.0092 6.8660 0.3719 0.3827 0.1807 5.7612 1.5697
+#> 152: 93.2222 -6.4637 -0.1154 2.2737 -0.9950 1.6744 6.2289 0.3670 0.3881 0.1638 5.8514 1.5920
+#> 153: 93.1619 -6.3230 -0.1224 2.2638 -0.9924 1.7907 5.5429 0.3842 0.3946 0.1720 5.7562 1.5493
+#> 154: 93.0402 -6.4004 -0.1205 2.2633 -0.9868 1.7620 6.2494 0.3860 0.3891 0.1737 5.7577 1.5109
+#> 155: 93.1692 -6.4353 -0.1203 2.2696 -0.9761 1.8710 6.4519 0.3949 0.3962 0.1721 5.8348 1.4949
+#> 156: 93.2709 -6.2672 -0.1203 2.2663 -0.9708 2.1172 5.1692 0.3949 0.4187 0.1637 6.1251 1.5012
+#> 157: 93.1264 -6.1931 -0.1208 2.2728 -0.9669 1.9985 4.7739 0.3938 0.4031 0.1696 6.1014 1.5627
+#> 158: 93.1263 -6.1951 -0.1237 2.2826 -0.9729 1.7675 4.6131 0.3928 0.3904 0.1659 6.1582 1.5647
+#> 159: 92.9780 -6.2831 -0.1242 2.2726 -0.9770 1.8348 5.4674 0.3938 0.3887 0.1631 6.0622 1.5787
+#> 160: 93.1289 -6.4397 -0.1263 2.2651 -0.9675 2.4637 6.0560 0.3919 0.4017 0.1626 5.9486 1.5859
+#> 161: 93.2629 -6.3336 -0.1294 2.2670 -0.9666 2.9602 5.4966 0.3872 0.3988 0.1667 5.9034 1.5421
+#> 162: 93.1652 -6.3800 -0.1342 2.2518 -0.9754 2.8800 5.6206 0.3908 0.4158 0.1627 5.9332 1.5306
+#> 163: 93.2886 -6.4115 -0.1437 2.2330 -0.9685 1.9997 6.2760 0.4015 0.4076 0.1623 5.7905 1.5398
+#> 164: 93.4631 -6.7246 -0.1396 2.2358 -0.9854 1.8885 7.8014 0.3952 0.4028 0.1573 5.7052 1.5695
+#> 165: 93.4757 -6.8408 -0.1404 2.2346 -0.9825 2.4877 9.3632 0.3948 0.4019 0.1615 5.8406 1.5902
+#> 166: 93.9075 -6.7707 -0.1428 2.2331 -0.9848 1.9761 8.9292 0.3939 0.3909 0.1610 5.7600 1.5966
+#> 167: 93.8895 -7.1938 -0.1363 2.2449 -0.9870 2.0894 11.4058 0.3850 0.3899 0.1627 5.8501 1.5748
+#> 168: 93.5849 -6.8478 -0.1294 2.2466 -0.9888 2.3573 9.4037 0.3935 0.3808 0.1645 6.0206 1.6591
+#> 169: 93.4931 -6.4550 -0.1173 2.2727 -0.9990 2.1948 6.5738 0.3844 0.4029 0.1699 6.0990 1.6123
+#> 170: 93.7188 -6.4015 -0.1173 2.2715 -0.9981 1.8800 6.1745 0.3844 0.4001 0.1635 6.1990 1.5745
+#> 171: 93.5938 -6.4389 -0.1119 2.2663 -0.9893 2.5731 6.5397 0.3858 0.4044 0.1554 6.1636 1.5631
+#> 172: 93.4515 -6.2049 -0.1050 2.2937 -0.9701 2.6134 4.6813 0.3687 0.4017 0.1715 6.3875 1.5006
+#> 173: 93.2254 -6.2074 -0.1041 2.3111 -0.9661 2.5799 4.6939 0.3669 0.4016 0.1738 6.5633 1.5229
+#> 174: 93.4116 -6.1198 -0.1050 2.3075 -0.9711 3.0196 4.3080 0.3720 0.3988 0.1778 6.4856 1.5214
+#> 175: 93.4952 -6.0439 -0.1050 2.3008 -0.9714 3.1172 3.7728 0.3720 0.3979 0.1749 6.1918 1.4985
+#> 176: 93.6186 -6.0891 -0.1061 2.3033 -0.9794 2.1081 3.8909 0.3705 0.4029 0.1796 6.1064 1.4657
+#> 177: 93.6432 -5.9977 -0.1031 2.2953 -0.9950 1.9411 3.4156 0.3694 0.3970 0.1843 6.0473 1.4918
+#> 178: 93.5736 -6.0079 -0.0996 2.2986 -0.9809 1.7778 3.5107 0.3696 0.3909 0.1840 6.1243 1.4937
+#> 179: 93.6407 -6.0246 -0.0977 2.3042 -0.9770 2.0631 3.8144 0.3718 0.3885 0.1798 6.1851 1.5212
+#> 180: 93.6336 -5.8865 -0.0969 2.3217 -0.9871 2.2566 3.1377 0.3721 0.3715 0.1784 6.0747 1.5546
+#> 181: 93.5075 -5.8632 -0.0965 2.3140 -0.9764 2.5812 2.9771 0.3715 0.3728 0.1876 5.9833 1.5356
+#> 182: 93.4464 -5.8627 -0.0930 2.3211 -0.9713 2.5956 2.8054 0.3836 0.3759 0.1861 6.1293 1.6259
+#> 183: 93.2737 -5.8238 -0.0977 2.3127 -0.9642 2.8739 2.6277 0.3846 0.3743 0.1868 6.0451 1.6493
+#> 184: 93.2191 -5.9175 -0.0993 2.3107 -0.9592 2.3088 3.0689 0.3829 0.3515 0.1711 6.1487 1.6666
+#> 185: 93.3626 -5.8872 -0.1070 2.3112 -0.9413 2.2812 3.2719 0.3712 0.3555 0.1783 6.1295 1.6288
+#> 186: 93.1585 -5.8532 -0.1053 2.3140 -0.9665 2.7906 2.8415 0.3734 0.3531 0.1680 6.0294 1.6104
+#> 187: 93.3041 -5.6798 -0.0957 2.3158 -0.9608 3.1056 2.0850 0.3813 0.3484 0.1728 6.1191 1.5813
+#> 188: 93.2466 -5.6791 -0.0954 2.3172 -0.9446 3.8296 2.1956 0.3816 0.3439 0.1757 5.9670 1.5445
+#> 189: 93.3532 -5.6883 -0.0859 2.3335 -0.9594 2.8968 2.3125 0.3691 0.3512 0.1812 5.9467 1.6101
+#> 190: 93.5064 -5.6288 -0.0726 2.3548 -0.9562 2.8233 2.1930 0.3334 0.3700 0.1759 6.4036 1.5877
+#> 191: 93.4145 -5.6906 -0.0726 2.3467 -0.9624 2.8818 2.3581 0.3334 0.3771 0.1712 6.2046 1.4952
+#> 192: 93.2060 -5.7479 -0.0716 2.3433 -0.9618 2.5221 2.6613 0.3324 0.3909 0.1552 6.1651 1.4971
+#> 193: 93.2904 -5.7634 -0.0811 2.3327 -0.9585 2.6968 2.6324 0.3339 0.3856 0.1632 6.5621 1.5258
+#> 194: 93.5271 -5.7859 -0.0874 2.3419 -0.9580 2.8361 2.8424 0.3286 0.3784 0.1636 6.3714 1.5386
+#> 195: 93.3944 -5.9358 -0.0838 2.3407 -0.9718 3.4161 3.2427 0.3315 0.3787 0.1678 6.3722 1.5181
+#> 196: 93.2341 -5.9078 -0.0701 2.3492 -0.9816 3.1580 3.0586 0.3285 0.3666 0.1681 6.4633 1.5382
+#> 197: 93.2967 -6.0131 -0.0745 2.3426 -0.9991 3.7978 3.6459 0.3353 0.3491 0.1796 6.2264 1.5310
+#> 198: 93.2628 -5.7991 -0.0730 2.3434 -0.9819 2.3896 2.6695 0.3371 0.3431 0.1762 6.3141 1.5254
+#> 199: 93.2765 -5.9078 -0.0782 2.3553 -0.9864 2.2760 3.3883 0.3420 0.3459 0.1866 6.0192 1.4982
+#> 200: 93.0447 -5.9148 -0.0769 2.3543 -0.9759 2.1516 2.9675 0.3455 0.3476 0.1870 5.9079 1.4688
+#> 201: 93.1655 -5.8951 -0.0763 2.3493 -0.9707 1.8254 2.9481 0.3448 0.3526 0.1831 6.0676 1.5097
+#> 202: 93.1082 -5.8916 -0.0768 2.3499 -0.9673 1.8503 2.9562 0.3447 0.3574 0.1821 6.1282 1.5026
+#> 203: 93.0728 -5.9316 -0.0774 2.3506 -0.9650 2.0210 3.2306 0.3441 0.3563 0.1827 6.1253 1.4974
+#> 204: 93.0846 -5.9347 -0.0773 2.3494 -0.9648 2.1463 3.2567 0.3453 0.3563 0.1824 6.1301 1.4911
+#> 205: 93.0929 -5.9439 -0.0781 2.3491 -0.9659 2.2204 3.3165 0.3453 0.3572 0.1823 6.1098 1.4941
+#> 206: 93.1795 -5.9401 -0.0795 2.3481 -0.9681 2.2588 3.2940 0.3470 0.3568 0.1829 6.1132 1.4996
+#> 207: 93.2303 -5.9158 -0.0805 2.3467 -0.9703 2.3439 3.1823 0.3484 0.3571 0.1845 6.1021 1.5059
+#> 208: 93.2161 -5.8969 -0.0825 2.3440 -0.9700 2.3306 3.0999 0.3496 0.3563 0.1848 6.0998 1.5177
+#> 209: 93.2077 -5.8842 -0.0848 2.3413 -0.9681 2.3580 3.0406 0.3499 0.3553 0.1841 6.0829 1.5199
+#> 210: 93.1951 -5.8661 -0.0867 2.3383 -0.9656 2.4170 2.9578 0.3501 0.3543 0.1833 6.0562 1.5261
+#> 211: 93.1870 -5.8543 -0.0892 2.3347 -0.9645 2.4650 2.9307 0.3502 0.3548 0.1831 6.0286 1.5289
+#> 212: 93.2077 -5.8506 -0.0915 2.3316 -0.9626 2.4909 2.9544 0.3504 0.3555 0.1835 6.0079 1.5300
+#> 213: 93.2104 -5.8492 -0.0938 2.3283 -0.9612 2.4695 2.9635 0.3503 0.3548 0.1841 5.9859 1.5341
+#> 214: 93.2059 -5.8537 -0.0959 2.3255 -0.9615 2.4264 3.0084 0.3499 0.3540 0.1835 5.9698 1.5370
+#> 215: 93.2051 -5.8569 -0.0977 2.3227 -0.9608 2.4277 3.0541 0.3495 0.3534 0.1830 5.9586 1.5374
+#> 216: 93.1879 -5.8596 -0.0993 2.3199 -0.9600 2.4347 3.0802 0.3493 0.3534 0.1828 5.9465 1.5380
+#> 217: 93.1834 -5.8621 -0.1008 2.3173 -0.9594 2.4479 3.0998 0.3491 0.3535 0.1827 5.9369 1.5402
+#> 218: 93.1796 -5.8657 -0.1021 2.3152 -0.9593 2.4234 3.1238 0.3492 0.3534 0.1835 5.9184 1.5441
+#> 219: 93.1680 -5.8721 -0.1032 2.3132 -0.9588 2.4640 3.1464 0.3494 0.3531 0.1839 5.8929 1.5493
+#> 220: 93.1579 -5.8839 -0.1044 2.3118 -0.9586 2.5707 3.1909 0.3495 0.3531 0.1847 5.8754 1.5496
+#> 221: 93.1557 -5.8882 -0.1058 2.3100 -0.9583 2.6662 3.2052 0.3492 0.3533 0.1854 5.8662 1.5518
+#> 222: 93.1624 -5.8832 -0.1074 2.3075 -0.9578 2.7993 3.1736 0.3490 0.3542 0.1861 5.8489 1.5546
+#> 223: 93.1699 -5.8771 -0.1086 2.3052 -0.9583 2.9085 3.1456 0.3488 0.3558 0.1871 5.8436 1.5610
+#> 224: 93.1870 -5.8751 -0.1097 2.3037 -0.9583 2.9988 3.1279 0.3487 0.3570 0.1878 5.8390 1.5628
+#> 225: 93.2094 -5.8719 -0.1110 2.3012 -0.9583 3.0581 3.1018 0.3485 0.3574 0.1885 5.8214 1.5656
+#> 226: 93.2352 -5.8683 -0.1122 2.2988 -0.9587 3.1297 3.0761 0.3482 0.3584 0.1895 5.8105 1.5680
+#> 227: 93.2611 -5.8653 -0.1132 2.2964 -0.9589 3.1563 3.0610 0.3476 0.3594 0.1904 5.8038 1.5701
+#> 228: 93.2741 -5.8593 -0.1140 2.2943 -0.9591 3.1641 3.0356 0.3470 0.3603 0.1911 5.7984 1.5730
+#> 229: 93.2899 -5.8593 -0.1151 2.2919 -0.9595 3.1626 3.0313 0.3466 0.3613 0.1918 5.7999 1.5745
+#> 230: 93.3048 -5.8650 -0.1164 2.2899 -0.9593 3.1743 3.0542 0.3460 0.3624 0.1921 5.7990 1.5753
+#> 231: 93.3159 -5.8638 -0.1177 2.2875 -0.9592 3.1930 3.0524 0.3454 0.3631 0.1924 5.7956 1.5748
+#> 232: 93.3209 -5.8611 -0.1189 2.2852 -0.9590 3.1872 3.0420 0.3450 0.3639 0.1926 5.7921 1.5755
+#> 233: 93.3196 -5.8556 -0.1200 2.2833 -0.9589 3.1861 3.0209 0.3445 0.3644 0.1926 5.7852 1.5779
+#> 234: 93.3245 -5.8530 -0.1210 2.2813 -0.9591 3.1890 3.0115 0.3441 0.3651 0.1922 5.7781 1.5786
+#> 235: 93.3219 -5.8522 -0.1218 2.2800 -0.9593 3.1573 3.0042 0.3437 0.3659 0.1917 5.7813 1.5797
+#> 236: 93.3155 -5.8524 -0.1227 2.2789 -0.9595 3.1542 3.0035 0.3433 0.3669 0.1913 5.7834 1.5800
+#> 237: 93.3060 -5.8556 -0.1235 2.2779 -0.9599 3.1308 3.0158 0.3430 0.3678 0.1910 5.7833 1.5809
+#> 238: 93.3111 -5.8563 -0.1242 2.2772 -0.9602 3.1194 3.0099 0.3427 0.3683 0.1907 5.7842 1.5809
+#> 239: 93.3177 -5.8580 -0.1248 2.2764 -0.9605 3.0944 3.0130 0.3423 0.3686 0.1904 5.7840 1.5815
+#> 240: 93.3222 -5.8606 -0.1255 2.2754 -0.9608 3.0739 3.0140 0.3420 0.3686 0.1902 5.7843 1.5825
+#> 241: 93.3289 -5.8627 -0.1262 2.2740 -0.9611 3.0848 3.0167 0.3417 0.3688 0.1900 5.7836 1.5840
+#> 242: 93.3366 -5.8627 -0.1270 2.2727 -0.9612 3.1273 3.0103 0.3415 0.3691 0.1898 5.7855 1.5850
+#> 243: 93.3441 -5.8646 -0.1277 2.2714 -0.9614 3.1530 3.0218 0.3414 0.3692 0.1896 5.7829 1.5856
+#> 244: 93.3499 -5.8645 -0.1285 2.2700 -0.9618 3.1705 3.0265 0.3412 0.3694 0.1894 5.7778 1.5874
+#> 245: 93.3619 -5.8673 -0.1294 2.2686 -0.9622 3.1863 3.0397 0.3412 0.3694 0.1892 5.7752 1.5889
+#> 246: 93.3745 -5.8698 -0.1301 2.2671 -0.9627 3.2105 3.0484 0.3412 0.3693 0.1890 5.7716 1.5905
+#> 247: 93.3838 -5.8757 -0.1307 2.2659 -0.9632 3.2158 3.0715 0.3412 0.3693 0.1889 5.7688 1.5922
+#> 248: 93.3914 -5.8799 -0.1314 2.2650 -0.9640 3.2268 3.0851 0.3413 0.3690 0.1889 5.7648 1.5934
+#> 249: 93.3983 -5.8844 -0.1319 2.2640 -0.9648 3.2471 3.0990 0.3415 0.3691 0.1889 5.7641 1.5944
+#> 250: 93.4032 -5.8898 -0.1324 2.2629 -0.9655 3.2828 3.1197 0.3414 0.3694 0.1887 5.7623 1.5965
+#> 251: 93.4053 -5.8939 -0.1329 2.2621 -0.9657 3.3074 3.1303 0.3414 0.3698 0.1887 5.7611 1.5978
+#> 252: 93.4095 -5.8950 -0.1334 2.2613 -0.9658 3.3479 3.1281 0.3414 0.3701 0.1887 5.7578 1.5986
+#> 253: 93.4132 -5.8956 -0.1340 2.2606 -0.9660 3.3486 3.1283 0.3413 0.3703 0.1887 5.7559 1.5999
+#> 254: 93.4201 -5.8966 -0.1345 2.2597 -0.9660 3.3502 3.1298 0.3413 0.3706 0.1888 5.7593 1.5997
+#> 255: 93.4235 -5.8953 -0.1349 2.2590 -0.9656 3.3332 3.1220 0.3412 0.3706 0.1887 5.7571 1.6012
+#> 256: 93.4231 -5.8926 -0.1353 2.2585 -0.9651 3.3255 3.1104 0.3411 0.3706 0.1886 5.7569 1.6018
+#> 257: 93.4247 -5.8874 -0.1356 2.2582 -0.9646 3.3164 3.0917 0.3410 0.3705 0.1885 5.7585 1.6030
+#> 258: 93.4198 -5.8857 -0.1359 2.2580 -0.9641 3.3086 3.0828 0.3409 0.3702 0.1885 5.7608 1.6026
+#> 259: 93.4125 -5.8833 -0.1362 2.2576 -0.9638 3.2926 3.0726 0.3408 0.3701 0.1885 5.7651 1.6023
+#> 260: 93.4073 -5.8847 -0.1365 2.2572 -0.9640 3.2737 3.0759 0.3406 0.3703 0.1885 5.7687 1.6030
+#> 261: 93.4049 -5.8885 -0.1368 2.2571 -0.9642 3.2510 3.0904 0.3402 0.3702 0.1882 5.7742 1.6028
+#> 262: 93.4036 -5.8931 -0.1371 2.2566 -0.9645 3.2279 3.1104 0.3397 0.3699 0.1880 5.7766 1.6033
+#> 263: 93.4026 -5.8964 -0.1375 2.2562 -0.9647 3.2024 3.1313 0.3395 0.3696 0.1877 5.7786 1.6029
+#> 264: 93.3990 -5.9003 -0.1377 2.2559 -0.9649 3.1808 3.1545 0.3393 0.3694 0.1874 5.7778 1.6022
+#> 265: 93.4005 -5.9013 -0.1380 2.2555 -0.9650 3.1664 3.1680 0.3390 0.3693 0.1871 5.7765 1.6021
+#> 266: 93.4005 -5.9011 -0.1382 2.2552 -0.9653 3.1530 3.1708 0.3387 0.3692 0.1869 5.7763 1.6020
+#> 267: 93.4006 -5.9035 -0.1384 2.2549 -0.9654 3.1384 3.1902 0.3384 0.3690 0.1866 5.7768 1.6014
+#> 268: 93.3972 -5.9086 -0.1385 2.2547 -0.9653 3.1224 3.2331 0.3380 0.3688 0.1863 5.7778 1.6008
+#> 269: 93.3936 -5.9113 -0.1386 2.2547 -0.9654 3.0959 3.2552 0.3377 0.3688 0.1861 5.7782 1.6001
+#> 270: 93.3867 -5.9139 -0.1387 2.2547 -0.9653 3.0853 3.2756 0.3372 0.3687 0.1859 5.7787 1.5989
+#> 271: 93.3836 -5.9154 -0.1389 2.2545 -0.9654 3.0824 3.2889 0.3367 0.3686 0.1858 5.7761 1.5980
+#> 272: 93.3812 -5.9160 -0.1390 2.2543 -0.9653 3.0741 3.2919 0.3362 0.3686 0.1857 5.7729 1.5977
+#> 273: 93.3767 -5.9174 -0.1390 2.2542 -0.9652 3.0663 3.2992 0.3358 0.3687 0.1856 5.7699 1.5970
+#> 274: 93.3696 -5.9171 -0.1391 2.2543 -0.9652 3.0604 3.2940 0.3355 0.3687 0.1855 5.7688 1.5958
+#> 275: 93.3658 -5.9177 -0.1393 2.2544 -0.9651 3.0605 3.2961 0.3353 0.3687 0.1853 5.7675 1.5952
+#> 276: 93.3621 -5.9185 -0.1395 2.2543 -0.9649 3.0508 3.2992 0.3351 0.3686 0.1852 5.7672 1.5940
+#> 277: 93.3602 -5.9206 -0.1397 2.2542 -0.9649 3.0453 3.3087 0.3349 0.3685 0.1851 5.7679 1.5935
+#> 278: 93.3565 -5.9213 -0.1400 2.2539 -0.9648 3.0366 3.3117 0.3347 0.3683 0.1852 5.7695 1.5931
+#> 279: 93.3548 -5.9222 -0.1403 2.2535 -0.9647 3.0284 3.3179 0.3345 0.3682 0.1854 5.7703 1.5928
+#> 280: 93.3544 -5.9215 -0.1407 2.2528 -0.9647 3.0193 3.3141 0.3344 0.3683 0.1854 5.7714 1.5927
+#> 281: 93.3533 -5.9205 -0.1410 2.2522 -0.9647 3.0130 3.3090 0.3341 0.3685 0.1855 5.7706 1.5927
+#> 282: 93.3564 -5.9189 -0.1414 2.2514 -0.9648 3.0025 3.3019 0.3339 0.3686 0.1856 5.7682 1.5930
+#> 283: 93.3571 -5.9164 -0.1417 2.2508 -0.9646 2.9990 3.2926 0.3337 0.3686 0.1858 5.7642 1.5943
+#> 284: 93.3576 -5.9154 -0.1421 2.2501 -0.9644 2.9976 3.2895 0.3336 0.3686 0.1860 5.7625 1.5942
+#> 285: 93.3584 -5.9142 -0.1425 2.2496 -0.9644 2.9906 3.2835 0.3334 0.3684 0.1861 5.7591 1.5939
+#> 286: 93.3609 -5.9137 -0.1429 2.2491 -0.9642 2.9852 3.2817 0.3332 0.3682 0.1863 5.7572 1.5939
+#> 287: 93.3641 -5.9131 -0.1433 2.2485 -0.9641 2.9732 3.2785 0.3331 0.3680 0.1863 5.7547 1.5944
+#> 288: 93.3671 -5.9128 -0.1436 2.2480 -0.9641 2.9673 3.2767 0.3330 0.3679 0.1864 5.7540 1.5939
+#> 289: 93.3676 -5.9125 -0.1440 2.2474 -0.9639 2.9663 3.2765 0.3329 0.3678 0.1865 5.7536 1.5939
+#> 290: 93.3659 -5.9126 -0.1443 2.2469 -0.9637 2.9570 3.2776 0.3328 0.3678 0.1866 5.7523 1.5941
+#> 291: 93.3620 -5.9109 -0.1447 2.2466 -0.9634 2.9472 3.2713 0.3327 0.3676 0.1866 5.7527 1.5943
+#> 292: 93.3601 -5.9096 -0.1450 2.2462 -0.9632 2.9359 3.2664 0.3326 0.3675 0.1866 5.7517 1.5944
+#> 293: 93.3582 -5.9077 -0.1453 2.2457 -0.9629 2.9295 3.2586 0.3326 0.3675 0.1866 5.7514 1.5945
+#> 294: 93.3583 -5.9054 -0.1456 2.2454 -0.9626 2.9203 3.2478 0.3326 0.3676 0.1867 5.7508 1.5942
+#> 295: 93.3577 -5.9037 -0.1459 2.2449 -0.9624 2.9216 3.2406 0.3325 0.3678 0.1867 5.7493 1.5934
+#> 296: 93.3570 -5.9016 -0.1462 2.2445 -0.9623 2.9304 3.2334 0.3323 0.3680 0.1868 5.7502 1.5933
+#> 297: 93.3538 -5.8988 -0.1462 2.2441 -0.9621 2.9429 3.2217 0.3321 0.3681 0.1870 5.7539 1.5939
+#> 298: 93.3525 -5.8966 -0.1463 2.2438 -0.9620 2.9662 3.2118 0.3319 0.3683 0.1870 5.7555 1.5942
+#> 299: 93.3526 -5.8957 -0.1465 2.2437 -0.9619 2.9812 3.2056 0.3318 0.3685 0.1870 5.7582 1.5938
+#> 300: 93.3504 -5.8953 -0.1467 2.2436 -0.9616 2.9982 3.2029 0.3316 0.3688 0.1873 5.7609 1.5937
+#> 301: 93.3469 -5.8941 -0.1469 2.2434 -0.9612 3.0124 3.1993 0.3315 0.3690 0.1875 5.7641 1.5933
+#> 302: 93.3442 -5.8944 -0.1472 2.2434 -0.9609 3.0353 3.2015 0.3313 0.3692 0.1876 5.7660 1.5937
+#> 303: 93.3428 -5.8970 -0.1474 2.2432 -0.9607 3.0454 3.2160 0.3312 0.3692 0.1876 5.7654 1.5938
+#> 304: 93.3407 -5.9012 -0.1475 2.2430 -0.9607 3.0626 3.2409 0.3310 0.3693 0.1877 5.7649 1.5932
+#> 305: 93.3395 -5.9051 -0.1476 2.2429 -0.9607 3.0756 3.2632 0.3308 0.3693 0.1879 5.7650 1.5924
+#> 306: 93.3398 -5.9099 -0.1478 2.2429 -0.9607 3.0881 3.2952 0.3306 0.3694 0.1880 5.7655 1.5920
+#> 307: 93.3406 -5.9128 -0.1479 2.2427 -0.9608 3.0995 3.3163 0.3305 0.3695 0.1880 5.7666 1.5921
+#> 308: 93.3418 -5.9165 -0.1480 2.2426 -0.9610 3.1060 3.3420 0.3303 0.3696 0.1881 5.7674 1.5914
+#> 309: 93.3437 -5.9205 -0.1481 2.2424 -0.9610 3.1185 3.3703 0.3301 0.3697 0.1882 5.7665 1.5908
+#> 310: 93.3442 -5.9236 -0.1482 2.2422 -0.9612 3.1270 3.3902 0.3299 0.3698 0.1882 5.7650 1.5904
+#> 311: 93.3482 -5.9268 -0.1482 2.2421 -0.9614 3.1333 3.4086 0.3296 0.3698 0.1882 5.7636 1.5900
+#> 312: 93.3529 -5.9286 -0.1482 2.2420 -0.9615 3.1348 3.4186 0.3294 0.3699 0.1882 5.7622 1.5895
+#> 313: 93.3573 -5.9290 -0.1481 2.2419 -0.9617 3.1332 3.4199 0.3291 0.3699 0.1882 5.7621 1.5891
+#> 314: 93.3630 -5.9293 -0.1482 2.2418 -0.9619 3.1398 3.4211 0.3289 0.3700 0.1883 5.7594 1.5888
+#> 315: 93.3669 -5.9284 -0.1483 2.2416 -0.9622 3.1464 3.4155 0.3286 0.3702 0.1885 5.7586 1.5889
+#> 316: 93.3724 -5.9279 -0.1485 2.2412 -0.9624 3.1426 3.4124 0.3283 0.3704 0.1887 5.7581 1.5887
+#> 317: 93.3763 -5.9281 -0.1487 2.2409 -0.9626 3.1335 3.4108 0.3281 0.3706 0.1888 5.7573 1.5880
+#> 318: 93.3786 -5.9275 -0.1488 2.2405 -0.9627 3.1262 3.4057 0.3279 0.3709 0.1888 5.7579 1.5876
+#> 319: 93.3821 -5.9275 -0.1490 2.2402 -0.9628 3.1273 3.4032 0.3276 0.3711 0.1889 5.7570 1.5870
+#> 320: 93.3856 -5.9272 -0.1491 2.2401 -0.9629 3.1337 3.3989 0.3273 0.3715 0.1888 5.7563 1.5861
+#> 321: 93.3902 -5.9263 -0.1492 2.2399 -0.9631 3.1388 3.3931 0.3269 0.3718 0.1887 5.7555 1.5852
+#> 322: 93.3951 -5.9251 -0.1493 2.2397 -0.9631 3.1415 3.3856 0.3266 0.3721 0.1886 5.7552 1.5846
+#> 323: 93.3988 -5.9251 -0.1493 2.2395 -0.9632 3.1377 3.3824 0.3262 0.3724 0.1885 5.7556 1.5841
+#> 324: 93.4030 -5.9236 -0.1494 2.2394 -0.9633 3.1355 3.3738 0.3259 0.3727 0.1885 5.7562 1.5837
+#> 325: 93.4047 -5.9219 -0.1495 2.2393 -0.9633 3.1415 3.3647 0.3256 0.3731 0.1884 5.7553 1.5831
+#> 326: 93.4077 -5.9204 -0.1495 2.2391 -0.9634 3.1489 3.3564 0.3254 0.3735 0.1884 5.7562 1.5829
+#> 327: 93.4121 -5.9185 -0.1496 2.2390 -0.9635 3.1503 3.3472 0.3250 0.3739 0.1884 5.7562 1.5825
+#> 328: 93.4157 -5.9182 -0.1496 2.2389 -0.9636 3.1564 3.3432 0.3246 0.3743 0.1884 5.7559 1.5823
+#> 329: 93.4181 -5.9169 -0.1496 2.2388 -0.9638 3.1666 3.3361 0.3243 0.3746 0.1884 5.7544 1.5822
+#> 330: 93.4206 -5.9171 -0.1497 2.2386 -0.9640 3.1726 3.3349 0.3239 0.3748 0.1885 5.7538 1.5824
+#> 331: 93.4214 -5.9172 -0.1497 2.2385 -0.9642 3.1764 3.3332 0.3236 0.3750 0.1886 5.7540 1.5824
+#> 332: 93.4226 -5.9171 -0.1497 2.2385 -0.9645 3.1787 3.3303 0.3232 0.3752 0.1887 5.7539 1.5826
+#> 333: 93.4242 -5.9168 -0.1497 2.2384 -0.9645 3.1757 3.3287 0.3229 0.3755 0.1886 5.7545 1.5823
+#> 334: 93.4273 -5.9167 -0.1497 2.2383 -0.9645 3.1832 3.3290 0.3226 0.3758 0.1887 5.7540 1.5818
+#> 335: 93.4306 -5.9170 -0.1498 2.2384 -0.9644 3.1910 3.3318 0.3223 0.3760 0.1887 5.7548 1.5814
+#> 336: 93.4315 -5.9177 -0.1498 2.2384 -0.9644 3.1999 3.3355 0.3219 0.3762 0.1887 5.7558 1.5811
+#> 337: 93.4332 -5.9181 -0.1499 2.2384 -0.9643 3.2145 3.3360 0.3216 0.3764 0.1887 5.7581 1.5805
+#> 338: 93.4352 -5.9169 -0.1498 2.2384 -0.9643 3.2221 3.3307 0.3213 0.3767 0.1887 5.7592 1.5802
+#> 339: 93.4385 -5.9152 -0.1498 2.2384 -0.9643 3.2356 3.3242 0.3210 0.3770 0.1887 5.7605 1.5797
+#> 340: 93.4417 -5.9130 -0.1498 2.2384 -0.9643 3.2506 3.3167 0.3207 0.3773 0.1888 5.7599 1.5794
+#> 341: 93.4452 -5.9102 -0.1497 2.2382 -0.9641 3.2568 3.3064 0.3205 0.3772 0.1888 5.7590 1.5799
+#> 342: 93.4487 -5.9077 -0.1497 2.2381 -0.9641 3.2628 3.2970 0.3203 0.3772 0.1889 5.7587 1.5802
+#> 343: 93.4519 -5.9055 -0.1497 2.2380 -0.9642 3.2685 3.2892 0.3201 0.3772 0.1889 5.7585 1.5810
+#> 344: 93.4556 -5.9048 -0.1497 2.2379 -0.9643 3.2690 3.2847 0.3200 0.3771 0.1891 5.7573 1.5812
+#> 345: 93.4588 -5.9041 -0.1498 2.2377 -0.9645 3.2704 3.2807 0.3199 0.3771 0.1893 5.7567 1.5811
+#> 346: 93.4605 -5.9033 -0.1498 2.2376 -0.9647 3.2655 3.2747 0.3198 0.3770 0.1893 5.7557 1.5808
+#> 347: 93.4638 -5.9027 -0.1498 2.2375 -0.9648 3.2725 3.2701 0.3198 0.3768 0.1894 5.7532 1.5808
+#> 348: 93.4643 -5.9028 -0.1498 2.2373 -0.9649 3.2764 3.2676 0.3197 0.3768 0.1893 5.7523 1.5807
+#> 349: 93.4664 -5.9023 -0.1497 2.2372 -0.9650 3.2806 3.2638 0.3197 0.3767 0.1893 5.7527 1.5815
+#> 350: 93.4700 -5.9014 -0.1497 2.2370 -0.9651 3.2817 3.2585 0.3196 0.3767 0.1892 5.7534 1.5817
+#> 351: 93.4724 -5.9001 -0.1497 2.2369 -0.9652 3.2825 3.2522 0.3196 0.3768 0.1892 5.7541 1.5818
+#> 352: 93.4744 -5.8986 -0.1497 2.2369 -0.9653 3.2875 3.2460 0.3195 0.3768 0.1891 5.7546 1.5819
+#> 353: 93.4738 -5.8975 -0.1496 2.2369 -0.9653 3.2891 3.2407 0.3195 0.3769 0.1889 5.7560 1.5822
+#> 354: 93.4733 -5.8960 -0.1496 2.2369 -0.9652 3.2856 3.2333 0.3194 0.3768 0.1889 5.7579 1.5824
+#> 355: 93.4731 -5.8944 -0.1496 2.2370 -0.9652 3.2893 3.2259 0.3194 0.3767 0.1888 5.7599 1.5826
+#> 356: 93.4724 -5.8933 -0.1495 2.2373 -0.9652 3.2924 3.2197 0.3194 0.3767 0.1888 5.7608 1.5832
+#> 357: 93.4723 -5.8929 -0.1493 2.2376 -0.9654 3.2907 3.2164 0.3194 0.3767 0.1887 5.7605 1.5833
+#> 358: 93.4723 -5.8923 -0.1491 2.2378 -0.9654 3.2875 3.2120 0.3194 0.3766 0.1886 5.7608 1.5837
+#> 359: 93.4705 -5.8931 -0.1490 2.2379 -0.9656 3.2875 3.2121 0.3194 0.3764 0.1886 5.7606 1.5843
+#> 360: 93.4699 -5.8938 -0.1488 2.2382 -0.9658 3.2837 3.2133 0.3195 0.3763 0.1886 5.7606 1.5848
+#> 361: 93.4693 -5.8951 -0.1487 2.2383 -0.9659 3.2822 3.2164 0.3195 0.3763 0.1886 5.7600 1.5852
+#> 362: 93.4691 -5.8963 -0.1486 2.2385 -0.9660 3.2770 3.2196 0.3195 0.3763 0.1884 5.7618 1.5856
+#> 363: 93.4681 -5.8970 -0.1485 2.2387 -0.9660 3.2706 3.2208 0.3195 0.3762 0.1883 5.7639 1.5857
+#> 364: 93.4674 -5.8970 -0.1484 2.2389 -0.9660 3.2593 3.2189 0.3195 0.3760 0.1881 5.7659 1.5855
+#> 365: 93.4680 -5.8968 -0.1482 2.2391 -0.9659 3.2513 3.2174 0.3196 0.3758 0.1881 5.7686 1.5857
+#> 366: 93.4672 -5.8962 -0.1480 2.2393 -0.9658 3.2493 3.2161 0.3196 0.3755 0.1880 5.7714 1.5861
+#> 367: 93.4656 -5.8953 -0.1479 2.2396 -0.9657 3.2462 3.2121 0.3195 0.3753 0.1881 5.7721 1.5862
+#> 368: 93.4645 -5.8946 -0.1478 2.2398 -0.9657 3.2469 3.2083 0.3194 0.3750 0.1882 5.7724 1.5860
+#> 369: 93.4638 -5.8946 -0.1476 2.2401 -0.9657 3.2544 3.2068 0.3194 0.3749 0.1882 5.7713 1.5856
+#> 370: 93.4639 -5.8946 -0.1475 2.2404 -0.9657 3.2547 3.2066 0.3194 0.3748 0.1882 5.7719 1.5853
+#> 371: 93.4646 -5.8959 -0.1474 2.2407 -0.9657 3.2584 3.2129 0.3194 0.3746 0.1883 5.7725 1.5847
+#> 372: 93.4648 -5.8964 -0.1473 2.2409 -0.9658 3.2649 3.2172 0.3193 0.3745 0.1883 5.7730 1.5843
+#> 373: 93.4658 -5.8958 -0.1471 2.2411 -0.9659 3.2744 3.2135 0.3193 0.3743 0.1884 5.7730 1.5843
+#> 374: 93.4678 -5.8953 -0.1470 2.2412 -0.9662 3.2855 3.2100 0.3192 0.3742 0.1885 5.7727 1.5847
+#> 375: 93.4697 -5.8955 -0.1470 2.2413 -0.9663 3.2917 3.2087 0.3190 0.3742 0.1885 5.7733 1.5845
+#> 376: 93.4707 -5.8960 -0.1469 2.2414 -0.9664 3.2997 3.2095 0.3189 0.3741 0.1885 5.7726 1.5841
+#> 377: 93.4712 -5.8965 -0.1468 2.2415 -0.9665 3.3016 3.2100 0.3188 0.3741 0.1885 5.7724 1.5836
+#> 378: 93.4706 -5.8971 -0.1468 2.2416 -0.9665 3.2958 3.2113 0.3187 0.3741 0.1884 5.7733 1.5829
+#> 379: 93.4699 -5.8983 -0.1467 2.2418 -0.9666 3.2940 3.2174 0.3186 0.3741 0.1883 5.7732 1.5827
+#> 380: 93.4709 -5.8993 -0.1467 2.2418 -0.9667 3.2907 3.2225 0.3185 0.3739 0.1882 5.7726 1.5826
+#> 381: 93.4730 -5.9009 -0.1467 2.2418 -0.9667 3.2861 3.2325 0.3185 0.3737 0.1881 5.7709 1.5825
+#> 382: 93.4746 -5.9018 -0.1467 2.2418 -0.9667 3.2841 3.2407 0.3184 0.3734 0.1880 5.7692 1.5822
+#> 383: 93.4744 -5.9033 -0.1468 2.2418 -0.9667 3.2847 3.2537 0.3184 0.3732 0.1878 5.7672 1.5819
+#> 384: 93.4747 -5.9049 -0.1468 2.2418 -0.9667 3.2854 3.2640 0.3184 0.3729 0.1878 5.7657 1.5816
+#> 385: 93.4751 -5.9062 -0.1468 2.2418 -0.9666 3.2917 3.2702 0.3184 0.3727 0.1877 5.7642 1.5813
+#> 386: 93.4756 -5.9074 -0.1468 2.2418 -0.9666 3.2971 3.2753 0.3185 0.3725 0.1876 5.7625 1.5810
+#> 387: 93.4761 -5.9084 -0.1469 2.2417 -0.9666 3.2988 3.2789 0.3185 0.3723 0.1875 5.7613 1.5804
+#> 388: 93.4777 -5.9092 -0.1469 2.2417 -0.9666 3.3055 3.2811 0.3185 0.3721 0.1875 5.7599 1.5803
+#> 389: 93.4805 -5.9092 -0.1468 2.2417 -0.9667 3.3138 3.2802 0.3185 0.3719 0.1874 5.7588 1.5803
+#> 390: 93.4828 -5.9089 -0.1468 2.2417 -0.9667 3.3164 3.2782 0.3186 0.3718 0.1873 5.7576 1.5806
+#> 391: 93.4854 -5.9094 -0.1467 2.2416 -0.9668 3.3265 3.2800 0.3186 0.3716 0.1873 5.7556 1.5804
+#> 392: 93.4877 -5.9103 -0.1467 2.2416 -0.9669 3.3327 3.2836 0.3187 0.3715 0.1873 5.7535 1.5803
+#> 393: 93.4899 -5.9110 -0.1467 2.2416 -0.9669 3.3419 3.2876 0.3187 0.3715 0.1873 5.7517 1.5803
+#> 394: 93.4925 -5.9117 -0.1467 2.2416 -0.9669 3.3494 3.2903 0.3187 0.3714 0.1873 5.7508 1.5801
+#> 395: 93.4945 -5.9121 -0.1467 2.2416 -0.9670 3.3536 3.2912 0.3187 0.3714 0.1873 5.7497 1.5796
+#> 396: 93.4951 -5.9124 -0.1467 2.2416 -0.9670 3.3590 3.2918 0.3187 0.3715 0.1873 5.7476 1.5793
+#> 397: 93.4955 -5.9123 -0.1467 2.2416 -0.9669 3.3626 3.2904 0.3186 0.3715 0.1873 5.7456 1.5788
+#> 398: 93.4971 -5.9120 -0.1467 2.2416 -0.9669 3.3735 3.2887 0.3186 0.3716 0.1873 5.7433 1.5786
+#> 399: 93.4995 -5.9116 -0.1467 2.2415 -0.9669 3.3854 3.2866 0.3186 0.3716 0.1873 5.7422 1.5785
+#> 400: 93.5007 -5.9116 -0.1466 2.2415 -0.9669 3.3923 3.2856 0.3186 0.3717 0.1873 5.7416 1.5786
+#> 401: 93.5028 -5.9109 -0.1467 2.2415 -0.9669 3.4020 3.2820 0.3186 0.3718 0.1873 5.7412 1.5787
+#> 402: 93.5042 -5.9099 -0.1467 2.2414 -0.9669 3.4114 3.2781 0.3186 0.3719 0.1874 5.7406 1.5788
+#> 403: 93.5054 -5.9090 -0.1467 2.2413 -0.9670 3.4179 3.2735 0.3186 0.3720 0.1874 5.7401 1.5785
+#> 404: 93.5071 -5.9093 -0.1468 2.2412 -0.9670 3.4190 3.2726 0.3186 0.3720 0.1875 5.7392 1.5779
+#> 405: 93.5087 -5.9087 -0.1468 2.2411 -0.9671 3.4186 3.2689 0.3186 0.3721 0.1876 5.7386 1.5776
+#> 406: 93.5091 -5.9087 -0.1469 2.2411 -0.9671 3.4228 3.2688 0.3186 0.3721 0.1876 5.7377 1.5774
+#> 407: 93.5094 -5.9091 -0.1470 2.2411 -0.9672 3.4285 3.2698 0.3186 0.3720 0.1877 5.7368 1.5770
+#> 408: 93.5108 -5.9081 -0.1470 2.2410 -0.9672 3.4378 3.2648 0.3187 0.3719 0.1877 5.7358 1.5766
+#> 409: 93.5113 -5.9082 -0.1470 2.2410 -0.9672 3.4444 3.2643 0.3187 0.3719 0.1878 5.7357 1.5763
+#> 410: 93.5102 -5.9099 -0.1470 2.2410 -0.9672 3.4502 3.2731 0.3188 0.3719 0.1878 5.7359 1.5756
+#> 411: 93.5097 -5.9109 -0.1469 2.2410 -0.9673 3.4534 3.2793 0.3188 0.3718 0.1878 5.7348 1.5753
+#> 412: 93.5102 -5.9114 -0.1469 2.2410 -0.9673 3.4522 3.2836 0.3189 0.3717 0.1878 5.7330 1.5753
+#> 413: 93.5110 -5.9120 -0.1469 2.2410 -0.9675 3.4534 3.2885 0.3189 0.3716 0.1878 5.7320 1.5756
+#> 414: 93.5126 -5.9130 -0.1469 2.2410 -0.9675 3.4550 3.2943 0.3190 0.3716 0.1878 5.7314 1.5753
+#> 415: 93.5144 -5.9140 -0.1469 2.2409 -0.9676 3.4574 3.3003 0.3190 0.3715 0.1878 5.7304 1.5751
+#> 416: 93.5147 -5.9149 -0.1469 2.2409 -0.9676 3.4632 3.3059 0.3191 0.3714 0.1878 5.7292 1.5750
+#> 417: 93.5132 -5.9156 -0.1468 2.2410 -0.9677 3.4675 3.3090 0.3192 0.3713 0.1878 5.7292 1.5747
+#> 418: 93.5131 -5.9165 -0.1468 2.2410 -0.9678 3.4680 3.3130 0.3192 0.3712 0.1878 5.7296 1.5747
+#> 419: 93.5142 -5.9166 -0.1467 2.2411 -0.9678 3.4663 3.3143 0.3193 0.3712 0.1879 5.7302 1.5744
+#> 420: 93.5150 -5.9164 -0.1466 2.2412 -0.9679 3.4626 3.3130 0.3193 0.3712 0.1879 5.7303 1.5744
+#> 421: 93.5162 -5.9169 -0.1465 2.2413 -0.9681 3.4596 3.3158 0.3194 0.3713 0.1880 5.7315 1.5743
+#> 422: 93.5173 -5.9172 -0.1465 2.2414 -0.9682 3.4567 3.3165 0.3194 0.3714 0.1881 5.7332 1.5740
+#> 423: 93.5174 -5.9178 -0.1464 2.2415 -0.9684 3.4550 3.3185 0.3194 0.3715 0.1882 5.7348 1.5741
+#> 424: 93.5174 -5.9189 -0.1464 2.2417 -0.9685 3.4531 3.3225 0.3193 0.3716 0.1882 5.7360 1.5737
+#> 425: 93.5171 -5.9184 -0.1463 2.2418 -0.9685 3.4508 3.3186 0.3192 0.3718 0.1882 5.7372 1.5738
+#> 426: 93.5167 -5.9177 -0.1462 2.2419 -0.9686 3.4566 3.3143 0.3192 0.3720 0.1882 5.7385 1.5735
+#> 427: 93.5185 -5.9174 -0.1462 2.2420 -0.9687 3.4561 3.3114 0.3191 0.3721 0.1881 5.7389 1.5734
+#> 428: 93.5192 -5.9177 -0.1461 2.2421 -0.9688 3.4574 3.3112 0.3191 0.3722 0.1880 5.7398 1.5731
+#> 429: 93.5184 -5.9179 -0.1460 2.2421 -0.9689 3.4558 3.3102 0.3190 0.3723 0.1879 5.7405 1.5729
+#> 430: 93.5170 -5.9187 -0.1460 2.2421 -0.9690 3.4575 3.3132 0.3190 0.3724 0.1879 5.7404 1.5727
+#> 431: 93.5156 -5.9192 -0.1460 2.2422 -0.9691 3.4556 3.3150 0.3190 0.3724 0.1879 5.7405 1.5726
+#> 432: 93.5148 -5.9203 -0.1459 2.2422 -0.9692 3.4557 3.3201 0.3190 0.3725 0.1878 5.7409 1.5727
+#> 433: 93.5134 -5.9215 -0.1459 2.2422 -0.9692 3.4569 3.3263 0.3190 0.3726 0.1878 5.7415 1.5731
+#> 434: 93.5128 -5.9222 -0.1459 2.2423 -0.9691 3.4623 3.3304 0.3190 0.3726 0.1877 5.7422 1.5728
+#> 435: 93.5116 -5.9231 -0.1459 2.2424 -0.9691 3.4672 3.3376 0.3191 0.3727 0.1877 5.7424 1.5726
+#> 436: 93.5111 -5.9228 -0.1459 2.2425 -0.9692 3.4658 3.3352 0.3190 0.3727 0.1876 5.7429 1.5725
+#> 437: 93.5100 -5.9227 -0.1459 2.2425 -0.9692 3.4651 3.3328 0.3190 0.3727 0.1876 5.7430 1.5725
+#> 438: 93.5071 -5.9230 -0.1459 2.2425 -0.9692 3.4614 3.3329 0.3190 0.3728 0.1876 5.7437 1.5725
+#> 439: 93.5035 -5.9225 -0.1459 2.2426 -0.9691 3.4555 3.3298 0.3190 0.3728 0.1875 5.7449 1.5725
+#> 440: 93.5006 -5.9222 -0.1459 2.2426 -0.9690 3.4503 3.3286 0.3190 0.3728 0.1874 5.7461 1.5723
+#> 441: 93.4988 -5.9220 -0.1459 2.2427 -0.9689 3.4445 3.3272 0.3190 0.3728 0.1874 5.7466 1.5721
+#> 442: 93.4971 -5.9216 -0.1459 2.2428 -0.9688 3.4392 3.3265 0.3190 0.3728 0.1874 5.7475 1.5721
+#> 443: 93.4957 -5.9214 -0.1458 2.2429 -0.9688 3.4338 3.3256 0.3190 0.3729 0.1874 5.7487 1.5723
+#> 444: 93.4949 -5.9210 -0.1458 2.2430 -0.9688 3.4288 3.3236 0.3189 0.3729 0.1874 5.7502 1.5721
+#> 445: 93.4932 -5.9210 -0.1458 2.2430 -0.9687 3.4283 3.3237 0.3189 0.3731 0.1874 5.7516 1.5719
+#> 446: 93.4922 -5.9205 -0.1458 2.2430 -0.9687 3.4253 3.3215 0.3188 0.3733 0.1873 5.7524 1.5717
+#> 447: 93.4917 -5.9205 -0.1458 2.2430 -0.9686 3.4257 3.3213 0.3187 0.3736 0.1873 5.7528 1.5715
+#> 448: 93.4924 -5.9205 -0.1458 2.2430 -0.9685 3.4296 3.3209 0.3186 0.3737 0.1872 5.7532 1.5717
+#> 449: 93.4920 -5.9203 -0.1459 2.2430 -0.9684 3.4302 3.3194 0.3185 0.3739 0.1872 5.7542 1.5717
+#> 450: 93.4915 -5.9207 -0.1459 2.2430 -0.9684 3.4314 3.3217 0.3184 0.3741 0.1871 5.7551 1.5715
+#> 451: 93.4915 -5.9214 -0.1459 2.2430 -0.9684 3.4371 3.3253 0.3183 0.3743 0.1871 5.7562 1.5717
+#> 452: 93.4926 -5.9212 -0.1458 2.2430 -0.9683 3.4417 3.3242 0.3182 0.3745 0.1870 5.7567 1.5717
+#> 453: 93.4935 -5.9211 -0.1459 2.2430 -0.9683 3.4413 3.3232 0.3182 0.3746 0.1870 5.7574 1.5714
+#> 454: 93.4941 -5.9209 -0.1459 2.2429 -0.9683 3.4406 3.3222 0.3182 0.3748 0.1870 5.7580 1.5713
+#> 455: 93.4947 -5.9212 -0.1459 2.2429 -0.9684 3.4450 3.3232 0.3181 0.3750 0.1870 5.7580 1.5710
+#> 456: 93.4950 -5.9214 -0.1459 2.2429 -0.9684 3.4481 3.3236 0.3181 0.3751 0.1870 5.7585 1.5708
+#> 457: 93.4961 -5.9220 -0.1459 2.2429 -0.9685 3.4516 3.3266 0.3180 0.3752 0.1869 5.7590 1.5707
+#> 458: 93.4965 -5.9218 -0.1459 2.2428 -0.9685 3.4553 3.3257 0.3179 0.3753 0.1869 5.7589 1.5707
+#> 459: 93.4959 -5.9212 -0.1459 2.2428 -0.9685 3.4572 3.3229 0.3178 0.3754 0.1868 5.7596 1.5705
+#> 460: 93.4960 -5.9209 -0.1459 2.2428 -0.9685 3.4573 3.3209 0.3178 0.3755 0.1868 5.7598 1.5704
+#> 461: 93.4944 -5.9211 -0.1459 2.2428 -0.9685 3.4592 3.3202 0.3177 0.3757 0.1868 5.7609 1.5701
+#> 462: 93.4941 -5.9214 -0.1459 2.2428 -0.9686 3.4630 3.3206 0.3176 0.3759 0.1868 5.7617 1.5700
+#> 463: 93.4932 -5.9215 -0.1459 2.2429 -0.9686 3.4708 3.3197 0.3175 0.3761 0.1868 5.7622 1.5699
+#> 464: 93.4933 -5.9209 -0.1459 2.2429 -0.9685 3.4759 3.3162 0.3175 0.3762 0.1869 5.7628 1.5696
+#> 465: 93.4928 -5.9204 -0.1459 2.2428 -0.9685 3.4794 3.3133 0.3174 0.3764 0.1870 5.7642 1.5693
+#> 466: 93.4934 -5.9197 -0.1460 2.2428 -0.9685 3.4838 3.3105 0.3173 0.3766 0.1870 5.7659 1.5693
+#> 467: 93.4931 -5.9197 -0.1460 2.2428 -0.9685 3.4866 3.3094 0.3172 0.3768 0.1871 5.7667 1.5691
+#> 468: 93.4933 -5.9198 -0.1460 2.2428 -0.9685 3.4916 3.3099 0.3172 0.3769 0.1871 5.7672 1.5690
+#> 469: 93.4936 -5.9200 -0.1461 2.2427 -0.9685 3.4929 3.3119 0.3171 0.3771 0.1871 5.7681 1.5689
+#> 470: 93.4938 -5.9200 -0.1461 2.2427 -0.9685 3.4931 3.3111 0.3171 0.3773 0.1871 5.7685 1.5687
+#> 471: 93.4943 -5.9198 -0.1461 2.2427 -0.9685 3.4932 3.3097 0.3170 0.3776 0.1871 5.7681 1.5686
+#> 472: 93.4931 -5.9197 -0.1461 2.2427 -0.9684 3.4923 3.3092 0.3170 0.3778 0.1870 5.7683 1.5686
+#> 473: 93.4928 -5.9193 -0.1461 2.2426 -0.9684 3.4918 3.3068 0.3169 0.3781 0.1870 5.7690 1.5685
+#> 474: 93.4920 -5.9193 -0.1462 2.2426 -0.9683 3.4878 3.3075 0.3169 0.3781 0.1870 5.7687 1.5688
+#> 475: 93.4909 -5.9191 -0.1463 2.2425 -0.9683 3.4868 3.3069 0.3169 0.3782 0.1869 5.7681 1.5692
+#> 476: 93.4887 -5.9190 -0.1464 2.2424 -0.9682 3.4881 3.3072 0.3169 0.3783 0.1869 5.7673 1.5694
+#> 477: 93.4875 -5.9185 -0.1465 2.2423 -0.9681 3.4847 3.3059 0.3169 0.3784 0.1868 5.7667 1.5696
+#> 478: 93.4867 -5.9182 -0.1466 2.2421 -0.9681 3.4804 3.3056 0.3170 0.3784 0.1867 5.7661 1.5700
+#> 479: 93.4865 -5.9178 -0.1468 2.2419 -0.9681 3.4768 3.3043 0.3171 0.3784 0.1867 5.7657 1.5702
+#> 480: 93.4863 -5.9181 -0.1469 2.2417 -0.9680 3.4733 3.3057 0.3172 0.3784 0.1866 5.7656 1.5702
+#> 481: 93.4865 -5.9182 -0.1470 2.2415 -0.9680 3.4694 3.3069 0.3173 0.3784 0.1866 5.7648 1.5705
+#> 482: 93.4871 -5.9187 -0.1472 2.2412 -0.9681 3.4667 3.3089 0.3173 0.3784 0.1865 5.7631 1.5709
+#> 483: 93.4860 -5.9192 -0.1473 2.2410 -0.9681 3.4668 3.3107 0.3174 0.3785 0.1865 5.7624 1.5709
+#> 484: 93.4858 -5.9193 -0.1474 2.2408 -0.9681 3.4681 3.3111 0.3174 0.3786 0.1864 5.7615 1.5713
+#> 485: 93.4858 -5.9195 -0.1476 2.2406 -0.9681 3.4643 3.3110 0.3174 0.3787 0.1864 5.7612 1.5717
+#> 486: 93.4853 -5.9198 -0.1477 2.2404 -0.9682 3.4665 3.3115 0.3174 0.3788 0.1864 5.7612 1.5717
+#> 487: 93.4856 -5.9201 -0.1478 2.2402 -0.9682 3.4687 3.3143 0.3173 0.3790 0.1864 5.7612 1.5719
+#> 488: 93.4858 -5.9209 -0.1479 2.2401 -0.9683 3.4688 3.3186 0.3173 0.3792 0.1864 5.7626 1.5722
+#> 489: 93.4870 -5.9211 -0.1480 2.2399 -0.9684 3.4681 3.3198 0.3174 0.3794 0.1863 5.7640 1.5725
+#> 490: 93.4881 -5.9213 -0.1481 2.2398 -0.9684 3.4694 3.3211 0.3174 0.3797 0.1864 5.7650 1.5728
+#> 491: 93.4892 -5.9210 -0.1482 2.2395 -0.9685 3.4716 3.3193 0.3173 0.3799 0.1864 5.7650 1.5732
+#> 492: 93.4907 -5.9211 -0.1483 2.2393 -0.9686 3.4754 3.3179 0.3173 0.3801 0.1865 5.7648 1.5736
+#> 493: 93.4928 -5.9215 -0.1484 2.2390 -0.9686 3.4858 3.3185 0.3173 0.3803 0.1865 5.7640 1.5738
+#> 494: 93.4937 -5.9217 -0.1485 2.2388 -0.9687 3.4940 3.3182 0.3172 0.3805 0.1865 5.7639 1.5740
+#> 495: 93.4945 -5.9213 -0.1485 2.2386 -0.9688 3.4998 3.3151 0.3172 0.3808 0.1866 5.7638 1.5742
+#> 496: 93.4953 -5.9208 -0.1486 2.2384 -0.9688 3.5036 3.3123 0.3172 0.3810 0.1867 5.7635 1.5745
+#> 497: 93.4969 -5.9205 -0.1487 2.2382 -0.9689 3.5064 3.3109 0.3172 0.3813 0.1868 5.7637 1.5747
+#> 498: 93.4980 -5.9205 -0.1488 2.2379 -0.9690 3.5057 3.3104 0.3171 0.3815 0.1868 5.7639 1.5752
+#> 499: 93.4999 -5.9205 -0.1488 2.2377 -0.9691 3.5095 3.3102 0.3171 0.3817 0.1869 5.7639 1.5756
+#> 500: 93.5013 -5.9210 -0.1489 2.2376 -0.9691 3.5093 3.3135 0.3171 0.3818 0.1869 5.7644 1.5758
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_alpha |
+#> |.....................| log_beta |sigma_parent | sigma_A1 | o1 |
+#> |.....................| o2 | o3 | o4 | o5 |
+#> | 1| 470.09130 | 1.000 | -1.000 | -0.9119 | -0.8960 |
+#> |.....................| -0.8494 | -0.8528 | -0.8683 | -0.8768 |
+#> |.....................| -0.8744 | -0.8681 | -0.8700 | -0.8694 |
+#> | U| 470.0913 | 94.11 | -5.371 | -0.9909 | -0.1965 |
+#> |.....................| 2.121 | 1.952 | 1.178 | 0.7545 |
+#> |.....................| 0.8769 | 1.189 | 1.095 | 1.127 |
+#> | X| 470.0913 | 94.11 | 0.004648 | 0.2707 | 0.8216 |
+#> |.....................| 8.339 | 1.952 | 1.178 | 0.7545 |
+#> |.....................| 0.8769 | 1.189 | 1.095 | 1.127 |
+#> | G| Gill Diff. | 72.01 | 2.213 | -0.2476 | -0.3163 |
+#> |.....................| -0.8532 | -32.82 | -13.44 | 9.552 |
+#> |.....................| 11.72 | -12.16 | -9.599 | -9.049 |
+#> | 2| 5180.4321 | 0.1393 | -1.026 | -0.9090 | -0.8922 |
+#> |.....................| -0.8392 | -0.4605 | -0.7077 | -0.9910 |
+#> |.....................| -1.014 | -0.7228 | -0.7553 | -0.7612 |
+#> | U| 5180.4321 | 13.11 | -5.398 | -0.9880 | -0.1927 |
+#> |.....................| 2.131 | 2.334 | 1.272 | 0.6684 |
+#> |.....................| 0.7541 | 1.362 | 1.220 | 1.248 |
+#> | X| 5180.4321 | 13.11 | 0.004526 | 0.2713 | 0.8247 |
+#> |.....................| 8.424 | 2.334 | 1.272 | 0.6684 |
+#> |.....................| 0.7541 | 1.362 | 1.220 | 1.248 |
+#> | 3| 529.93288 | 0.9139 | -1.003 | -0.9116 | -0.8956 |
+#> |.....................| -0.8484 | -0.8135 | -0.8523 | -0.8883 |
+#> |.....................| -0.8884 | -0.8536 | -0.8585 | -0.8585 |
+#> | U| 529.93288 | 86.01 | -5.374 | -0.9906 | -0.1961 |
+#> |.....................| 2.122 | 1.990 | 1.187 | 0.7459 |
+#> |.....................| 0.8647 | 1.206 | 1.107 | 1.139 |
+#> | X| 529.93288 | 86.01 | 0.004635 | 0.2708 | 0.8219 |
+#> |.....................| 8.347 | 1.990 | 1.187 | 0.7459 |
+#> |.....................| 0.8647 | 1.206 | 1.107 | 1.139 |
+#> | 4| 469.96296 | 0.9914 | -1.000 | -0.9119 | -0.8959 |
+#> |.....................| -0.8493 | -0.8489 | -0.8667 | -0.8780 |
+#> |.....................| -0.8758 | -0.8667 | -0.8689 | -0.8683 |
+#> | U| 469.96296 | 93.30 | -5.372 | -0.9909 | -0.1965 |
+#> |.....................| 2.121 | 1.955 | 1.179 | 0.7536 |
+#> |.....................| 0.8757 | 1.191 | 1.096 | 1.128 |
+#> | X| 469.96296 | 93.30 | 0.004646 | 0.2707 | 0.8216 |
+#> |.....................| 8.339 | 1.955 | 1.179 | 0.7536 |
+#> |.....................| 0.8757 | 1.191 | 1.096 | 1.128 |
+#> | F| Forward Diff. | -91.63 | 2.121 | -0.4143 | -0.3985 |
+#> |.....................| -1.124 | -34.23 | -12.87 | 9.567 |
+#> |.....................| 8.592 | -11.79 | -9.469 | -8.518 |
+#> | 5| 469.41305 | 0.9973 | -1.001 | -0.9118 | -0.8959 |
+#> |.....................| -0.8491 | -0.8424 | -0.8642 | -0.8798 |
+#> |.....................| -0.8776 | -0.8644 | -0.8670 | -0.8666 |
+#> | U| 469.41305 | 93.85 | -5.372 | -0.9908 | -0.1964 |
+#> |.....................| 2.121 | 1.962 | 1.180 | 0.7523 |
+#> |.....................| 0.8741 | 1.193 | 1.098 | 1.130 |
+#> | X| 469.41305 | 93.85 | 0.004644 | 0.2707 | 0.8217 |
+#> |.....................| 8.341 | 1.962 | 1.180 | 0.7523 |
+#> |.....................| 0.8741 | 1.193 | 1.098 | 1.130 |
+#> | F| Forward Diff. | 19.88 | 2.163 | -0.2989 | -0.3449 |
+#> |.....................| -0.9473 | -32.84 | -13.22 | 8.952 |
+#> |.....................| 11.37 | -11.75 | -9.421 | -8.530 |
+#> | 6| 469.13124 | 0.9930 | -1.001 | -0.9118 | -0.8958 |
+#> |.....................| -0.8489 | -0.8354 | -0.8614 | -0.8817 |
+#> |.....................| -0.8801 | -0.8619 | -0.8650 | -0.8648 |
+#> | U| 469.13124 | 93.45 | -5.373 | -0.9908 | -0.1963 |
+#> |.....................| 2.121 | 1.969 | 1.182 | 0.7508 |
+#> |.....................| 0.8719 | 1.196 | 1.100 | 1.132 |
+#> | X| 469.13124 | 93.45 | 0.004642 | 0.2708 | 0.8218 |
+#> |.....................| 8.343 | 1.969 | 1.182 | 0.7508 |
+#> |.....................| 0.8719 | 1.196 | 1.100 | 1.132 |
+#> | F| Forward Diff. | -60.06 | 2.108 | -0.3845 | -0.3876 |
+#> |.....................| -1.088 | -32.82 | -12.89 | 8.720 |
+#> |.....................| 9.663 | -11.60 | -9.301 | -8.348 |
+#> | 7| 468.71336 | 0.9979 | -1.002 | -0.9117 | -0.8957 |
+#> |.....................| -0.8487 | -0.8285 | -0.8586 | -0.8835 |
+#> |.....................| -0.8823 | -0.8594 | -0.8631 | -0.8630 |
+#> | U| 468.71336 | 93.91 | -5.373 | -0.9907 | -0.1962 |
+#> |.....................| 2.122 | 1.975 | 1.183 | 0.7495 |
+#> |.....................| 0.8700 | 1.199 | 1.102 | 1.134 |
+#> | X| 468.71336 | 93.91 | 0.004640 | 0.2708 | 0.8218 |
+#> |.....................| 8.345 | 1.975 | 1.183 | 0.7495 |
+#> |.....................| 0.8700 | 1.199 | 1.102 | 1.134 |
+#> | F| Forward Diff. | 31.80 | 2.131 | -0.3007 | -0.3556 |
+#> |.....................| -0.9543 | -30.66 | -12.35 | 8.979 |
+#> |.....................| 9.681 | -11.54 | -9.231 | -8.330 |
+#> | 8| 468.42878 | 0.9931 | -1.002 | -0.9116 | -0.8956 |
+#> |.....................| -0.8484 | -0.8217 | -0.8559 | -0.8855 |
+#> |.....................| -0.8845 | -0.8568 | -0.8610 | -0.8612 |
+#> | U| 468.42878 | 93.46 | -5.373 | -0.9906 | -0.1962 |
+#> |.....................| 2.122 | 1.982 | 1.185 | 0.7480 |
+#> |.....................| 0.8681 | 1.202 | 1.105 | 1.136 |
+#> | X| 468.42878 | 93.46 | 0.004638 | 0.2708 | 0.8219 |
+#> |.....................| 8.346 | 1.982 | 1.185 | 0.7480 |
+#> |.....................| 0.8681 | 1.202 | 1.105 | 1.136 |
+#> | F| Forward Diff. | -55.97 | 2.081 | -0.3855 | -0.3928 |
+#> |.....................| -1.100 | -30.89 | -12.11 | 8.596 |
+#> |.....................| 9.353 | -11.36 | -9.087 | -8.137 |
+#> | 9| 468.02528 | 0.9977 | -1.003 | -0.9115 | -0.8955 |
+#> |.....................| -0.8482 | -0.8148 | -0.8531 | -0.8875 |
+#> |.....................| -0.8866 | -0.8542 | -0.8589 | -0.8593 |
+#> | U| 468.02528 | 93.90 | -5.374 | -0.9905 | -0.1961 |
+#> |.....................| 2.122 | 1.989 | 1.187 | 0.7465 |
+#> |.....................| 0.8662 | 1.206 | 1.107 | 1.138 |
+#> | X| 468.02528 | 93.90 | 0.004636 | 0.2708 | 0.8220 |
+#> |.....................| 8.348 | 1.989 | 1.187 | 0.7465 |
+#> |.....................| 0.8662 | 1.206 | 1.107 | 1.138 |
+#> | F| Forward Diff. | 28.40 | 2.101 | -0.3066 | -0.3612 |
+#> |.....................| -0.9721 | -29.21 | -11.91 | 8.561 |
+#> |.....................| 9.360 | -11.31 | -9.026 | -8.108 |
+#> | 10| 467.76129 | 0.9930 | -1.003 | -0.9115 | -0.8954 |
+#> |.....................| -0.8479 | -0.8081 | -0.8503 | -0.8895 |
+#> |.....................| -0.8888 | -0.8515 | -0.8567 | -0.8574 |
+#> | U| 467.76129 | 93.46 | -5.374 | -0.9905 | -0.1960 |
+#> |.....................| 2.122 | 1.995 | 1.188 | 0.7450 |
+#> |.....................| 0.8643 | 1.209 | 1.109 | 1.140 |
+#> | X| 467.76129 | 93.46 | 0.004633 | 0.2708 | 0.8220 |
+#> |.....................| 8.351 | 1.995 | 1.188 | 0.7450 |
+#> |.....................| 0.8643 | 1.209 | 1.109 | 1.140 |
+#> | F| Forward Diff. | -56.33 | 2.052 | -0.3905 | -0.3944 |
+#> |.....................| -1.108 | -29.62 | -11.80 | 8.124 |
+#> |.....................| 9.000 | -11.14 | -8.878 | -7.912 |
+#> | 11| 467.36507 | 0.9976 | -1.004 | -0.9114 | -0.8953 |
+#> |.....................| -0.8477 | -0.8013 | -0.8475 | -0.8914 |
+#> |.....................| -0.8910 | -0.8487 | -0.8545 | -0.8554 |
+#> | U| 467.36507 | 93.88 | -5.375 | -0.9904 | -0.1959 |
+#> |.....................| 2.123 | 2.002 | 1.190 | 0.7435 |
+#> |.....................| 0.8624 | 1.212 | 1.112 | 1.142 |
+#> | X| 467.36507 | 93.88 | 0.004631 | 0.2708 | 0.8221 |
+#> |.....................| 8.353 | 2.002 | 1.190 | 0.7435 |
+#> |.....................| 0.8624 | 1.212 | 1.112 | 1.142 |
+#> | F| Forward Diff. | 25.62 | 2.072 | -0.2964 | -0.3658 |
+#> |.....................| -0.9890 | -26.78 | -10.91 | 8.547 |
+#> |.....................| 9.002 | -11.08 | -8.799 | -7.879 |
+#> | 12| 467.13453 | 0.9928 | -1.004 | -0.9113 | -0.8952 |
+#> |.....................| -0.8474 | -0.7947 | -0.8448 | -0.8935 |
+#> |.....................| -0.8932 | -0.8459 | -0.8523 | -0.8534 |
+#> | U| 467.13453 | 93.43 | -5.376 | -0.9903 | -0.1958 |
+#> |.....................| 2.123 | 2.008 | 1.191 | 0.7419 |
+#> |.....................| 0.8604 | 1.215 | 1.114 | 1.145 |
+#> | X| 467.13453 | 93.43 | 0.004628 | 0.2709 | 0.8222 |
+#> |.....................| 8.355 | 2.008 | 1.191 | 0.7419 |
+#> |.....................| 0.8604 | 1.215 | 1.114 | 1.145 |
+#> | F| Forward Diff. | -59.86 | 2.021 | -0.3893 | -0.4093 |
+#> |.....................| -1.140 | -28.00 | -11.13 | 7.926 |
+#> |.....................| 9.918 | -10.90 | -8.684 | -7.680 |
+#> | 13| 466.72836 | 0.9971 | -1.005 | -0.9112 | -0.8951 |
+#> |.....................| -0.8471 | -0.7882 | -0.8421 | -0.8957 |
+#> |.....................| -0.8959 | -0.8428 | -0.8499 | -0.8513 |
+#> | U| 466.72836 | 93.84 | -5.376 | -0.9902 | -0.1956 |
+#> |.....................| 2.123 | 2.015 | 1.193 | 0.7403 |
+#> |.....................| 0.8581 | 1.219 | 1.117 | 1.147 |
+#> | X| 466.72836 | 93.84 | 0.004626 | 0.2709 | 0.8223 |
+#> |.....................| 8.358 | 2.015 | 1.193 | 0.7403 |
+#> |.....................| 0.8581 | 1.219 | 1.117 | 1.147 |
+#> | F| Forward Diff. | 18.13 | 2.039 | -0.3145 | -0.3694 |
+#> |.....................| -1.015 | -26.10 | -10.63 | 8.044 |
+#> |.....................| 8.616 | -10.80 | -8.580 | -7.637 |
+#> | 14| 466.53378 | 0.9925 | -1.005 | -0.9111 | -0.8950 |
+#> |.....................| -0.8468 | -0.7815 | -0.8394 | -0.8978 |
+#> |.....................| -0.8981 | -0.8400 | -0.8477 | -0.8494 |
+#> | U| 466.53378 | 93.40 | -5.377 | -0.9901 | -0.1956 |
+#> |.....................| 2.123 | 2.021 | 1.195 | 0.7387 |
+#> |.....................| 0.8562 | 1.222 | 1.119 | 1.149 |
+#> | X| 466.53378 | 93.40 | 0.004623 | 0.2709 | 0.8224 |
+#> |.....................| 8.360 | 2.021 | 1.195 | 0.7387 |
+#> |.....................| 0.8562 | 1.222 | 1.119 | 1.149 |
+#> | F| Forward Diff. | -63.81 | 1.989 | -0.4067 | -0.4178 |
+#> |.....................| -1.167 | -26.39 | -10.45 | 7.924 |
+#> |.....................| 8.221 | -10.62 | -8.445 | -7.432 |
+#> | 15| 466.13347 | 0.9972 | -1.006 | -0.9110 | -0.8949 |
+#> |.....................| -0.8464 | -0.7752 | -0.8368 | -0.9000 |
+#> |.....................| -0.9002 | -0.8369 | -0.8452 | -0.8472 |
+#> | U| 466.13347 | 93.85 | -5.377 | -0.9900 | -0.1954 |
+#> |.....................| 2.124 | 2.027 | 1.196 | 0.7370 |
+#> |.....................| 0.8543 | 1.226 | 1.122 | 1.152 |
+#> | X| 466.13347 | 93.85 | 0.004620 | 0.2709 | 0.8225 |
+#> |.....................| 8.363 | 2.027 | 1.196 | 0.7370 |
+#> |.....................| 0.8543 | 1.226 | 1.122 | 1.152 |
+#> | F| Forward Diff. | 18.92 | 2.012 | -0.3108 | -0.3757 |
+#> |.....................| -1.021 | -25.52 | -10.81 | 7.279 |
+#> |.....................| 9.661 | -10.54 | -8.331 | -7.395 |
+#> | 16| 465.94504 | 0.9925 | -1.006 | -0.9109 | -0.8948 |
+#> |.....................| -0.8461 | -0.7686 | -0.8339 | -0.9019 |
+#> |.....................| -0.9028 | -0.8341 | -0.8430 | -0.8453 |
+#> | U| 465.94504 | 93.41 | -5.378 | -0.9899 | -0.1953 |
+#> |.....................| 2.124 | 2.034 | 1.198 | 0.7356 |
+#> |.....................| 0.8521 | 1.229 | 1.124 | 1.154 |
+#> | X| 465.94504 | 93.41 | 0.004618 | 0.2709 | 0.8226 |
+#> |.....................| 8.366 | 2.034 | 1.198 | 0.7356 |
+#> |.....................| 0.8521 | 1.229 | 1.124 | 1.154 |
+#> | F| Forward Diff. | -61.65 | 1.961 | -0.4097 | -0.4254 |
+#> |.....................| -1.181 | -25.22 | -10.13 | 7.338 |
+#> |.....................| 9.206 | -10.38 | -8.223 | -7.205 |
+#> | 17| 465.56754 | 0.9973 | -1.007 | -0.9108 | -0.8946 |
+#> |.....................| -0.8457 | -0.7626 | -0.8312 | -0.9037 |
+#> |.....................| -0.9058 | -0.8309 | -0.8405 | -0.8432 |
+#> | U| 465.56754 | 93.86 | -5.378 | -0.9898 | -0.1952 |
+#> |.....................| 2.125 | 2.040 | 1.199 | 0.7342 |
+#> |.....................| 0.8494 | 1.233 | 1.127 | 1.156 |
+#> | X| 465.56754 | 93.86 | 0.004615 | 0.2710 | 0.8227 |
+#> |.....................| 8.369 | 2.040 | 1.199 | 0.7342 |
+#> |.....................| 0.8494 | 1.233 | 1.127 | 1.156 |
+#> | F| Forward Diff. | 20.78 | 1.982 | -0.3060 | -0.3796 |
+#> |.....................| -1.026 | -23.61 | -9.859 | 7.282 |
+#> |.....................| 6.603 | -10.29 | -8.096 | -7.167 |
+#> | 18| 465.36858 | 0.9928 | -1.008 | -0.9107 | -0.8945 |
+#> |.....................| -0.8454 | -0.7560 | -0.8284 | -0.9059 |
+#> |.....................| -0.9077 | -0.8278 | -0.8381 | -0.8410 |
+#> | U| 465.36858 | 93.44 | -5.379 | -0.9897 | -0.1950 |
+#> |.....................| 2.125 | 2.046 | 1.201 | 0.7326 |
+#> |.....................| 0.8477 | 1.237 | 1.130 | 1.159 |
+#> | X| 465.36858 | 93.44 | 0.004612 | 0.2710 | 0.8228 |
+#> |.....................| 8.372 | 2.046 | 1.201 | 0.7326 |
+#> |.....................| 0.8477 | 1.237 | 1.130 | 1.159 |
+#> | F| Forward Diff. | -55.43 | 1.935 | -0.4028 | -0.4254 |
+#> |.....................| -1.182 | -23.34 | -9.189 | 7.305 |
+#> |.....................| 7.555 | -10.07 | -7.946 | -6.960 |
+#> | 19| 465.01863 | 0.9972 | -1.008 | -0.9105 | -0.8943 |
+#> |.....................| -0.8449 | -0.7499 | -0.8257 | -0.9082 |
+#> |.....................| -0.9092 | -0.8240 | -0.8352 | -0.8386 |
+#> | U| 465.01863 | 93.84 | -5.380 | -0.9895 | -0.1948 |
+#> |.....................| 2.125 | 2.052 | 1.203 | 0.7308 |
+#> |.....................| 0.8464 | 1.241 | 1.133 | 1.161 |
+#> | X| 465.01863 | 93.84 | 0.004609 | 0.2710 | 0.8230 |
+#> |.....................| 8.376 | 2.052 | 1.203 | 0.7308 |
+#> |.....................| 0.8464 | 1.241 | 1.133 | 1.161 |
+#> | F| Forward Diff. | 18.74 | 1.956 | -0.3105 | -0.3857 |
+#> |.....................| -1.041 | -22.36 | -9.386 | 7.151 |
+#> |.....................| 7.639 | -9.969 | -7.832 | -6.900 |
+#> | 20| 464.81883 | 0.9930 | -1.009 | -0.9104 | -0.8942 |
+#> |.....................| -0.8445 | -0.7435 | -0.8230 | -0.9105 |
+#> |.....................| -0.9115 | -0.8207 | -0.8326 | -0.8363 |
+#> | U| 464.81883 | 93.45 | -5.381 | -0.9894 | -0.1947 |
+#> |.....................| 2.126 | 2.058 | 1.204 | 0.7291 |
+#> |.....................| 0.8444 | 1.245 | 1.136 | 1.164 |
+#> | X| 464.81883 | 93.45 | 0.004605 | 0.2710 | 0.8231 |
+#> |.....................| 8.380 | 2.058 | 1.204 | 0.7291 |
+#> |.....................| 0.8444 | 1.245 | 1.136 | 1.164 |
+#> | F| Forward Diff. | -51.40 | 1.910 | -0.3971 | -0.4173 |
+#> |.....................| -1.192 | -21.85 | -8.569 | 7.088 |
+#> |.....................| 7.257 | -9.784 | -7.694 | -6.698 |
+#> | 21| 464.49434 | 0.9973 | -1.010 | -0.9102 | -0.8940 |
+#> |.....................| -0.8439 | -0.7380 | -0.8206 | -0.9131 |
+#> |.....................| -0.9139 | -0.8168 | -0.8296 | -0.8338 |
+#> | U| 464.49434 | 93.85 | -5.381 | -0.9892 | -0.1945 |
+#> |.....................| 2.126 | 2.064 | 1.206 | 0.7271 |
+#> |.....................| 0.8423 | 1.250 | 1.139 | 1.167 |
+#> | X| 464.49434 | 93.85 | 0.004602 | 0.2711 | 0.8233 |
+#> |.....................| 8.385 | 2.064 | 1.206 | 0.7271 |
+#> |.....................| 0.8423 | 1.250 | 1.139 | 1.167 |
+#> | F| Forward Diff. | 20.43 | 1.927 | -0.3065 | -0.3887 |
+#> |.....................| -1.043 | -20.85 | -8.676 | 6.819 |
+#> |.....................| 7.291 | -9.652 | -7.555 | -6.636 |
+#> | 22| 464.27900 | 0.9935 | -1.011 | -0.9101 | -0.8938 |
+#> |.....................| -0.8433 | -0.7319 | -0.8180 | -0.9156 |
+#> |.....................| -0.9164 | -0.8129 | -0.8266 | -0.8314 |
+#> | U| 464.279 | 93.50 | -5.382 | -0.9891 | -0.1943 |
+#> |.....................| 2.127 | 2.070 | 1.207 | 0.7252 |
+#> |.....................| 0.8401 | 1.255 | 1.142 | 1.169 |
+#> | X| 464.279 | 93.50 | 0.004598 | 0.2711 | 0.8234 |
+#> |.....................| 8.389 | 2.070 | 1.207 | 0.7252 |
+#> |.....................| 0.8401 | 1.255 | 1.142 | 1.169 |
+#> | F| Forward Diff. | -42.65 | 1.884 | -0.3905 | -0.4168 |
+#> |.....................| -1.174 | -21.12 | -8.566 | 6.431 |
+#> |.....................| 8.301 | -9.439 | -7.399 | -6.436 |
+#> | 23| 463.98221 | 0.9971 | -1.012 | -0.9099 | -0.8935 |
+#> |.....................| -0.8426 | -0.7266 | -0.8156 | -0.9179 |
+#> |.....................| -0.9200 | -0.8088 | -0.8235 | -0.8288 |
+#> | U| 463.98221 | 93.84 | -5.383 | -0.9889 | -0.1940 |
+#> |.....................| 2.128 | 2.075 | 1.209 | 0.7235 |
+#> |.....................| 0.8370 | 1.260 | 1.146 | 1.172 |
+#> | X| 463.98221 | 93.84 | 0.004593 | 0.2711 | 0.8236 |
+#> |.....................| 8.395 | 2.075 | 1.209 | 0.7235 |
+#> |.....................| 0.8370 | 1.260 | 1.146 | 1.172 |
+#> | F| Forward Diff. | 17.69 | 1.891 | -0.3039 | -0.3774 |
+#> |.....................| -1.038 | -20.36 | -8.704 | 6.334 |
+#> |.....................| 6.886 | -9.291 | -7.246 | -6.355 |
+#> | 24| 463.80345 | 0.9930 | -1.013 | -0.9097 | -0.8933 |
+#> |.....................| -0.8421 | -0.7205 | -0.8127 | -0.9199 |
+#> |.....................| -0.9227 | -0.8053 | -0.8209 | -0.8265 |
+#> | U| 463.80345 | 93.45 | -5.384 | -0.9887 | -0.1939 |
+#> |.....................| 2.128 | 2.081 | 1.210 | 0.7220 |
+#> |.....................| 0.8346 | 1.264 | 1.148 | 1.175 |
+#> | X| 463.80345 | 93.45 | 0.004590 | 0.2712 | 0.8238 |
+#> |.....................| 8.399 | 2.081 | 1.210 | 0.7220 |
+#> |.....................| 0.8346 | 1.264 | 1.148 | 1.175 |
+#> | F| Forward Diff. | -49.16 | 1.846 | -0.3979 | -0.4233 |
+#> |.....................| -1.191 | -20.11 | -8.128 | 6.150 |
+#> |.....................| 7.842 | -9.114 | -7.113 | -6.163 |
+#> | 25| 463.50095 | 0.9970 | -1.014 | -0.9095 | -0.8930 |
+#> |.....................| -0.8413 | -0.7152 | -0.8100 | -0.9219 |
+#> |.....................| -0.9258 | -0.8011 | -0.8178 | -0.8240 |
+#> | U| 463.50095 | 93.83 | -5.385 | -0.9885 | -0.1936 |
+#> |.....................| 2.129 | 2.086 | 1.212 | 0.7205 |
+#> |.....................| 0.8318 | 1.269 | 1.152 | 1.178 |
+#> | X| 463.50095 | 93.83 | 0.004585 | 0.2712 | 0.8240 |
+#> |.....................| 8.406 | 2.086 | 1.212 | 0.7205 |
+#> |.....................| 0.8318 | 1.269 | 1.152 | 1.178 |
+#> | F| Forward Diff. | 15.76 | 1.857 | -0.2989 | -0.3817 |
+#> |.....................| -1.050 | -19.47 | -8.354 | 5.597 |
+#> |.....................| 5.177 | -8.956 | -6.950 | -6.091 |
+#> | 26| 463.33971 | 0.9930 | -1.014 | -0.9093 | -0.8928 |
+#> |.....................| -0.8408 | -0.7088 | -0.8070 | -0.9237 |
+#> |.....................| -0.9274 | -0.7974 | -0.8150 | -0.8217 |
+#> | U| 463.33971 | 93.45 | -5.386 | -0.9883 | -0.1934 |
+#> |.....................| 2.129 | 2.092 | 1.214 | 0.7192 |
+#> |.....................| 0.8304 | 1.273 | 1.155 | 1.180 |
+#> | X| 463.33971 | 93.45 | 0.004581 | 0.2712 | 0.8242 |
+#> |.....................| 8.411 | 2.092 | 1.214 | 0.7192 |
+#> |.....................| 0.8304 | 1.273 | 1.155 | 1.180 |
+#> | F| Forward Diff. | -49.38 | 1.817 | -0.3945 | -0.4254 |
+#> |.....................| -1.192 | -18.49 | -7.219 | 6.140 |
+#> |.....................| 6.147 | -8.752 | -6.775 | -5.892 |
+#> | 27| 463.06378 | 0.9971 | -1.016 | -0.9091 | -0.8925 |
+#> |.....................| -0.8398 | -0.7035 | -0.8044 | -0.9255 |
+#> |.....................| -0.9274 | -0.7927 | -0.8116 | -0.8189 |
+#> | U| 463.06378 | 93.84 | -5.387 | -0.9881 | -0.1930 |
+#> |.....................| 2.130 | 2.097 | 1.215 | 0.7178 |
+#> |.....................| 0.8305 | 1.279 | 1.159 | 1.184 |
+#> | X| 463.06378 | 93.84 | 0.004575 | 0.2713 | 0.8245 |
+#> |.....................| 8.419 | 2.097 | 1.215 | 0.7178 |
+#> |.....................| 0.8305 | 1.279 | 1.159 | 1.184 |
+#> | F| Forward Diff. | 17.15 | 1.839 | -0.2941 | -0.3829 |
+#> |.....................| -1.046 | -18.21 | -7.786 | 5.595 |
+#> |.....................| 7.714 | -8.592 | -6.652 | -5.814 |
+#> | 28| 462.87224 | 0.9938 | -1.017 | -0.9088 | -0.8922 |
+#> |.....................| -0.8390 | -0.6982 | -0.8019 | -0.9277 |
+#> |.....................| -0.9311 | -0.7885 | -0.8085 | -0.8163 |
+#> | U| 462.87224 | 93.52 | -5.388 | -0.9879 | -0.1927 |
+#> |.....................| 2.131 | 2.102 | 1.217 | 0.7161 |
+#> |.....................| 0.8272 | 1.284 | 1.162 | 1.186 |
+#> | X| 462.87224 | 93.52 | 0.004570 | 0.2713 | 0.8247 |
+#> |.....................| 8.425 | 2.102 | 1.217 | 0.7161 |
+#> |.....................| 0.8272 | 1.284 | 1.162 | 1.186 |
+#> | F| Forward Diff. | -35.81 | 1.797 | -0.3699 | -0.4180 |
+#> |.....................| -1.164 | -17.54 | -6.949 | 5.683 |
+#> |.....................| 5.938 | -8.368 | -6.484 | -5.617 |
+#> | 29| 462.64279 | 0.9976 | -1.018 | -0.9085 | -0.8918 |
+#> |.....................| -0.8379 | -0.6938 | -0.7998 | -0.9297 |
+#> |.....................| -0.9347 | -0.7837 | -0.8051 | -0.8136 |
+#> | U| 462.64279 | 93.88 | -5.390 | -0.9876 | -0.1923 |
+#> |.....................| 2.132 | 2.107 | 1.218 | 0.7146 |
+#> |.....................| 0.8240 | 1.289 | 1.166 | 1.189 |
+#> | X| 462.64279 | 93.88 | 0.004563 | 0.2714 | 0.8250 |
+#> |.....................| 8.435 | 2.107 | 1.218 | 0.7146 |
+#> |.....................| 0.8240 | 1.289 | 1.166 | 1.189 |
+#> | F| Forward Diff. | 23.89 | 1.802 | -0.2695 | -0.3764 |
+#> |.....................| -1.014 | -17.48 | -7.590 | 5.234 |
+#> |.....................| 7.275 | -8.199 | -6.306 | -5.540 |
+#> | 30| 462.43086 | 0.9946 | -1.020 | -0.9083 | -0.8914 |
+#> |.....................| -0.8367 | -0.6890 | -0.7974 | -0.9317 |
+#> |.....................| -0.9381 | -0.7789 | -0.8017 | -0.8108 |
+#> | U| 462.43086 | 93.61 | -5.391 | -0.9873 | -0.1919 |
+#> |.....................| 2.134 | 2.111 | 1.219 | 0.7131 |
+#> |.....................| 0.8211 | 1.295 | 1.169 | 1.193 |
+#> | X| 462.43086 | 93.61 | 0.004556 | 0.2715 | 0.8254 |
+#> |.....................| 8.445 | 2.111 | 1.219 | 0.7131 |
+#> |.....................| 0.8211 | 1.295 | 1.169 | 1.193 |
+#> | F| Forward Diff. | -22.12 | 1.763 | -0.3409 | -0.4033 |
+#> |.....................| -1.105 | -16.76 | -6.743 | 5.132 |
+#> |.....................| 5.573 | -7.935 | -6.123 | -5.337 |
+#> | 31| 462.24769 | 0.9981 | -1.021 | -0.9079 | -0.8909 |
+#> |.....................| -0.8355 | -0.6838 | -0.7950 | -0.9332 |
+#> |.....................| -0.9404 | -0.7741 | -0.7984 | -0.8080 |
+#> | U| 462.24769 | 93.94 | -5.393 | -0.9870 | -0.1915 |
+#> |.....................| 2.135 | 2.117 | 1.221 | 0.7120 |
+#> |.....................| 0.8190 | 1.301 | 1.173 | 1.196 |
+#> | X| 462.24769 | 93.94 | 0.004549 | 0.2715 | 0.8258 |
+#> |.....................| 8.455 | 2.117 | 1.221 | 0.7120 |
+#> |.....................| 0.8190 | 1.301 | 1.173 | 1.196 |
+#> | F| Forward Diff. | 32.76 | 1.771 | -0.2440 | -0.3645 |
+#> |.....................| -0.9678 | -16.08 | -6.874 | 5.077 |
+#> |.....................| 5.606 | -7.758 | -5.959 | -5.256 |
+#> | 32| 462.04894 | 0.9949 | -1.023 | -0.9076 | -0.8904 |
+#> |.....................| -0.8341 | -0.6790 | -0.7932 | -0.9353 |
+#> |.....................| -0.9395 | -0.7687 | -0.7947 | -0.8049 |
+#> | U| 462.04894 | 93.63 | -5.395 | -0.9866 | -0.1909 |
+#> |.....................| 2.136 | 2.121 | 1.222 | 0.7104 |
+#> |.....................| 0.8198 | 1.307 | 1.177 | 1.199 |
+#> | X| 462.04894 | 93.63 | 0.004540 | 0.2716 | 0.8262 |
+#> |.....................| 8.467 | 2.121 | 1.222 | 0.7104 |
+#> |.....................| 0.8198 | 1.307 | 1.177 | 1.199 |
+#> | F| Forward Diff. | -16.92 | 1.743 | -0.3189 | -0.3951 |
+#> |.....................| -1.072 | -15.84 | -6.430 | 4.847 |
+#> |.....................| 5.467 | -7.483 | -5.756 | -5.023 |
+#> | 33| 461.88553 | 0.9980 | -1.025 | -0.9073 | -0.8898 |
+#> |.....................| -0.8327 | -0.6736 | -0.7912 | -0.9375 |
+#> |.....................| -0.9397 | -0.7637 | -0.7912 | -0.8019 |
+#> | U| 461.88553 | 93.92 | -5.397 | -0.9863 | -0.1904 |
+#> |.....................| 2.138 | 2.126 | 1.223 | 0.7088 |
+#> |.....................| 0.8197 | 1.313 | 1.181 | 1.203 |
+#> | X| 461.88553 | 93.92 | 0.004531 | 0.2716 | 0.8266 |
+#> |.....................| 8.479 | 2.126 | 1.223 | 0.7088 |
+#> |.....................| 0.8197 | 1.313 | 1.181 | 1.203 |
+#> | F| Forward Diff. | 30.55 | 1.755 | -0.2327 | -0.3563 |
+#> |.....................| -0.9551 | -15.13 | -6.434 | 4.973 |
+#> |.....................| 5.515 | -7.304 | -5.584 | -4.904 |
+#> | 34| 461.69674 | 0.9949 | -1.028 | -0.9069 | -0.8892 |
+#> |.....................| -0.8309 | -0.6692 | -0.7896 | -0.9402 |
+#> |.....................| -0.9399 | -0.7583 | -0.7876 | -0.7990 |
+#> | U| 461.69674 | 93.63 | -5.400 | -0.9859 | -0.1897 |
+#> |.....................| 2.139 | 2.131 | 1.224 | 0.7067 |
+#> |.....................| 0.8195 | 1.320 | 1.185 | 1.206 |
+#> | X| 461.69674 | 93.63 | 0.004519 | 0.2717 | 0.8272 |
+#> |.....................| 8.494 | 2.131 | 1.224 | 0.7067 |
+#> |.....................| 0.8195 | 1.320 | 1.185 | 1.206 |
+#> | F| Forward Diff. | -16.57 | 1.720 | -0.3086 | -0.3856 |
+#> |.....................| -1.039 | -14.73 | -5.908 | 4.823 |
+#> |.....................| 5.359 | -7.008 | -5.393 | -4.695 |
+#> | 35| 461.54208 | 0.9978 | -1.031 | -0.9065 | -0.8885 |
+#> |.....................| -0.8293 | -0.6648 | -0.7883 | -0.9440 |
+#> |.....................| -0.9414 | -0.7533 | -0.7842 | -0.7963 |
+#> | U| 461.54208 | 93.91 | -5.402 | -0.9855 | -0.1891 |
+#> |.....................| 2.141 | 2.135 | 1.225 | 0.7038 |
+#> |.....................| 0.8182 | 1.325 | 1.189 | 1.209 |
+#> | X| 461.54208 | 93.91 | 0.004507 | 0.2718 | 0.8277 |
+#> |.....................| 8.508 | 2.135 | 1.225 | 0.7038 |
+#> |.....................| 0.8182 | 1.325 | 1.189 | 1.209 |
+#> | F| Forward Diff. | 27.49 | 1.722 | -0.2172 | -0.3438 |
+#> |.....................| -0.9069 | -13.76 | -5.979 | 4.702 |
+#> |.....................| 5.353 | -6.828 | -5.231 | -4.587 |
+#> | 36| 461.38014 | 0.9949 | -1.034 | -0.9061 | -0.8878 |
+#> |.....................| -0.8274 | -0.6624 | -0.7872 | -0.9482 |
+#> |.....................| -0.9437 | -0.7482 | -0.7807 | -0.7935 |
+#> | U| 461.38014 | 93.63 | -5.405 | -0.9851 | -0.1883 |
+#> |.....................| 2.143 | 2.137 | 1.225 | 0.7007 |
+#> |.....................| 0.8162 | 1.332 | 1.192 | 1.212 |
+#> | X| 461.38014 | 93.63 | 0.004492 | 0.2719 | 0.8283 |
+#> |.....................| 8.524 | 2.137 | 1.225 | 0.7007 |
+#> |.....................| 0.8162 | 1.332 | 1.192 | 1.212 |
+#> | F| Forward Diff. | -16.54 | 1.681 | -0.2967 | -0.3702 |
+#> |.....................| -1.003 | -14.15 | -5.693 | 4.358 |
+#> |.....................| 5.078 | -6.560 | -5.051 | -4.397 |
+#> | 37| 461.22820 | 0.9976 | -1.038 | -0.9057 | -0.8870 |
+#> |.....................| -0.8255 | -0.6585 | -0.7854 | -0.9513 |
+#> |.....................| -0.9460 | -0.7433 | -0.7774 | -0.7908 |
+#> | U| 461.2282 | 93.88 | -5.409 | -0.9847 | -0.1876 |
+#> |.....................| 2.145 | 2.141 | 1.226 | 0.6983 |
+#> |.....................| 0.8141 | 1.337 | 1.196 | 1.215 |
+#> | X| 461.2282 | 93.88 | 0.004476 | 0.2720 | 0.8290 |
+#> |.....................| 8.540 | 2.141 | 1.226 | 0.6983 |
+#> |.....................| 0.8141 | 1.337 | 1.196 | 1.215 |
+#> | F| Forward Diff. | 22.68 | 1.675 | -0.2117 | -0.3293 |
+#> |.....................| -0.8651 | -13.27 | -5.458 | 4.237 |
+#> |.....................| 3.708 | -6.326 | -4.874 | -4.289 |
+#> | 38| 461.10880 | 0.9948 | -1.041 | -0.9053 | -0.8864 |
+#> |.....................| -0.8238 | -0.6532 | -0.7845 | -0.9533 |
+#> |.....................| -0.9419 | -0.7394 | -0.7747 | -0.7885 |
+#> | U| 461.1088 | 93.62 | -5.412 | -0.9844 | -0.1869 |
+#> |.....................| 2.146 | 2.146 | 1.227 | 0.6968 |
+#> |.....................| 0.8177 | 1.342 | 1.199 | 1.218 |
+#> | X| 461.1088 | 93.62 | 0.004461 | 0.2720 | 0.8295 |
+#> |.....................| 8.555 | 2.146 | 1.227 | 0.6968 |
+#> |.....................| 0.8177 | 1.342 | 1.199 | 1.218 |
+#> | F| Forward Diff. | -17.23 | 1.655 | -0.2888 | -0.3567 |
+#> |.....................| -0.9524 | -13.71 | -5.652 | 3.877 |
+#> |.....................| 5.125 | -6.149 | -4.743 | -4.110 |
+#> | 39| 460.99174 | 0.9974 | -1.045 | -0.9049 | -0.8856 |
+#> |.....................| -0.8221 | -0.6468 | -0.7824 | -0.9536 |
+#> |.....................| -0.9388 | -0.7360 | -0.7723 | -0.7867 |
+#> | U| 460.99174 | 93.87 | -5.416 | -0.9840 | -0.1862 |
+#> |.....................| 2.148 | 2.153 | 1.228 | 0.6966 |
+#> |.....................| 0.8204 | 1.346 | 1.202 | 1.220 |
+#> | X| 460.99174 | 93.87 | 0.004444 | 0.2721 | 0.8301 |
+#> |.....................| 8.569 | 2.153 | 1.228 | 0.6966 |
+#> |.....................| 0.8204 | 1.346 | 1.202 | 1.220 |
+#> | F| Forward Diff. | 21.44 | 1.663 | -0.2166 | -0.3206 |
+#> |.....................| -0.8444 | -13.00 | -5.647 | 3.881 |
+#> |.....................| 5.370 | -6.036 | -4.631 | -4.039 |
+#> | 40| 460.85317 | 0.9948 | -1.049 | -0.9044 | -0.8849 |
+#> |.....................| -0.8203 | -0.6417 | -0.7791 | -0.9516 |
+#> |.....................| -0.9438 | -0.7341 | -0.7712 | -0.7862 |
+#> | U| 460.85317 | 93.62 | -5.420 | -0.9835 | -0.1854 |
+#> |.....................| 2.150 | 2.158 | 1.230 | 0.6981 |
+#> |.....................| 0.8161 | 1.348 | 1.203 | 1.220 |
+#> | X| 460.85317 | 93.62 | 0.004425 | 0.2722 | 0.8308 |
+#> |.....................| 8.585 | 2.158 | 1.230 | 0.6981 |
+#> |.....................| 0.8161 | 1.348 | 1.203 | 1.220 |
+#> | F| Forward Diff. | -17.08 | 1.613 | -0.2650 | -0.3380 |
+#> |.....................| -0.8994 | -12.83 | -5.261 | 3.879 |
+#> |.....................| 3.650 | -5.911 | -4.518 | -3.985 |
+#> | 41| 460.73362 | 0.9974 | -1.054 | -0.9040 | -0.8841 |
+#> |.....................| -0.8184 | -0.6359 | -0.7754 | -0.9517 |
+#> |.....................| -0.9423 | -0.7308 | -0.7693 | -0.7845 |
+#> | U| 460.73362 | 93.86 | -5.425 | -0.9831 | -0.1846 |
+#> |.....................| 2.152 | 2.163 | 1.232 | 0.6980 |
+#> |.....................| 0.8173 | 1.352 | 1.205 | 1.222 |
+#> | X| 460.73362 | 93.86 | 0.004404 | 0.2723 | 0.8314 |
+#> |.....................| 8.601 | 2.163 | 1.232 | 0.6980 |
+#> |.....................| 0.8173 | 1.352 | 1.205 | 1.222 |
+#> | F| Forward Diff. | 20.68 | 1.612 | -0.1811 | -0.2966 |
+#> |.....................| -0.7710 | -11.91 | -4.976 | 4.011 |
+#> |.....................| 3.788 | -5.788 | -4.468 | -3.936 |
+#> | 42| 460.64877 | 0.9948 | -1.058 | -0.9038 | -0.8835 |
+#> |.....................| -0.8171 | -0.6318 | -0.7737 | -0.9543 |
+#> |.....................| -0.9372 | -0.7272 | -0.7669 | -0.7822 |
+#> | U| 460.64877 | 93.62 | -5.429 | -0.9829 | -0.1841 |
+#> |.....................| 2.153 | 2.167 | 1.233 | 0.6961 |
+#> |.....................| 0.8219 | 1.357 | 1.208 | 1.225 |
+#> | X| 460.64877 | 93.62 | 0.004387 | 0.2723 | 0.8319 |
+#> |.....................| 8.612 | 2.167 | 1.233 | 0.6961 |
+#> |.....................| 0.8219 | 1.357 | 1.208 | 1.225 |
+#> | F| Forward Diff. | -16.17 | 1.594 | -0.2646 | -0.3254 |
+#> |.....................| -0.8335 | -11.77 | -4.666 | 3.810 |
+#> |.....................| 5.289 | -5.625 | -4.348 | -3.754 |
+#> | 43| 460.54180 | 0.9972 | -1.063 | -0.9035 | -0.8829 |
+#> |.....................| -0.8158 | -0.6297 | -0.7745 | -0.9584 |
+#> |.....................| -0.9393 | -0.7227 | -0.7634 | -0.7794 |
+#> | U| 460.5418 | 93.85 | -5.434 | -0.9826 | -0.1834 |
+#> |.....................| 2.154 | 2.169 | 1.233 | 0.6929 |
+#> |.....................| 0.8200 | 1.362 | 1.211 | 1.228 |
+#> | X| 460.5418 | 93.85 | 0.004366 | 0.2724 | 0.8324 |
+#> |.....................| 8.623 | 2.169 | 1.233 | 0.6929 |
+#> |.....................| 0.8200 | 1.362 | 1.211 | 1.228 |
+#> | F| Forward Diff. | 18.48 | 1.582 | -0.1851 | -0.2851 |
+#> |.....................| -0.7462 | -11.38 | -4.808 | 3.651 |
+#> |.....................| 5.261 | -5.402 | -4.159 | -3.623 |
+#> | 44| 460.43711 | 0.9948 | -1.067 | -0.9032 | -0.8823 |
+#> |.....................| -0.8147 | -0.6284 | -0.7753 | -0.9609 |
+#> |.....................| -0.9464 | -0.7199 | -0.7613 | -0.7778 |
+#> | U| 460.43711 | 93.63 | -5.438 | -0.9823 | -0.1829 |
+#> |.....................| 2.156 | 2.171 | 1.232 | 0.6911 |
+#> |.....................| 0.8138 | 1.365 | 1.214 | 1.230 |
+#> | X| 460.43711 | 93.63 | 0.004347 | 0.2724 | 0.8329 |
+#> |.....................| 8.632 | 2.171 | 1.232 | 0.6911 |
+#> |.....................| 0.8138 | 1.365 | 1.214 | 1.230 |
+#> | 45| 460.35910 | 0.9948 | -1.072 | -0.9029 | -0.8817 |
+#> |.....................| -0.8135 | -0.6285 | -0.7770 | -0.9633 |
+#> |.....................| -0.9542 | -0.7172 | -0.7594 | -0.7765 |
+#> | U| 460.3591 | 93.63 | -5.443 | -0.9820 | -0.1822 |
+#> |.....................| 2.157 | 2.170 | 1.231 | 0.6893 |
+#> |.....................| 0.8069 | 1.368 | 1.216 | 1.231 |
+#> | X| 460.3591 | 93.63 | 0.004325 | 0.2725 | 0.8334 |
+#> |.....................| 8.643 | 2.170 | 1.231 | 0.6893 |
+#> |.....................| 0.8069 | 1.368 | 1.216 | 1.231 |
+#> | 46| 460.06586 | 0.9948 | -1.095 | -0.9016 | -0.8789 |
+#> |.....................| -0.8080 | -0.6294 | -0.7850 | -0.9744 |
+#> |.....................| -0.9902 | -0.7052 | -0.7507 | -0.7704 |
+#> | U| 460.06586 | 93.63 | -5.466 | -0.9807 | -0.1794 |
+#> |.....................| 2.162 | 2.170 | 1.227 | 0.6809 |
+#> |.....................| 0.7753 | 1.383 | 1.225 | 1.238 |
+#> | X| 460.06586 | 93.63 | 0.004227 | 0.2728 | 0.8358 |
+#> |.....................| 8.691 | 2.170 | 1.227 | 0.6809 |
+#> |.....................| 0.7753 | 1.383 | 1.225 | 1.238 |
+#> | 47| 459.86897 | 0.9949 | -1.169 | -0.8972 | -0.8697 |
+#> |.....................| -0.7899 | -0.6321 | -0.8109 | -1.010 |
+#> |.....................| -1.107 | -0.6662 | -0.7224 | -0.7508 |
+#> | U| 459.86897 | 93.63 | -5.541 | -0.9763 | -0.1702 |
+#> |.....................| 2.180 | 2.167 | 1.211 | 0.6537 |
+#> |.....................| 0.6731 | 1.429 | 1.256 | 1.260 |
+#> | X| 459.86897 | 93.63 | 0.003924 | 0.2736 | 0.8435 |
+#> |.....................| 8.849 | 2.167 | 1.211 | 0.6537 |
+#> |.....................| 0.6731 | 1.429 | 1.256 | 1.260 |
+#> | F| Forward Diff. | -18.09 | 0.8663 | 0.2544 | 0.003114 |
+#> |.....................| -0.1212 | -11.64 | -7.047 | 0.1395 |
+#> |.....................| -6.727 | -2.881 | -1.866 | -2.263 |
+#> | 48| 458.58262 | 0.9946 | -1.323 | -0.9067 | -0.8597 |
+#> |.....................| -0.7710 | -0.5295 | -0.7001 | -0.9650 |
+#> |.....................| -1.113 | -0.6398 | -0.7228 | -0.7390 |
+#> | U| 458.58262 | 93.60 | -5.695 | -0.9858 | -0.1602 |
+#> |.....................| 2.199 | 2.267 | 1.277 | 0.6880 |
+#> |.....................| 0.6674 | 1.460 | 1.256 | 1.273 |
+#> | X| 458.58262 | 93.60 | 0.003363 | 0.2717 | 0.8520 |
+#> |.....................| 9.019 | 2.267 | 1.277 | 0.6880 |
+#> |.....................| 0.6674 | 1.460 | 1.256 | 1.273 |
+#> | F| Forward Diff. | -24.91 | 0.5848 | -0.03458 | 0.2475 |
+#> |.....................| 0.3762 | -4.573 | -0.04388 | 1.648 |
+#> |.....................| -5.878 | -2.073 | -1.935 | -2.146 |
+#> | 49| 460.44377 | 0.9922 | -1.558 | -0.9059 | -0.8818 |
+#> |.....................| -0.8081 | -0.3861 | -0.8607 | -1.070 |
+#> |.....................| -0.9432 | -0.5131 | -0.5915 | -0.5851 |
+#> | U| 460.44377 | 93.38 | -5.929 | -0.9849 | -0.1824 |
+#> |.....................| 2.162 | 2.407 | 1.182 | 0.6086 |
+#> |.....................| 0.8166 | 1.611 | 1.400 | 1.447 |
+#> | X| 460.44377 | 93.38 | 0.002660 | 0.2719 | 0.8333 |
+#> |.....................| 8.690 | 2.407 | 1.182 | 0.6086 |
+#> |.....................| 0.8166 | 1.611 | 1.400 | 1.447 |
+#> | 50| 458.18867 | 0.9958 | -1.393 | -0.9065 | -0.8663 |
+#> |.....................| -0.7821 | -0.4865 | -0.7479 | -0.9965 |
+#> |.....................| -1.062 | -0.6019 | -0.6835 | -0.6930 |
+#> | U| 458.18867 | 93.71 | -5.765 | -0.9855 | -0.1668 |
+#> |.....................| 2.188 | 2.309 | 1.248 | 0.6642 |
+#> |.....................| 0.7122 | 1.506 | 1.299 | 1.325 |
+#> | X| 458.18867 | 93.71 | 0.003136 | 0.2718 | 0.8463 |
+#> |.....................| 8.919 | 2.309 | 1.248 | 0.6642 |
+#> |.....................| 0.7122 | 1.506 | 1.299 | 1.325 |
+#> | F| Forward Diff. | -3.049 | 0.4396 | -0.1330 | 0.02964 |
+#> |.....................| -0.08039 | -2.599 | -3.012 | -0.1957 |
+#> |.....................| -2.463 | -0.6721 | 0.3494 | 0.7476 |
+#> | 51| 458.45407 | 0.9980 | -1.449 | -0.8787 | -0.8738 |
+#> |.....................| -0.7836 | -0.4935 | -0.7244 | -1.061 |
+#> |.....................| -1.034 | -0.5419 | -0.6952 | -0.7610 |
+#> | U| 458.45407 | 93.92 | -5.821 | -0.9579 | -0.1743 |
+#> |.....................| 2.187 | 2.302 | 1.262 | 0.6155 |
+#> |.....................| 0.7366 | 1.577 | 1.286 | 1.249 |
+#> | X| 458.45407 | 93.92 | 0.002965 | 0.2773 | 0.8400 |
+#> |.....................| 8.906 | 2.302 | 1.262 | 0.6155 |
+#> |.....................| 0.7366 | 1.577 | 1.286 | 1.249 |
+#> | 52| 458.19883 | 0.9985 | -1.406 | -0.9001 | -0.8680 |
+#> |.....................| -0.7823 | -0.4861 | -0.7404 | -1.011 |
+#> |.....................| -1.054 | -0.5879 | -0.6864 | -0.7089 |
+#> | U| 458.19883 | 93.97 | -5.778 | -0.9792 | -0.1685 |
+#> |.....................| 2.188 | 2.309 | 1.253 | 0.6534 |
+#> |.....................| 0.7193 | 1.522 | 1.296 | 1.307 |
+#> | X| 458.19883 | 93.97 | 0.003096 | 0.2731 | 0.8449 |
+#> |.....................| 8.917 | 2.309 | 1.253 | 0.6534 |
+#> |.....................| 0.7193 | 1.522 | 1.296 | 1.307 |
+#> | 53| 458.20478 | 0.9986 | -1.399 | -0.9039 | -0.8670 |
+#> |.....................| -0.7821 | -0.4848 | -0.7433 | -1.002 |
+#> |.....................| -1.058 | -0.5961 | -0.6848 | -0.6996 |
+#> | U| 458.20478 | 93.98 | -5.770 | -0.9830 | -0.1675 |
+#> |.....................| 2.188 | 2.311 | 1.251 | 0.6601 |
+#> |.....................| 0.7162 | 1.512 | 1.297 | 1.318 |
+#> | X| 458.20478 | 93.98 | 0.003120 | 0.2723 | 0.8458 |
+#> |.....................| 8.919 | 2.311 | 1.251 | 0.6601 |
+#> |.....................| 0.7162 | 1.512 | 1.297 | 1.318 |
+#> | 54| 458.21371 | 0.9986 | -1.394 | -0.9063 | -0.8663 |
+#> |.....................| -0.7820 | -0.4840 | -0.7451 | -0.9963 |
+#> |.....................| -1.060 | -0.6013 | -0.6838 | -0.6937 |
+#> | U| 458.21371 | 93.98 | -5.765 | -0.9854 | -0.1669 |
+#> |.....................| 2.188 | 2.311 | 1.250 | 0.6644 |
+#> |.....................| 0.7142 | 1.506 | 1.298 | 1.325 |
+#> | X| 458.21371 | 93.98 | 0.003135 | 0.2718 | 0.8463 |
+#> |.....................| 8.920 | 2.311 | 1.250 | 0.6644 |
+#> |.....................| 0.7142 | 1.506 | 1.298 | 1.325 |
+#> | 55| 458.18572 | 0.9965 | -1.393 | -0.9064 | -0.8663 |
+#> |.....................| -0.7820 | -0.4858 | -0.7472 | -0.9964 |
+#> |.....................| -1.062 | -0.6017 | -0.6836 | -0.6932 |
+#> | U| 458.18572 | 93.79 | -5.765 | -0.9855 | -0.1668 |
+#> |.....................| 2.188 | 2.310 | 1.249 | 0.6643 |
+#> |.....................| 0.7128 | 1.506 | 1.299 | 1.325 |
+#> | X| 458.18572 | 93.79 | 0.003136 | 0.2718 | 0.8463 |
+#> |.....................| 8.919 | 2.310 | 1.249 | 0.6643 |
+#> |.....................| 0.7128 | 1.506 | 1.299 | 1.325 |
+#> | F| Forward Diff. | 5.905 | 0.4355 | -0.1157 | 0.02634 |
+#> |.....................| -0.05151 | -1.735 | -2.785 | -0.07657 |
+#> |.....................| -2.587 | -0.1320 | 0.06282 | 0.8041 |
+#> | 56| 458.18221 | 0.9957 | -1.394 | -0.9063 | -0.8663 |
+#> |.....................| -0.7820 | -0.4856 | -0.7465 | -0.9968 |
+#> |.....................| -1.061 | -0.6016 | -0.6835 | -0.6937 |
+#> | U| 458.18221 | 93.70 | -5.765 | -0.9853 | -0.1669 |
+#> |.....................| 2.188 | 2.310 | 1.249 | 0.6640 |
+#> |.....................| 0.7132 | 1.506 | 1.299 | 1.325 |
+#> | X| 458.18221 | 93.70 | 0.003135 | 0.2718 | 0.8463 |
+#> |.....................| 8.920 | 2.310 | 1.249 | 0.6640 |
+#> |.....................| 0.7132 | 1.506 | 1.299 | 1.325 |
+#> | F| Forward Diff. | -4.339 | 0.4378 | -0.1282 | 0.03581 |
+#> |.....................| -0.09329 | -1.978 | -2.551 | -0.01933 |
+#> |.....................| -3.951 | -0.1424 | 0.01723 | 0.8408 |
+#> | 57| 458.17882 | 0.9963 | -1.394 | -0.9061 | -0.8663 |
+#> |.....................| -0.7819 | -0.4855 | -0.7459 | -0.9972 |
+#> |.....................| -1.060 | -0.6016 | -0.6832 | -0.6941 |
+#> | U| 458.17882 | 93.76 | -5.766 | -0.9852 | -0.1669 |
+#> |.....................| 2.188 | 2.310 | 1.250 | 0.6637 |
+#> |.....................| 0.7139 | 1.506 | 1.299 | 1.324 |
+#> | X| 458.17882 | 93.76 | 0.003134 | 0.2719 | 0.8463 |
+#> |.....................| 8.920 | 2.310 | 1.250 | 0.6637 |
+#> |.....................| 0.7139 | 1.506 | 1.299 | 1.324 |
+#> | F| Forward Diff. | 2.737 | 0.4289 | -0.1193 | 0.04099 |
+#> |.....................| -0.07175 | -2.104 | -2.655 | -0.1084 |
+#> |.....................| -2.489 | -0.08715 | 0.1037 | 0.7775 |
+#> | 58| 458.17628 | 0.9955 | -1.394 | -0.9061 | -0.8663 |
+#> |.....................| -0.7819 | -0.4849 | -0.7451 | -0.9972 |
+#> |.....................| -1.060 | -0.6016 | -0.6832 | -0.6943 |
+#> | U| 458.17628 | 93.69 | -5.766 | -0.9851 | -0.1669 |
+#> |.....................| 2.188 | 2.311 | 1.250 | 0.6637 |
+#> |.....................| 0.7145 | 1.506 | 1.299 | 1.324 |
+#> | X| 458.17628 | 93.69 | 0.003133 | 0.2719 | 0.8463 |
+#> |.....................| 8.920 | 2.311 | 1.250 | 0.6637 |
+#> |.....................| 0.7145 | 1.506 | 1.299 | 1.324 |
+#> | F| Forward Diff. | -5.829 | 0.4364 | -0.1238 | 0.03009 |
+#> |.....................| -0.09450 | -1.871 | -2.366 | 0.01771 |
+#> |.....................| -2.486 | -0.08743 | 0.03350 | 0.7982 |
+#> | 59| 458.17323 | 0.9963 | -1.395 | -0.9059 | -0.8664 |
+#> |.....................| -0.7819 | -0.4846 | -0.7446 | -0.9977 |
+#> |.....................| -1.059 | -0.6018 | -0.6829 | -0.6949 |
+#> | U| 458.17323 | 93.77 | -5.766 | -0.9850 | -0.1669 |
+#> |.....................| 2.188 | 2.311 | 1.250 | 0.6633 |
+#> |.....................| 0.7149 | 1.506 | 1.299 | 1.323 |
+#> | X| 458.17323 | 93.77 | 0.003132 | 0.2719 | 0.8463 |
+#> |.....................| 8.921 | 2.311 | 1.250 | 0.6633 |
+#> |.....................| 0.7149 | 1.506 | 1.299 | 1.323 |
+#> | F| Forward Diff. | 3.135 | 0.4259 | -0.1111 | 0.03860 |
+#> |.....................| -0.07150 | -1.713 | -2.294 | -0.1635 |
+#> |.....................| -3.755 | -0.1071 | 0.1242 | 0.7274 |
+#> | 60| 458.17055 | 0.9957 | -1.395 | -0.9058 | -0.8664 |
+#> |.....................| -0.7818 | -0.4843 | -0.7440 | -0.9980 |
+#> |.....................| -1.058 | -0.6018 | -0.6828 | -0.6953 |
+#> | U| 458.17055 | 93.70 | -5.766 | -0.9848 | -0.1669 |
+#> |.....................| 2.188 | 2.311 | 1.251 | 0.6631 |
+#> |.....................| 0.7157 | 1.506 | 1.300 | 1.323 |
+#> | X| 458.17055 | 93.70 | 0.003131 | 0.2719 | 0.8463 |
+#> |.....................| 8.921 | 2.311 | 1.251 | 0.6631 |
+#> |.....................| 0.7157 | 1.506 | 1.300 | 1.323 |
+#> | F| Forward Diff. | -3.767 | 0.4346 | -0.1027 | 0.03296 |
+#> |.....................| -0.07232 | -2.503 | -3.089 | -0.1630 |
+#> |.....................| -2.382 | -0.08570 | 0.1151 | 0.7161 |
+#> | 61| 458.16819 | 0.9965 | -1.395 | -0.9058 | -0.8664 |
+#> |.....................| -0.7818 | -0.4837 | -0.7432 | -0.9981 |
+#> |.....................| -1.058 | -0.6018 | -0.6828 | -0.6955 |
+#> | U| 458.16819 | 93.79 | -5.767 | -0.9848 | -0.1669 |
+#> |.....................| 2.188 | 2.312 | 1.251 | 0.6630 |
+#> |.....................| 0.7162 | 1.506 | 1.300 | 1.322 |
+#> | X| 458.16819 | 93.79 | 0.003130 | 0.2719 | 0.8462 |
+#> |.....................| 8.921 | 2.312 | 1.251 | 0.6630 |
+#> |.....................| 0.7162 | 1.506 | 1.300 | 1.322 |
+#> | F| Forward Diff. | 6.568 | 0.4333 | -0.07429 | 0.03599 |
+#> |.....................| -0.03802 | -2.553 | -3.191 | -0.5393 |
+#> |.....................| -0.9714 | -0.8035 | 0.1031 | 0.6902 |
+#> | 62| 458.16513 | 0.9957 | -1.396 | -0.9056 | -0.8666 |
+#> |.....................| -0.7821 | -0.4835 | -0.7425 | -0.9983 |
+#> |.....................| -1.057 | -0.6019 | -0.6824 | -0.6959 |
+#> | U| 458.16513 | 93.70 | -5.767 | -0.9847 | -0.1672 |
+#> |.....................| 2.188 | 2.312 | 1.252 | 0.6629 |
+#> |.....................| 0.7164 | 1.506 | 1.300 | 1.322 |
+#> | X| 458.16513 | 93.70 | 0.003129 | 0.2720 | 0.8461 |
+#> |.....................| 8.919 | 2.312 | 1.252 | 0.6629 |
+#> |.....................| 0.7164 | 1.506 | 1.300 | 1.322 |
+#> | F| Forward Diff. | -3.933 | 0.4306 | -0.09800 | 0.02413 |
+#> |.....................| -0.09225 | -1.469 | -2.000 | -0.05194 |
+#> |.....................| -3.675 | -0.07209 | 0.09082 | 0.7196 |
+#> | 63| 458.16261 | 0.9962 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4834 | -0.7420 | -0.9986 |
+#> |.....................| -1.057 | -0.6017 | -0.6820 | -0.6964 |
+#> | U| 458.16261 | 93.76 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.312 | 1.252 | 0.6626 |
+#> |.....................| 0.7170 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16261 | 93.76 | 0.003127 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.312 | 1.252 | 0.6626 |
+#> |.....................| 0.7170 | 1.506 | 1.300 | 1.321 |
+#> | F| Forward Diff. | 2.233 | 0.4197 | -0.09277 | 0.03004 |
+#> |.....................| -0.08165 | -1.772 | -2.245 | -0.08206 |
+#> |.....................| -2.339 | -0.1510 | 0.07888 | 0.6887 |
+#> | 64| 458.16062 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16062 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16062 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | M| Mixed Diff. | -6.515 | 0.4169 | -0.1028 |-1.670e+05 |
+#> |.....................| -0.1097 | -2.956 | -2.997 | -0.5657 |
+#> |.....................| -4.153 | -0.6659 | -0.7853 | 0.1256 |
+#> | 65| 458.16519 | 0.9948 | -1.397 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4822 | -0.7405 | -0.9986 |
+#> |.....................| -1.055 | -0.6016 | -0.6821 | -0.6969 |
+#> | U| 458.16519 | 93.62 | -5.768 | -0.9844 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.253 | 0.6627 |
+#> |.....................| 0.7183 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16519 | 93.62 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.253 | 0.6627 |
+#> |.....................| 0.7183 | 1.506 | 1.300 | 1.321 |
+#> | 66| 458.16209 | 0.9951 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4825 | -0.7409 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6968 |
+#> | U| 458.16209 | 93.65 | -5.768 | -0.9844 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.253 | 0.6626 |
+#> |.....................| 0.7180 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16209 | 93.65 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.253 | 0.6626 |
+#> |.....................| 0.7180 | 1.506 | 1.300 | 1.321 |
+#> | 67| 458.16115 | 0.9953 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4827 | -0.7410 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16115 | 93.67 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.253 | 0.6626 |
+#> |.....................| 0.7178 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16115 | 93.67 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.253 | 0.6626 |
+#> |.....................| 0.7178 | 1.506 | 1.300 | 1.321 |
+#> | 68| 458.16084 | 0.9954 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4827 | -0.7411 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16084 | 93.68 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16084 | 93.68 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | 69| 458.16072 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16072 | 93.68 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16072 | 93.68 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | 70| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7177 | 1.506 | 1.300 | 1.321 |
+#> | 71| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 72| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 73| 458.16072 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16072 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16072 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 74| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 75| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 76| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 77| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 78| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 79| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 80| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 81| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 82| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 83| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 84| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 85| 458.16068 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16068 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16068 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 86| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 87| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 88| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 89| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 90| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 91| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | 92| 458.16067 | 0.9955 | -1.396 | -0.9054 | -0.8667 |
+#> |.....................| -0.7822 | -0.4828 | -0.7412 | -0.9986 |
+#> |.....................| -1.056 | -0.6017 | -0.6821 | -0.6967 |
+#> | U| 458.16067 | 93.69 | -5.768 | -0.9845 | -0.1673 |
+#> |.....................| 2.188 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> | X| 458.16067 | 93.69 | 0.003126 | 0.2720 | 0.8460 |
+#> |.....................| 8.918 | 2.313 | 1.252 | 0.6626 |
+#> |.....................| 0.7176 | 1.506 | 1.300 | 1.321 |
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.5791 -5.6199 -2.0817 -3.9984 -1.2037 0.1481 4.5359 1.6042 1.1515 2.4545 0.4989 0.5230 19.1822 10.0277
+#> 2: 93.5157 -5.6781 -1.9742 -4.0546 -1.1333 0.1109 4.4678 1.5240 1.0939 2.3318 0.4740 0.6338 12.8885 7.4711
+#> 3: 93.2898 -5.7047 -1.8559 -4.1328 -1.0939 0.0438 5.0096 1.4478 1.1939 2.2152 0.4503 0.6021 11.0381 5.1444
+#> 4: 93.0426 -5.7814 -1.8501 -4.1839 -1.0410 0.0594 6.3802 1.4778 1.2229 2.1556 0.4278 0.5972 10.2381 4.4049
+#> 5: 92.9134 -5.8482 -1.8162 -4.2071 -1.0582 0.0732 6.9858 1.8242 1.1718 2.3151 0.4064 0.5822 9.8642 4.4088
+#> 6: 92.7655 -5.8047 -1.8535 -4.2041 -0.9870 0.0611 6.6365 1.7739 1.1619 2.2910 0.3861 0.5531 8.6374 4.0594
+#> 7: 93.0259 -5.8252 -1.9173 -4.2093 -0.9549 0.0995 6.3047 2.2731 1.1038 2.1765 0.3668 0.5255 9.0819 3.0678
+#> 8: 93.1406 -5.7510 -1.9019 -4.2213 -0.9559 0.1508 5.9894 2.5908 1.0919 2.0948 0.3484 0.4992 8.3332 2.3703
+#> 9: 93.3980 -5.5162 -1.9512 -4.2707 -0.9026 0.1570 5.6900 2.4612 1.0373 2.3579 0.3310 0.4742 7.7762 2.1692
+#> 10: 93.5148 -5.4966 -1.9184 -4.2482 -0.9045 0.1396 5.4055 2.3382 0.9855 2.2400 0.3145 0.4652 7.5796 1.9233
+#> 11: 93.1833 -5.5679 -1.9315 -4.2869 -0.9148 0.1713 5.1352 2.2213 0.9362 2.1465 0.2987 0.4622 7.5181 1.8003
+#> 12: 92.9902 -5.7249 -1.9741 -4.3054 -0.9148 0.1927 4.8784 2.9298 0.8975 2.3858 0.2838 0.5005 7.3638 1.7074
+#> 13: 92.5821 -5.7143 -1.9662 -4.3403 -0.8940 0.1595 4.6345 2.8035 0.9305 2.5370 0.2696 0.4755 7.1732 1.6333
+#> 14: 92.1385 -5.5571 -1.9874 -4.2935 -0.8815 0.1762 5.5000 2.6634 0.9011 2.4102 0.2561 0.5012 7.1920 1.7020
+#> 15: 92.1244 -5.5198 -1.9701 -4.3134 -0.8984 0.1704 5.2250 2.5302 0.9705 2.4401 0.2433 0.4839 7.4072 1.6160
+#> 16: 92.6306 -5.4666 -1.9776 -4.3023 -0.8906 0.1737 4.9638 2.4037 1.0278 2.3181 0.2312 0.5183 7.5105 1.6033
+#> 17: 92.5769 -5.4886 -2.0034 -4.3892 -0.8863 0.1967 5.6659 2.2835 1.0796 2.7700 0.2196 0.5138 7.6495 1.4656
+#> 18: 92.0321 -5.5257 -2.0086 -4.3651 -0.8914 0.1869 6.5345 2.1693 1.0771 2.6315 0.2086 0.4906 7.8248 1.4297
+#> 19: 92.5497 -5.5509 -1.9892 -4.3590 -0.8947 0.2148 6.2078 2.0936 1.0629 2.4999 0.1992 0.4847 7.8809 1.4881
+#> 20: 92.3638 -5.5322 -1.9943 -4.3507 -0.9153 0.1787 6.2176 2.1784 1.0242 2.5190 0.1923 0.4604 7.7900 1.5147
+#> 21: 92.3946 -5.5963 -1.9984 -4.3234 -0.9031 0.1961 5.9067 2.4305 0.9962 2.3930 0.1827 0.4374 7.6671 1.5182
+#> 22: 92.3389 -5.7757 -1.9686 -4.3485 -0.9054 0.1677 5.6113 3.2010 0.9650 2.4493 0.1907 0.4220 7.1305 1.5425
+#> 23: 92.5054 -5.7766 -1.9947 -4.3613 -0.9069 0.1781 5.3308 3.2506 0.9932 2.5478 0.1868 0.4217 7.6690 1.4526
+#> 24: 92.5865 -5.8597 -1.9691 -4.4676 -0.8950 0.1755 5.0642 4.0954 0.9471 3.5482 0.1891 0.4438 7.2397 1.6349
+#> 25: 92.3775 -5.8727 -1.9577 -4.4964 -0.8955 0.1477 4.8354 3.8906 0.9557 3.5054 0.2003 0.4216 6.7966 1.5576
+#> 26: 92.2427 -5.9696 -1.9672 -4.4384 -0.9063 0.1733 4.5937 4.0917 0.9924 3.3326 0.1918 0.4341 6.9377 1.5723
+#> 27: 92.7312 -5.8434 -1.9590 -4.3655 -0.9095 0.1669 4.4448 3.8871 1.0032 3.1660 0.2006 0.4320 7.1970 1.5118
+#> 28: 92.7033 -5.8759 -1.9827 -4.3776 -0.9145 0.1844 4.5885 3.6928 0.9750 3.0077 0.2093 0.4104 6.8745 1.4865
+#> 29: 92.5242 -5.8627 -1.9806 -4.4623 -0.9142 0.2069 5.2823 3.5081 0.9748 3.5849 0.2098 0.4120 6.9735 1.5115
+#> 30: 92.2312 -5.8332 -1.9739 -4.3699 -0.9100 0.1624 5.0182 3.5473 0.9553 3.4056 0.2102 0.3914 6.8547 1.5172
+#> 31: 92.1659 -5.7898 -1.9642 -4.3956 -0.9105 0.1625 4.7672 3.3700 0.9442 3.2571 0.2071 0.3795 6.5191 1.5452
+#> 32: 92.5436 -5.7968 -1.9642 -4.3987 -0.9179 0.1110 4.5289 3.2015 0.9382 3.0943 0.2024 0.3605 6.5921 1.5105
+#> 33: 92.7837 -5.8155 -1.9539 -4.3145 -0.9157 0.1398 4.3024 3.3616 0.9119 2.9395 0.1981 0.3494 6.2870 1.6036
+#> 34: 93.0500 -5.8853 -1.9587 -4.2507 -0.9146 0.1455 4.0873 4.3592 0.9129 2.7926 0.1961 0.3319 6.3493 1.6059
+#> 35: 93.1208 -5.8581 -1.9614 -4.2722 -0.9127 0.1255 4.0645 4.1413 0.9262 2.6529 0.1964 0.3157 6.1337 1.6010
+#> 36: 93.1002 -5.8598 -1.9886 -4.2092 -0.9076 0.1192 4.2392 3.9342 0.9566 2.5203 0.2015 0.3222 6.5326 1.4847
+#> 37: 92.8242 -5.6228 -1.9655 -4.2054 -0.9099 0.1010 6.8190 3.7375 0.9087 2.3943 0.1942 0.3141 6.2613 1.6015
+#> 38: 93.1512 -5.5747 -1.9736 -4.2054 -0.9115 0.0887 6.4781 3.5506 0.8904 2.2746 0.1930 0.3298 6.4960 1.5750
+#> 39: 92.9998 -5.5416 -1.9750 -4.2124 -0.9101 0.0953 6.1542 3.3731 0.9013 2.1608 0.1858 0.3204 6.6470 1.5705
+#> 40: 93.2158 -5.7057 -1.9587 -4.2101 -0.9122 0.0630 5.8464 3.2044 0.9350 2.1357 0.1851 0.3044 6.6842 1.5069
+#> 41: 93.0585 -5.5453 -1.9306 -4.2101 -0.9021 0.0531 5.5541 3.0442 0.9458 2.1673 0.1851 0.2892 6.3923 1.5949
+#> 42: 93.0958 -5.4512 -1.9484 -4.2227 -0.8959 0.0649 5.2764 2.8920 0.9571 2.1930 0.1829 0.2747 6.3082 1.5985
+#> 43: 93.2333 -5.5398 -1.9391 -4.2400 -0.8972 0.0870 5.0126 2.7474 0.9913 2.2830 0.1984 0.2720 6.0810 1.6131
+#> 44: 92.9479 -5.5648 -1.9227 -4.2468 -0.9104 0.0963 4.7620 2.6100 0.9682 2.2976 0.2038 0.2648 5.8461 1.6955
+#> 45: 93.0244 -5.6247 -1.9379 -4.2588 -0.9093 0.0865 5.2997 2.4894 0.9837 2.3100 0.2039 0.2844 5.9439 1.6121
+#> 46: 92.5959 -5.6240 -1.9513 -4.2588 -0.9172 0.0923 5.3111 2.5081 1.0158 2.3100 0.2050 0.2702 6.0141 1.6189
+#> 47: 92.8483 -5.5823 -1.9529 -4.2684 -0.9194 0.0770 6.2469 2.3827 1.0328 2.3567 0.2104 0.2567 6.0472 1.5858
+#> 48: 92.6210 -5.6336 -1.9379 -4.3049 -0.9054 0.0747 7.5721 2.3177 1.0379 2.5427 0.2103 0.2439 6.0431 1.5860
+#> 49: 92.6337 -5.6723 -1.9486 -4.2879 -0.8985 0.0773 7.1935 2.6572 1.0181 2.4515 0.2056 0.2559 6.0895 1.5217
+#> 50: 92.2413 -5.7138 -1.9587 -4.2804 -0.8926 0.0774 8.1551 2.9779 1.0282 2.4807 0.2090 0.2510 6.2355 1.5223
+#> 51: 92.2223 -5.6765 -1.9496 -4.2971 -0.8840 0.1034 7.7638 3.0625 1.0017 2.6024 0.2075 0.2384 6.3495 1.6621
+#> 52: 92.4242 -5.6573 -1.9408 -4.2943 -0.8993 0.1136 8.3190 2.9093 1.0044 2.4822 0.2163 0.2411 6.0611 1.5241
+#> 53: 92.6070 -5.5921 -1.9397 -4.2873 -0.9046 0.0904 10.3681 2.7639 1.0098 2.4895 0.2194 0.2393 6.1728 1.5264
+#> 54: 92.9339 -5.6194 -1.9292 -4.2950 -0.9006 0.1010 9.9150 2.6257 1.0088 2.4268 0.2346 0.2492 5.9203 1.5693
+#> 55: 93.4640 -5.5851 -1.8969 -4.2614 -0.9065 0.1058 10.3986 2.4944 1.0204 2.3055 0.2257 0.2403 5.7030 1.5717
+#> 56: 93.3646 -5.5851 -1.9127 -4.3130 -0.9196 0.1077 9.8787 2.3697 1.0067 2.6259 0.2261 0.2370 5.7389 1.5053
+#> 57: 93.5408 -5.4962 -1.9150 -4.3285 -0.9148 0.0880 9.3848 2.2512 0.9903 2.6118 0.2160 0.2494 5.7530 1.5780
+#> 58: 93.5195 -5.4358 -1.9459 -4.3041 -0.9076 0.1022 8.9155 2.1386 1.0220 2.5253 0.2220 0.2578 6.0138 1.4494
+#> 59: 93.5906 -5.4624 -1.9507 -4.3065 -0.9124 0.1374 8.4698 2.0317 1.0230 2.5539 0.2212 0.2449 5.7538 1.6021
+#> 60: 93.3308 -5.3784 -1.9540 -4.2417 -0.9173 0.1337 8.0463 1.9301 1.0298 2.4262 0.2173 0.2327 5.8841 1.4634
+#> 61: 93.3506 -5.4000 -1.9688 -4.2389 -0.9130 0.0942 7.6440 1.8336 1.0437 2.3049 0.2216 0.2210 6.0098 1.4243
+#> 62: 93.6969 -5.4175 -1.9467 -4.2389 -0.9135 0.1315 7.2618 1.7419 1.0213 2.2519 0.2250 0.2149 5.6278 1.4755
+#> 63: 93.6188 -5.3860 -1.9295 -4.2637 -0.9222 0.1196 7.8033 1.6548 1.0340 2.2699 0.2282 0.2282 5.6763 1.4755
+#> 64: 93.6782 -5.4118 -1.9518 -4.2655 -0.9298 0.1055 8.3519 1.5721 1.0227 2.4426 0.2317 0.2560 5.8006 1.4724
+#> 65: 93.5253 -5.4313 -1.9314 -4.2538 -0.9245 0.0919 7.9343 1.4980 1.0771 2.3486 0.2249 0.2635 5.8752 1.4850
+#> 66: 93.3192 -5.5672 -1.9715 -4.2575 -0.9224 0.1404 8.2293 1.9722 1.0233 2.3758 0.2365 0.2546 5.9462 1.5148
+#> 67: 93.0765 -5.4861 -1.9673 -4.2472 -0.9103 0.0935 8.3227 1.8736 0.9889 2.3305 0.2493 0.2419 5.7836 1.4946
+#> 68: 93.2666 -5.4963 -1.9635 -4.2435 -0.9093 0.0940 9.2911 1.7800 1.0050 2.3179 0.2495 0.2298 5.7104 1.4797
+#> 69: 93.3894 -5.5666 -1.9342 -4.2325 -0.9227 0.0957 9.0211 2.0287 1.0012 2.3052 0.2483 0.2348 5.8939 1.5158
+#> 70: 93.2671 -5.5710 -1.9486 -4.2723 -0.9323 0.1062 8.5700 2.1251 0.9714 2.3266 0.2498 0.2466 6.1562 1.5041
+#> 71: 92.9975 -5.5829 -1.9507 -4.2632 -0.9317 0.1166 8.1415 2.0322 0.9403 2.3654 0.2373 0.2454 5.8668 1.5122
+#> 72: 92.6364 -5.5255 -1.9888 -4.2605 -0.9255 0.1062 8.8866 1.9306 0.9680 2.4488 0.2314 0.2438 6.2101 1.5098
+#> 73: 92.4442 -5.5679 -1.9880 -4.3501 -0.9070 0.0972 9.1986 1.9203 0.9597 3.1091 0.2369 0.2412 6.1257 1.5029
+#> 74: 92.3866 -5.5447 -1.9895 -4.3137 -0.9004 0.0898 10.2222 1.8961 0.9573 2.9536 0.2494 0.2361 6.0474 1.4875
+#> 75: 92.2491 -5.6481 -1.9591 -4.3587 -0.8991 0.1028 9.7111 2.2694 1.0140 2.9121 0.2524 0.2243 6.0995 1.4780
+#> 76: 92.4656 -5.6014 -1.9860 -4.3538 -0.9015 0.0978 11.3121 2.1560 0.9861 2.9372 0.2489 0.2314 6.0996 1.4464
+#> 77: 92.5076 -5.5929 -1.9560 -4.3624 -0.9051 0.1008 12.0483 2.0482 1.0212 3.0132 0.2551 0.2378 5.9595 1.5081
+#> 78: 92.5987 -5.7000 -1.9592 -4.3611 -0.9131 0.0958 11.4458 2.3873 1.0062 2.9848 0.2549 0.2372 6.0385 1.4666
+#> 79: 92.4883 -5.7675 -1.9900 -4.4226 -0.9163 0.1153 10.8735 2.7867 0.9616 3.4984 0.2546 0.2309 5.9441 1.4722
+#> 80: 92.1716 -5.7782 -1.9810 -4.4398 -0.9122 0.1193 10.3299 3.0280 0.9642 3.6766 0.2520 0.2291 6.3013 1.4698
+#> 81: 92.1145 -5.8494 -1.9836 -4.3634 -0.9196 0.1013 9.8134 3.1850 0.9160 3.4927 0.2562 0.2409 6.2458 1.4664
+#> 82: 92.3761 -5.9668 -1.9722 -4.3888 -0.9240 0.1139 9.9738 3.9484 0.8923 3.3519 0.2434 0.2318 6.0987 1.4847
+#> 83: 92.7805 -6.1135 -1.9335 -4.3600 -0.9273 0.1027 11.2060 4.7684 0.8932 3.1843 0.2454 0.2202 5.9824 1.4920
+#> 84: 92.9601 -6.2190 -1.9374 -4.3187 -0.9376 0.1140 10.6457 5.6632 0.9077 3.0250 0.2464 0.2188 5.9979 1.5152
+#> 85: 92.4579 -6.1486 -1.9398 -4.3269 -0.9417 0.0979 10.1134 5.3800 0.9011 2.8738 0.2446 0.2330 5.7007 1.5648
+#> 86: 92.3580 -6.2177 -1.9549 -4.3287 -0.9510 0.1073 9.6077 5.1608 0.9318 2.7301 0.2497 0.2214 5.9916 1.5305
+#> 87: 92.8919 -6.3309 -1.9480 -4.3285 -0.9647 0.1009 9.1273 6.4577 0.9494 2.7023 0.2408 0.2126 5.9053 1.4313
+#> 88: 93.0621 -6.1220 -1.9623 -4.3341 -0.9624 0.1300 8.6710 6.1349 0.9563 2.6593 0.2404 0.2130 6.1925 1.4510
+#> 89: 92.7711 -6.2636 -1.9545 -4.3520 -0.9496 0.1227 8.2374 6.2143 0.9791 2.5862 0.2346 0.2333 5.9772 1.4523
+#> 90: 92.9148 -6.5481 -1.9586 -4.3275 -0.9496 0.1096 7.8255 8.2617 0.9787 2.4647 0.2346 0.2216 5.9136 1.4247
+#> 91: 92.8129 -6.4655 -1.9753 -4.3287 -0.9435 0.1210 9.1893 7.8487 0.9642 2.5304 0.2354 0.2268 5.9129 1.4229
+#> 92: 93.1090 -6.4752 -1.9841 -4.3533 -0.9428 0.1509 10.1133 7.7232 0.9160 2.6037 0.2457 0.2265 5.8601 1.4646
+#> 93: 93.4781 -6.3780 -1.9909 -4.3713 -0.9450 0.1544 9.6076 7.3370 0.9153 2.7656 0.2485 0.2499 5.9150 1.5180
+#> 94: 93.2125 -6.3021 -1.9798 -4.3459 -0.9470 0.1520 9.6738 6.9702 0.9314 2.6273 0.2428 0.2519 5.8752 1.4456
+#> 95: 93.0091 -5.9727 -1.9828 -4.3777 -0.9447 0.1370 9.6411 6.6217 0.9107 2.7137 0.2428 0.2556 5.8302 1.4477
+#> 96: 92.8731 -5.7813 -1.9952 -4.3343 -0.9352 0.1505 9.1590 6.2906 0.9011 2.5780 0.2366 0.2546 6.0545 1.4887
+#> 97: 92.7834 -5.8119 -1.9975 -4.3303 -0.9258 0.1231 8.8022 5.9760 0.9005 2.5331 0.2392 0.2419 5.9522 1.4754
+#> 98: 92.8447 -5.9773 -1.9940 -4.3353 -0.9301 0.1409 8.3621 5.6772 0.9244 2.4828 0.2426 0.2490 6.1027 1.4129
+#> 99: 93.1697 -5.8958 -1.9964 -4.3325 -0.9248 0.1411 7.9440 5.3934 0.9586 2.6138 0.2378 0.2545 6.2793 1.3719
+#> 100: 93.2536 -5.8481 -2.0009 -4.3408 -0.9304 0.1718 8.7965 5.1237 0.9290 2.6161 0.2398 0.2418 6.0908 1.4534
+#> 101: 93.2942 -5.8684 -1.9650 -4.3096 -0.9305 0.1496 9.7633 4.8675 0.9166 2.4853 0.2372 0.2565 5.9079 1.4948
+#> 102: 93.2636 -6.1363 -1.9517 -4.2653 -0.9235 0.1175 10.7772 5.1927 0.8944 2.3610 0.2448 0.2812 5.7748 1.5533
+#> 103: 92.6954 -5.9371 -1.9524 -4.2792 -0.9045 0.1288 10.2383 4.9331 0.8876 2.2429 0.2406 0.2720 5.5496 1.5601
+#> 104: 92.6149 -6.0650 -1.9532 -4.2752 -0.9048 0.0973 10.9914 4.6864 0.8845 2.1875 0.2475 0.2584 5.5593 1.4897
+#> 105: 92.8231 -5.9779 -1.9650 -4.2939 -0.9013 0.1112 10.4712 4.4521 0.9193 2.1985 0.2416 0.2455 5.4420 1.4910
+#> 106: 92.7599 -5.9602 -1.9594 -4.3018 -0.9026 0.1273 10.1396 4.2295 0.9308 2.1700 0.2453 0.2625 5.5458 1.4429
+#> 107: 93.1433 -5.9509 -1.9638 -4.2715 -0.9324 0.1385 9.6327 4.0415 0.9271 2.1026 0.2415 0.2626 5.4762 1.4286
+#> 108: 93.1354 -5.7359 -1.9691 -4.2962 -0.9256 0.1346 10.2794 3.8394 0.9387 2.1671 0.2412 0.2627 5.5107 1.4200
+#> 109: 92.9608 -5.8252 -1.9780 -4.3149 -0.9125 0.1564 9.7654 4.0619 0.9380 2.1731 0.2325 0.2657 5.8118 1.4379
+#> 110: 93.1043 -5.7632 -1.9874 -4.2868 -0.9113 0.1178 9.2771 3.8588 0.9420 2.1477 0.2214 0.2524 5.9352 1.4377
+#> 111: 92.8879 -5.7965 -1.9781 -4.2851 -0.9147 0.1107 8.8133 3.6659 0.9526 2.1891 0.2130 0.2398 5.6360 1.4461
+#> 112: 92.9347 -5.7484 -1.9460 -4.2825 -0.9195 0.1078 8.3726 3.4826 0.9710 2.2687 0.2051 0.2278 5.5771 1.5123
+#> 113: 92.7217 -5.7193 -1.9328 -4.2721 -0.9252 0.1021 7.9540 3.3085 1.0056 2.2848 0.2244 0.2164 5.7135 1.5082
+#> 114: 92.9944 -5.7382 -1.9414 -4.2835 -0.9210 0.1210 7.5563 3.1430 1.0184 2.2457 0.2260 0.2182 5.6799 1.4751
+#> 115: 93.1261 -5.8876 -1.9290 -4.2753 -0.9382 0.0960 9.7696 3.4406 1.0140 2.2745 0.2171 0.2073 5.3919 1.4919
+#> 116: 92.7669 -5.9842 -1.9484 -4.2828 -0.9504 0.1122 9.2811 4.1332 1.0202 2.2835 0.2160 0.2136 5.3651 1.5337
+#> 117: 92.9804 -5.9847 -1.9584 -4.2879 -0.9474 0.1234 9.2911 3.9265 0.9692 2.3115 0.2135 0.2163 5.1053 1.4774
+#> 118: 93.2853 -5.8443 -1.9494 -4.2700 -0.9400 0.1105 9.8572 3.7302 0.9736 2.2489 0.2192 0.2223 5.2416 1.4668
+#> 119: 93.2776 -5.8592 -1.9458 -4.2600 -0.9394 0.1072 9.3643 3.5437 0.9789 2.1964 0.2176 0.2205 5.2942 1.4847
+#> 120: 93.0335 -5.8156 -1.9453 -4.2623 -0.9437 0.1139 8.8961 3.3665 0.9698 2.2380 0.2206 0.2231 5.4427 1.4470
+#> 121: 93.0115 -5.8402 -1.9355 -4.2596 -0.9291 0.1138 8.4513 3.3018 0.9743 2.1463 0.2096 0.2120 5.1537 1.4487
+#> 122: 93.6277 -5.8852 -1.9276 -4.2787 -0.9419 0.1388 8.0287 3.4114 0.9438 2.1410 0.2072 0.2104 5.1198 1.5201
+#> 123: 93.4952 -6.0977 -1.9332 -4.2847 -0.9431 0.1412 7.6273 4.8225 0.9472 2.1335 0.2081 0.2129 5.2003 1.6193
+#> 124: 93.7207 -6.2280 -1.9105 -4.2692 -0.9551 0.1422 7.2459 5.4835 0.9657 2.0896 0.2148 0.2272 5.2901 1.5482
+#> 125: 93.6041 -6.0808 -1.9356 -4.2748 -0.9531 0.1184 7.0201 5.2094 0.9591 2.0421 0.2089 0.2158 5.3848 1.4896
+#> 126: 93.5193 -6.0164 -1.9296 -4.2890 -0.9600 0.1351 7.6848 4.9489 0.9931 2.1387 0.1989 0.2129 5.1988 1.4492
+#> 127: 93.7135 -5.9340 -1.9448 -4.2883 -0.9633 0.1428 8.3411 4.7014 0.9820 2.1192 0.1985 0.2046 5.3953 1.4985
+#> 128: 94.2312 -5.8849 -1.9404 -4.2754 -0.9633 0.1495 7.9240 4.4664 0.9884 2.0587 0.1902 0.2171 5.7113 1.4987
+#> 129: 94.0390 -5.8674 -1.9229 -4.3309 -0.9614 0.1472 8.5108 4.2430 1.0319 2.1023 0.1909 0.2154 5.5654 1.4294
+#> 130: 93.4178 -6.0458 -1.9224 -4.3364 -0.9560 0.1570 8.0852 4.4639 1.0184 2.2804 0.1869 0.2182 5.6585 1.4443
+#> 131: 93.5483 -6.2682 -1.9258 -4.3654 -0.9554 0.1449 7.6810 5.6020 1.0254 2.3477 0.1857 0.2230 5.4266 1.4324
+#> 132: 93.5180 -6.3297 -1.9204 -4.3577 -0.9640 0.1365 7.2969 5.5672 1.0354 2.3257 0.1788 0.2118 5.4913 1.4859
+#> 133: 93.4707 -6.0990 -1.9415 -4.3315 -0.9775 0.1232 6.9321 5.2888 1.0686 2.3421 0.1851 0.2012 5.8429 1.4618
+#> 134: 93.1012 -6.1236 -1.9308 -4.3409 -0.9654 0.1225 7.6471 5.0244 1.0517 2.4652 0.1947 0.2008 5.6902 1.5432
+#> 135: 93.2545 -6.1070 -1.9408 -4.3415 -0.9553 0.1228 9.2701 4.7732 1.0160 2.3607 0.1919 0.1907 5.5154 1.5317
+#> 136: 93.3338 -6.0321 -1.9336 -4.3074 -0.9598 0.1120 8.8066 4.5345 0.9652 2.2427 0.1999 0.2249 5.3667 1.6036
+#> 137: 93.5910 -6.0627 -1.9339 -4.3074 -0.9529 0.1407 8.3663 4.3078 0.9538 2.2128 0.1966 0.2195 5.2959 1.6015
+#> 138: 93.6338 -5.9702 -1.9252 -4.3105 -0.9615 0.1373 7.9480 4.0924 0.9875 2.2635 0.1964 0.2218 5.4532 1.5261
+#> 139: 93.6403 -5.8913 -1.9237 -4.2962 -0.9582 0.1165 8.0749 3.8878 0.9746 2.2457 0.1972 0.2125 5.9356 1.5173
+#> 140: 92.8503 -5.8314 -1.9452 -4.3180 -0.9487 0.1142 8.6356 3.6934 0.9933 2.2044 0.1961 0.2019 5.7908 1.5138
+#> 141: 93.1249 -6.0584 -1.9448 -4.3139 -0.9367 0.0950 8.9231 4.4196 1.0220 2.2246 0.2079 0.2077 6.0233 1.4339
+#> 142: 93.1846 -6.3026 -1.9152 -4.3093 -0.9392 0.0866 10.1508 5.9592 1.0562 2.3325 0.2082 0.2133 5.5285 1.4832
+#> 143: 92.4682 -6.1485 -1.9146 -4.2812 -0.9376 0.0260 9.6433 5.6613 1.0618 2.3594 0.2000 0.2027 6.0573 1.4428
+#> 144: 92.7792 -6.1108 -1.8939 -4.2740 -0.9341 0.0765 9.1611 5.3782 1.0917 2.3074 0.2057 0.2240 6.2141 1.4953
+#> 145: 93.1314 -6.2086 -1.8939 -4.3580 -0.9341 0.0741 8.7031 5.1093 1.0931 2.7164 0.2105 0.2229 5.8543 1.4855
+#> 146: 93.2254 -6.2170 -1.8998 -4.3724 -0.9311 0.0677 8.2679 5.0506 1.0811 2.8434 0.2049 0.2118 5.5455 1.4763
+#> 147: 93.3264 -6.0136 -1.8998 -4.3853 -0.9328 0.0817 9.4673 4.7980 1.0668 2.8512 0.2009 0.2114 5.5518 1.5225
+#> 148: 93.2298 -5.9143 -1.8921 -4.5001 -0.9296 0.1057 8.9939 4.5581 1.0563 3.8266 0.1982 0.2043 5.5242 1.5614
+#> 149: 93.3604 -5.9894 -1.8832 -4.5223 -0.9338 0.0858 8.5442 4.3302 1.0544 4.3930 0.1986 0.2003 5.4353 1.4957
+#> 150: 93.4715 -5.9630 -1.8833 -4.4796 -0.9335 0.0827 8.1170 4.1137 1.0912 4.1733 0.1984 0.1903 5.7477 1.4554
+#> 151: 93.3385 -5.8026 -1.9052 -4.4507 -0.9368 0.0684 8.7726 3.9080 1.1249 3.9647 0.2074 0.1808 5.7693 1.4400
+#> 152: 93.1682 -5.8529 -1.9441 -4.3545 -0.9309 0.0752 8.8042 3.1783 1.0496 3.0168 0.2069 0.1688 5.9161 1.4565
+#> 153: 93.0559 -6.0261 -1.9425 -4.3431 -0.9327 0.1016 9.1435 3.9939 1.0120 2.8470 0.1894 0.1509 5.4435 1.5486
+#> 154: 92.8582 -6.0887 -1.9278 -4.3094 -0.9352 0.1064 8.4316 4.2991 0.9819 2.6257 0.1907 0.1609 5.4587 1.5208
+#> 155: 93.3200 -5.8480 -1.9149 -4.3363 -0.9294 0.1143 9.6700 3.1734 0.9942 2.6441 0.1824 0.1906 5.5193 1.6410
+#> 156: 93.3199 -5.9053 -1.9213 -4.3163 -0.9369 0.1291 7.5899 3.5902 0.9823 2.4648 0.1770 0.1956 5.3816 1.5356
+#> 157: 93.2434 -5.8763 -1.9161 -4.3035 -0.9549 0.1075 8.4137 3.2576 0.9935 2.5007 0.1795 0.1852 5.4053 1.5706
+#> 158: 93.1494 -5.9243 -1.8929 -4.3162 -0.9680 0.1296 8.2959 3.3262 1.0029 2.4943 0.1866 0.1921 5.4369 1.5510
+#> 159: 93.5683 -6.0335 -1.9127 -4.3040 -0.9675 0.1271 7.7222 4.0079 0.9768 2.5765 0.1869 0.2028 5.7165 1.4968
+#> 160: 93.9417 -6.0018 -1.9085 -4.2818 -0.9611 0.1161 5.8791 4.4991 0.9658 2.4933 0.1878 0.1986 6.0579 1.5272
+#> 161: 94.1252 -5.9264 -1.8943 -4.2805 -0.9645 0.0860 4.9517 3.6307 0.9754 2.4988 0.1934 0.1785 5.7457 1.5878
+#> 162: 93.9389 -5.7613 -1.8946 -4.2410 -0.9752 0.0898 6.7269 2.5865 1.0184 2.4379 0.1933 0.1908 5.9052 1.5215
+#> 163: 93.5890 -5.7243 -1.8992 -4.2636 -0.9722 0.0759 8.4484 2.5137 1.0151 2.3869 0.1928 0.1889 5.4694 1.5048
+#> 164: 93.9751 -5.7314 -1.8786 -4.3271 -0.9702 0.1020 6.6884 2.5136 1.0133 2.8395 0.1907 0.1998 5.4625 1.4854
+#> 165: 93.9708 -5.7409 -1.8856 -4.3129 -0.9616 0.1094 5.8809 2.4589 1.0401 2.6662 0.1912 0.1998 5.4339 1.4549
+#> 166: 93.9265 -5.6937 -1.9134 -4.3080 -0.9702 0.1151 5.6940 2.4086 1.0065 2.6864 0.1983 0.1987 5.6907 1.4857
+#> 167: 93.4157 -5.7312 -1.9163 -4.3286 -0.9638 0.1216 5.1230 2.5468 1.0487 2.5930 0.1917 0.1940 5.5938 1.4267
+#> 168: 93.3701 -5.8757 -1.9196 -4.3493 -0.9579 0.1134 6.0802 3.3929 1.0517 2.6981 0.1888 0.2063 5.4125 1.4365
+#> 169: 93.4342 -6.0262 -1.9041 -4.3347 -0.9526 0.0997 6.0780 3.6349 1.0623 2.7344 0.1946 0.1978 5.4930 1.4594
+#> 170: 93.3751 -6.1195 -1.9093 -4.3541 -0.9872 0.0834 6.8972 4.0337 1.0763 2.8428 0.2077 0.2005 5.6759 1.4455
+#> 171: 93.3603 -6.0360 -1.9196 -4.4632 -0.9763 0.0866 7.4236 3.6025 1.0684 3.7611 0.2046 0.1894 5.6282 1.4414
+#> 172: 93.2776 -5.9538 -1.9031 -4.4815 -0.9779 0.1024 5.4751 3.2802 1.0599 3.9487 0.2115 0.1990 5.6116 1.4230
+#> 173: 93.4470 -5.8580 -1.9193 -4.4170 -0.9641 0.0957 5.6416 2.8005 1.0440 3.4509 0.2066 0.1863 5.5804 1.4485
+#> 174: 93.2952 -5.8590 -1.9010 -4.3600 -0.9640 0.0789 6.4314 2.9503 1.0808 2.9773 0.2045 0.1969 5.4423 1.4421
+#> 175: 93.3756 -5.7733 -1.8959 -4.3621 -0.9504 0.0609 6.1723 2.5287 1.0950 3.0019 0.2127 0.2053 5.4338 1.4470
+#> 176: 93.1450 -5.8266 -1.9053 -4.3401 -0.9457 0.0633 6.5237 3.0522 1.0942 2.9464 0.2134 0.2021 5.6501 1.3664
+#> 177: 92.7723 -5.9978 -1.9231 -4.3529 -0.9524 0.0658 7.4519 4.2374 1.0640 3.0260 0.2158 0.2146 5.9180 1.4100
+#> 178: 92.7261 -5.9836 -1.9189 -4.3349 -0.9576 0.0768 5.5211 4.2557 1.0611 2.8827 0.2169 0.2088 5.8872 1.4206
+#> 179: 92.9599 -6.0071 -1.9259 -4.3081 -0.9581 0.0657 6.0953 3.8205 1.0816 2.6709 0.2122 0.2014 5.8221 1.4026
+#> 180: 93.0831 -6.1544 -1.9400 -4.3018 -0.9496 0.0411 4.2312 4.9005 1.1064 2.6542 0.2143 0.2221 6.3264 1.3820
+#> 181: 92.8840 -6.0889 -1.9364 -4.3200 -0.9566 0.0861 4.2186 4.4615 1.0930 2.7270 0.2142 0.2424 6.0486 1.4035
+#> 182: 93.1913 -6.1457 -1.9384 -4.3085 -0.9606 0.0733 6.2878 4.6026 1.0917 2.6393 0.2131 0.2151 5.7042 1.4952
+#> 183: 93.1218 -6.3114 -1.9355 -4.2883 -0.9742 0.0741 7.2675 5.1377 1.0914 2.5060 0.2220 0.2111 5.5099 1.4097
+#> 184: 93.1462 -6.3147 -1.9068 -4.2880 -0.9653 0.0893 7.6928 5.6510 1.0563 2.5066 0.2256 0.2201 5.4138 1.5319
+#> 185: 93.1825 -6.3608 -1.9265 -4.2815 -0.9549 0.0873 7.1340 5.9801 1.0363 2.4788 0.2177 0.1958 5.4202 1.4569
+#> 186: 93.6270 -6.1413 -1.9278 -4.2702 -0.9696 0.1185 6.7652 4.5535 1.0400 2.3673 0.2163 0.1932 5.3005 1.5012
+#> 187: 93.9922 -6.3364 -1.9269 -4.2702 -0.9729 0.1197 7.7694 6.1592 0.9948 2.3673 0.2196 0.2091 5.3075 1.5105
+#> 188: 93.8884 -6.0236 -1.9207 -4.2928 -0.9900 0.1343 7.8090 4.2847 0.9840 2.4238 0.2195 0.1966 5.2861 1.5607
+#> 189: 94.3110 -6.0809 -1.9145 -4.2826 -0.9840 0.1224 8.5580 4.0998 0.9800 2.4505 0.2294 0.1840 5.7107 1.5180
+#> 190: 94.0039 -6.0996 -1.9140 -4.2793 -0.9782 0.1429 10.6594 4.1655 0.9796 2.4415 0.2297 0.1960 5.7533 1.5720
+#> 191: 93.9692 -6.1129 -1.9362 -4.3261 -0.9705 0.1462 8.8201 4.3146 1.0124 2.4625 0.2287 0.2049 5.5670 1.5206
+#> 192: 93.3178 -5.9759 -1.9192 -4.3378 -0.9664 0.1434 8.8047 3.7150 1.0282 2.4137 0.2243 0.1977 5.3858 1.4599
+#> 193: 93.1427 -5.9388 -1.9391 -4.3211 -0.9650 0.1401 7.1862 3.2835 1.0218 2.3216 0.2163 0.1866 5.3930 1.5017
+#> 194: 93.0588 -6.0605 -1.9361 -4.3350 -0.9462 0.1330 6.8930 4.0020 1.0166 2.3186 0.2057 0.1818 5.2535 1.5075
+#> 195: 93.1820 -6.1201 -1.9579 -4.3034 -0.9534 0.1557 8.1300 4.4218 0.9932 2.1873 0.2099 0.1834 5.4862 1.4698
+#> 196: 93.2230 -5.8879 -1.9725 -4.2965 -0.9584 0.1390 8.1307 3.0777 1.0051 2.1597 0.2089 0.1683 5.7058 1.3970
+#> 197: 93.3504 -5.8829 -1.9677 -4.3075 -0.9577 0.1638 6.7115 3.0660 1.0050 2.1377 0.2024 0.1642 5.4691 1.5016
+#> 198: 93.3016 -5.8771 -1.9885 -4.3241 -0.9605 0.1562 6.4722 3.0381 0.9727 2.2053 0.1975 0.1683 5.3434 1.4885
+#> 199: 93.2464 -5.8787 -1.9871 -4.3430 -0.9528 0.1751 4.5894 3.0445 0.9748 2.2247 0.1886 0.1780 5.4469 1.4405
+#> 200: 93.3474 -5.7995 -1.9767 -4.3298 -0.9480 0.1947 4.7024 2.8535 0.9895 2.2234 0.1951 0.2012 5.5130 1.4641
+#> 201: 93.3231 -5.8169 -1.9737 -4.3268 -0.9510 0.1804 4.4248 2.8913 0.9738 2.2141 0.1955 0.2057 5.5422 1.4843
+#> 202: 93.3484 -5.8009 -1.9732 -4.3240 -0.9519 0.1674 4.4068 2.8084 0.9736 2.2040 0.1959 0.2033 5.5843 1.4744
+#> 203: 93.2617 -5.7915 -1.9678 -4.3211 -0.9535 0.1629 4.5333 2.7678 0.9877 2.1980 0.1961 0.2023 5.6265 1.4811
+#> 204: 93.2210 -5.8071 -1.9647 -4.3220 -0.9504 0.1629 4.6144 2.8347 0.9922 2.1938 0.1937 0.2013 5.5745 1.4988
+#> 205: 93.1914 -5.8104 -1.9667 -4.3225 -0.9484 0.1593 4.5880 2.8639 0.9931 2.1952 0.1916 0.1979 5.5960 1.5057
+#> 206: 93.1827 -5.8348 -1.9697 -4.3236 -0.9498 0.1587 4.7189 3.0353 0.9929 2.2016 0.1922 0.1947 5.6096 1.5136
+#> 207: 93.2017 -5.8760 -1.9714 -4.3239 -0.9518 0.1592 4.8171 3.2659 0.9947 2.2042 0.1927 0.1910 5.6413 1.5078
+#> 208: 93.2226 -5.8819 -1.9736 -4.3261 -0.9532 0.1610 4.8241 3.2964 0.9957 2.2122 0.1938 0.1878 5.6704 1.5031
+#> 209: 93.2158 -5.8786 -1.9743 -4.3278 -0.9538 0.1595 4.6275 3.2763 0.9963 2.2279 0.1950 0.1848 5.6758 1.5038
+#> 210: 93.2216 -5.8798 -1.9746 -4.3286 -0.9535 0.1589 4.5667 3.2857 0.9974 2.2473 0.1948 0.1834 5.6707 1.5054
+#> 211: 93.2238 -5.8847 -1.9763 -4.3302 -0.9530 0.1591 4.5745 3.2932 0.9956 2.2576 0.1948 0.1823 5.6691 1.4990
+#> 212: 93.2242 -5.8893 -1.9777 -4.3323 -0.9532 0.1600 4.6203 3.2955 0.9938 2.2704 0.1958 0.1814 5.6732 1.4994
+#> 213: 93.2246 -5.8950 -1.9756 -4.3345 -0.9532 0.1588 4.7363 3.3106 0.9894 2.2864 0.1960 0.1791 5.6401 1.5015
+#> 214: 93.2056 -5.9070 -1.9740 -4.3368 -0.9532 0.1586 4.7814 3.3538 0.9888 2.3047 0.1960 0.1761 5.6265 1.5008
+#> 215: 93.2126 -5.9157 -1.9720 -4.3405 -0.9533 0.1580 4.9117 3.3916 0.9890 2.3191 0.1959 0.1742 5.6054 1.5015
+#> 216: 93.2161 -5.9242 -1.9716 -4.3423 -0.9533 0.1594 5.0163 3.4425 0.9897 2.3291 0.1959 0.1739 5.5975 1.5005
+#> 217: 93.2193 -5.9351 -1.9715 -4.3445 -0.9537 0.1614 4.9927 3.5085 0.9905 2.3309 0.1957 0.1739 5.5905 1.5024
+#> 218: 93.1973 -5.9314 -1.9725 -4.3479 -0.9548 0.1640 5.0502 3.4902 0.9918 2.3344 0.1952 0.1740 5.5909 1.5046
+#> 219: 93.1938 -5.9312 -1.9729 -4.3508 -0.9539 0.1664 5.0446 3.4901 0.9922 2.3365 0.1949 0.1746 5.5808 1.5046
+#> 220: 93.1994 -5.9424 -1.9734 -4.3531 -0.9536 0.1683 5.0462 3.5593 0.9917 2.3370 0.1945 0.1754 5.5831 1.5055
+#> 221: 93.2015 -5.9511 -1.9746 -4.3550 -0.9537 0.1702 5.1062 3.6002 0.9899 2.3368 0.1945 0.1762 5.5731 1.5043
+#> 222: 93.2057 -5.9653 -1.9756 -4.3571 -0.9541 0.1718 5.1727 3.6876 0.9886 2.3364 0.1943 0.1776 5.5813 1.5047
+#> 223: 93.1998 -5.9723 -1.9761 -4.3592 -0.9540 0.1726 5.1866 3.7239 0.9871 2.3428 0.1940 0.1791 5.5702 1.5047
+#> 224: 93.2042 -5.9799 -1.9768 -4.3615 -0.9540 0.1734 5.1516 3.7613 0.9849 2.3531 0.1934 0.1809 5.5705 1.5039
+#> 225: 93.1974 -5.9813 -1.9776 -4.3648 -0.9540 0.1740 5.1225 3.7676 0.9840 2.3663 0.1929 0.1834 5.5698 1.5030
+#> 226: 93.1963 -5.9807 -1.9777 -4.3679 -0.9535 0.1751 5.1632 3.7694 0.9839 2.3785 0.1927 0.1850 5.5676 1.5069
+#> 227: 93.1912 -5.9740 -1.9783 -4.3707 -0.9533 0.1768 5.1987 3.7421 0.9835 2.3931 0.1922 0.1855 5.5597 1.5091
+#> 228: 93.1902 -5.9799 -1.9792 -4.3745 -0.9533 0.1784 5.2070 3.7641 0.9825 2.4134 0.1917 0.1861 5.5502 1.5086
+#> 229: 93.1903 -5.9894 -1.9805 -4.3792 -0.9533 0.1796 5.2398 3.8109 0.9812 2.4382 0.1910 0.1870 5.5486 1.5075
+#> 230: 93.1833 -5.9946 -1.9816 -4.3836 -0.9530 0.1814 5.2357 3.8346 0.9800 2.4614 0.1904 0.1883 5.5515 1.5065
+#> 231: 93.1740 -6.0001 -1.9834 -4.3871 -0.9528 0.1833 5.2848 3.8635 0.9783 2.4814 0.1898 0.1893 5.5526 1.5057
+#> 232: 93.1581 -6.0071 -1.9852 -4.3904 -0.9523 0.1857 5.3056 3.8967 0.9766 2.5002 0.1891 0.1904 5.5571 1.5057
+#> 233: 93.1417 -6.0131 -1.9865 -4.3933 -0.9517 0.1869 5.3290 3.9227 0.9745 2.5129 0.1885 0.1909 5.5609 1.5069
+#> 234: 93.1245 -6.0198 -1.9878 -4.3961 -0.9514 0.1880 5.3062 3.9567 0.9731 2.5269 0.1886 0.1916 5.5645 1.5074
+#> 235: 93.1084 -6.0269 -1.9885 -4.3985 -0.9514 0.1892 5.3213 3.9969 0.9729 2.5390 0.1887 0.1931 5.5722 1.5065
+#> 236: 93.1037 -6.0382 -1.9897 -4.4009 -0.9517 0.1899 5.3601 4.0674 0.9744 2.5501 0.1886 0.1949 5.5811 1.5066
+#> 237: 93.0989 -6.0432 -1.9906 -4.4031 -0.9518 0.1909 5.3744 4.0877 0.9755 2.5623 0.1885 0.1964 5.5890 1.5051
+#> 238: 93.0932 -6.0433 -1.9912 -4.4041 -0.9521 0.1915 5.4192 4.0775 0.9772 2.5698 0.1886 0.1980 5.5980 1.5029
+#> 239: 93.0943 -6.0475 -1.9913 -4.4056 -0.9520 0.1921 5.4483 4.0960 0.9792 2.5785 0.1888 0.1997 5.5999 1.5011
+#> 240: 93.0904 -6.0498 -1.9909 -4.4070 -0.9520 0.1925 5.4921 4.1095 0.9814 2.5867 0.1887 0.2011 5.5974 1.5013
+#> 241: 93.0883 -6.0508 -1.9910 -4.4086 -0.9520 0.1931 5.5503 4.1140 0.9827 2.5966 0.1887 0.2023 5.6049 1.4997
+#> 242: 93.0884 -6.0487 -1.9916 -4.4102 -0.9517 0.1940 5.5634 4.1021 0.9831 2.6059 0.1886 0.2039 5.6116 1.5005
+#> 243: 93.0836 -6.0466 -1.9920 -4.4123 -0.9517 0.1950 5.5786 4.0878 0.9837 2.6204 0.1887 0.2054 5.6217 1.5000
+#> 244: 93.0756 -6.0477 -1.9926 -4.4149 -0.9517 0.1956 5.5827 4.0904 0.9843 2.6385 0.1887 0.2070 5.6306 1.4995
+#> 245: 93.0664 -6.0533 -1.9930 -4.4174 -0.9514 0.1963 5.6228 4.1208 0.9857 2.6549 0.1888 0.2086 5.6346 1.4996
+#> 246: 93.0643 -6.0543 -1.9931 -4.4200 -0.9511 0.1969 5.6236 4.1257 0.9872 2.6735 0.1886 0.2096 5.6381 1.4989
+#> 247: 93.0631 -6.0568 -1.9929 -4.4227 -0.9511 0.1974 5.6045 4.1389 0.9889 2.6910 0.1886 0.2107 5.6408 1.4984
+#> 248: 93.0636 -6.0567 -1.9924 -4.4264 -0.9513 0.1974 5.6016 4.1412 0.9906 2.7225 0.1886 0.2117 5.6424 1.4992
+#> 249: 93.0727 -6.0560 -1.9920 -4.4302 -0.9514 0.1973 5.6088 4.1383 0.9922 2.7584 0.1885 0.2125 5.6441 1.4992
+#> 250: 93.0865 -6.0551 -1.9915 -4.4337 -0.9512 0.1973 5.6127 4.1386 0.9941 2.7852 0.1884 0.2135 5.6522 1.4977
+#> 251: 93.0887 -6.0551 -1.9910 -4.4364 -0.9511 0.1967 5.5869 4.1455 0.9964 2.8060 0.1883 0.2146 5.6561 1.4968
+#> 252: 93.0877 -6.0522 -1.9904 -4.4376 -0.9511 0.1964 5.5778 4.1346 0.9987 2.8151 0.1883 0.2155 5.6583 1.4964
+#> 253: 93.0843 -6.0518 -1.9897 -4.4391 -0.9512 0.1961 5.5948 4.1323 1.0011 2.8253 0.1884 0.2164 5.6588 1.4972
+#> 254: 93.0818 -6.0518 -1.9896 -4.4399 -0.9512 0.1957 5.6122 4.1352 1.0016 2.8319 0.1882 0.2169 5.6573 1.4991
+#> 255: 93.0838 -6.0524 -1.9895 -4.4401 -0.9514 0.1954 5.6310 4.1366 1.0025 2.8408 0.1880 0.2174 5.6584 1.4996
+#> 256: 93.0850 -6.0579 -1.9892 -4.4400 -0.9515 0.1948 5.6526 4.1752 1.0043 2.8482 0.1879 0.2181 5.6611 1.4979
+#> 257: 93.0868 -6.0600 -1.9890 -4.4391 -0.9517 0.1940 5.6742 4.1941 1.0055 2.8499 0.1878 0.2189 5.6649 1.4985
+#> 258: 93.0873 -6.0606 -1.9888 -4.4391 -0.9518 0.1932 5.7088 4.2037 1.0066 2.8552 0.1877 0.2196 5.6668 1.4983
+#> 259: 93.0912 -6.0650 -1.9882 -4.4377 -0.9519 0.1925 5.7494 4.2300 1.0080 2.8537 0.1877 0.2204 5.6729 1.4977
+#> 260: 93.0964 -6.0699 -1.9874 -4.4362 -0.9519 0.1918 5.7609 4.2588 1.0100 2.8513 0.1877 0.2212 5.6792 1.4974
+#> 261: 93.1014 -6.0737 -1.9866 -4.4350 -0.9522 0.1913 5.7971 4.2807 1.0115 2.8496 0.1877 0.2220 5.6812 1.4969
+#> 262: 93.1064 -6.0734 -1.9859 -4.4346 -0.9526 0.1909 5.7936 4.2719 1.0129 2.8505 0.1877 0.2228 5.6824 1.4958
+#> 263: 93.1092 -6.0783 -1.9850 -4.4344 -0.9530 0.1906 5.8078 4.2973 1.0141 2.8525 0.1879 0.2233 5.6815 1.4954
+#> 264: 93.1128 -6.0830 -1.9842 -4.4338 -0.9535 0.1901 5.8245 4.3273 1.0146 2.8527 0.1880 0.2237 5.6768 1.4958
+#> 265: 93.1198 -6.0874 -1.9834 -4.4331 -0.9541 0.1895 5.8467 4.3490 1.0149 2.8522 0.1880 0.2238 5.6693 1.4965
+#> 266: 93.1284 -6.0890 -1.9828 -4.4327 -0.9546 0.1888 5.8350 4.3488 1.0149 2.8513 0.1881 0.2239 5.6650 1.4970
+#> 267: 93.1380 -6.0926 -1.9819 -4.4326 -0.9549 0.1883 5.8440 4.3677 1.0156 2.8526 0.1883 0.2240 5.6609 1.4974
+#> 268: 93.1480 -6.0915 -1.9810 -4.4321 -0.9552 0.1873 5.8565 4.3552 1.0163 2.8522 0.1886 0.2238 5.6537 1.4990
+#> 269: 93.1539 -6.0910 -1.9803 -4.4314 -0.9556 0.1866 5.8709 4.3438 1.0179 2.8503 0.1888 0.2237 5.6495 1.4989
+#> 270: 93.1620 -6.0898 -1.9798 -4.4311 -0.9561 0.1861 5.8678 4.3301 1.0197 2.8507 0.1890 0.2235 5.6466 1.4984
+#> 271: 93.1668 -6.0881 -1.9792 -4.4305 -0.9565 0.1857 5.8508 4.3147 1.0209 2.8487 0.1891 0.2234 5.6487 1.4997
+#> 272: 93.1725 -6.0848 -1.9787 -4.4300 -0.9569 0.1855 5.8431 4.2948 1.0217 2.8474 0.1894 0.2233 5.6488 1.5000
+#> 273: 93.1770 -6.0809 -1.9783 -4.4297 -0.9572 0.1850 5.8432 4.2739 1.0227 2.8470 0.1897 0.2235 5.6497 1.5000
+#> 274: 93.1797 -6.0774 -1.9776 -4.4299 -0.9574 0.1846 5.8549 4.2532 1.0243 2.8494 0.1901 0.2235 5.6511 1.5003
+#> 275: 93.1829 -6.0759 -1.9774 -4.4303 -0.9578 0.1845 5.8633 4.2387 1.0255 2.8514 0.1906 0.2234 5.6561 1.5010
+#> 276: 93.1846 -6.0764 -1.9771 -4.4303 -0.9581 0.1845 5.8738 4.2322 1.0267 2.8523 0.1911 0.2232 5.6554 1.5020
+#> 277: 93.1880 -6.0792 -1.9768 -4.4305 -0.9584 0.1844 5.8980 4.2423 1.0278 2.8541 0.1915 0.2229 5.6586 1.5019
+#> 278: 93.1920 -6.0791 -1.9766 -4.4307 -0.9586 0.1841 5.9368 4.2391 1.0289 2.8559 0.1919 0.2226 5.6600 1.5024
+#> 279: 93.1892 -6.0786 -1.9766 -4.4310 -0.9586 0.1839 5.9822 4.2309 1.0300 2.8584 0.1925 0.2226 5.6642 1.5015
+#> 280: 93.1868 -6.0782 -1.9765 -4.4311 -0.9587 0.1836 6.0381 4.2253 1.0311 2.8616 0.1930 0.2227 5.6686 1.5008
+#> 281: 93.1805 -6.0781 -1.9764 -4.4309 -0.9586 0.1832 6.0718 4.2228 1.0325 2.8626 0.1936 0.2227 5.6741 1.5002
+#> 282: 93.1780 -6.0768 -1.9762 -4.4318 -0.9585 0.1829 6.0867 4.2160 1.0341 2.8701 0.1941 0.2228 5.6740 1.4998
+#> 283: 93.1777 -6.0736 -1.9760 -4.4325 -0.9583 0.1825 6.1250 4.2003 1.0355 2.8768 0.1946 0.2228 5.6761 1.5010
+#> 284: 93.1745 -6.0726 -1.9757 -4.4337 -0.9582 0.1823 6.1509 4.1975 1.0370 2.8843 0.1951 0.2227 5.6764 1.5009
+#> 285: 93.1742 -6.0719 -1.9755 -4.4348 -0.9579 0.1820 6.1652 4.1936 1.0381 2.8910 0.1954 0.2225 5.6773 1.5011
+#> 286: 93.1706 -6.0698 -1.9754 -4.4356 -0.9576 0.1818 6.1840 4.1844 1.0394 2.8966 0.1958 0.2224 5.6780 1.5011
+#> 287: 93.1672 -6.0678 -1.9752 -4.4370 -0.9573 0.1816 6.2123 4.1767 1.0400 2.9079 0.1963 0.2224 5.6757 1.5015
+#> 288: 93.1628 -6.0658 -1.9753 -4.4379 -0.9572 0.1815 6.2355 4.1700 1.0407 2.9150 0.1967 0.2223 5.6742 1.5013
+#> 289: 93.1588 -6.0628 -1.9753 -4.4389 -0.9569 0.1818 6.2435 4.1565 1.0416 2.9217 0.1969 0.2218 5.6777 1.5007
+#> 290: 93.1560 -6.0590 -1.9754 -4.4399 -0.9565 0.1820 6.2564 4.1394 1.0425 2.9291 0.1971 0.2214 5.6778 1.5006
+#> 291: 93.1552 -6.0555 -1.9754 -4.4409 -0.9562 0.1821 6.2753 4.1246 1.0435 2.9375 0.1973 0.2210 5.6779 1.5009
+#> 292: 93.1546 -6.0541 -1.9754 -4.4415 -0.9558 0.1820 6.2881 4.1183 1.0444 2.9414 0.1975 0.2205 5.6762 1.5006
+#> 293: 93.1506 -6.0535 -1.9756 -4.4424 -0.9555 0.1821 6.2856 4.1182 1.0454 2.9474 0.1976 0.2200 5.6770 1.4994
+#> 294: 93.1453 -6.0520 -1.9758 -4.4424 -0.9553 0.1819 6.2733 4.1124 1.0463 2.9487 0.1979 0.2195 5.6792 1.4985
+#> 295: 93.1431 -6.0487 -1.9760 -4.4421 -0.9551 0.1820 6.2655 4.1009 1.0469 2.9498 0.1982 0.2190 5.6797 1.4989
+#> 296: 93.1425 -6.0460 -1.9760 -4.4432 -0.9548 0.1818 6.2801 4.0912 1.0478 2.9566 0.1984 0.2185 5.6795 1.4989
+#> 297: 93.1403 -6.0442 -1.9761 -4.4440 -0.9545 0.1818 6.2979 4.0836 1.0485 2.9626 0.1987 0.2182 5.6783 1.4978
+#> 298: 93.1400 -6.0438 -1.9763 -4.4440 -0.9543 0.1817 6.3069 4.0842 1.0492 2.9646 0.1989 0.2178 5.6783 1.4968
+#> 299: 93.1373 -6.0426 -1.9764 -4.4445 -0.9540 0.1813 6.3134 4.0790 1.0505 2.9694 0.1991 0.2175 5.6800 1.4953
+#> 300: 93.1340 -6.0412 -1.9764 -4.4450 -0.9538 0.1811 6.3192 4.0731 1.0516 2.9744 0.1993 0.2171 5.6782 1.4938
+#> 301: 93.1330 -6.0402 -1.9766 -4.4455 -0.9535 0.1808 6.3278 4.0685 1.0531 2.9784 0.1996 0.2167 5.6819 1.4925
+#> 302: 93.1308 -6.0402 -1.9768 -4.4457 -0.9534 0.1806 6.3417 4.0684 1.0549 2.9813 0.1998 0.2163 5.6824 1.4905
+#> 303: 93.1294 -6.0373 -1.9769 -4.4459 -0.9532 0.1804 6.3489 4.0538 1.0565 2.9838 0.2000 0.2159 5.6841 1.4890
+#> 304: 93.1304 -6.0345 -1.9771 -4.4461 -0.9530 0.1801 6.3543 4.0409 1.0581 2.9859 0.2002 0.2155 5.6869 1.4875
+#> 305: 93.1287 -6.0319 -1.9772 -4.4463 -0.9528 0.1800 6.3496 4.0293 1.0597 2.9882 0.2003 0.2151 5.6902 1.4867
+#> 306: 93.1261 -6.0301 -1.9775 -4.4474 -0.9527 0.1802 6.3479 4.0231 1.0614 2.9989 0.2003 0.2145 5.6963 1.4856
+#> 307: 93.1232 -6.0284 -1.9777 -4.4479 -0.9526 0.1802 6.3507 4.0135 1.0629 3.0036 0.2004 0.2141 5.6987 1.4849
+#> 308: 93.1192 -6.0264 -1.9779 -4.4483 -0.9524 0.1802 6.3641 4.0019 1.0644 3.0084 0.2004 0.2135 5.6991 1.4837
+#> 309: 93.1137 -6.0253 -1.9783 -4.4487 -0.9522 0.1803 6.3579 3.9953 1.0658 3.0133 0.2004 0.2130 5.7035 1.4826
+#> 310: 93.1100 -6.0223 -1.9787 -4.4489 -0.9520 0.1804 6.3423 3.9800 1.0665 3.0171 0.2005 0.2126 5.7061 1.4822
+#> 311: 93.1044 -6.0215 -1.9791 -4.4496 -0.9517 0.1804 6.3365 3.9744 1.0675 3.0251 0.2005 0.2121 5.7092 1.4816
+#> 312: 93.1006 -6.0206 -1.9795 -4.4501 -0.9516 0.1806 6.3317 3.9681 1.0688 3.0321 0.2006 0.2115 5.7128 1.4805
+#> 313: 93.0951 -6.0194 -1.9797 -4.4499 -0.9516 0.1805 6.3297 3.9609 1.0702 3.0333 0.2008 0.2109 5.7137 1.4805
+#> 314: 93.0922 -6.0192 -1.9800 -4.4497 -0.9515 0.1804 6.3486 3.9570 1.0715 3.0345 0.2009 0.2104 5.7144 1.4800
+#> 315: 93.0883 -6.0186 -1.9804 -4.4495 -0.9515 0.1803 6.3712 3.9528 1.0726 3.0351 0.2011 0.2100 5.7156 1.4794
+#> 316: 93.0808 -6.0182 -1.9808 -4.4492 -0.9514 0.1802 6.3979 3.9483 1.0738 3.0345 0.2013 0.2097 5.7164 1.4792
+#> 317: 93.0758 -6.0174 -1.9813 -4.4487 -0.9513 0.1801 6.4377 3.9428 1.0747 3.0327 0.2015 0.2094 5.7175 1.4787
+#> 318: 93.0713 -6.0166 -1.9816 -4.4484 -0.9513 0.1801 6.4856 3.9375 1.0757 3.0316 0.2017 0.2091 5.7197 1.4778
+#> 319: 93.0659 -6.0176 -1.9819 -4.4482 -0.9511 0.1800 6.5263 3.9425 1.0768 3.0313 0.2018 0.2088 5.7218 1.4772
+#> 320: 93.0607 -6.0165 -1.9822 -4.4484 -0.9510 0.1798 6.5554 3.9372 1.0777 3.0329 0.2019 0.2087 5.7236 1.4771
+#> 321: 93.0551 -6.0145 -1.9825 -4.4487 -0.9509 0.1797 6.5844 3.9275 1.0787 3.0368 0.2021 0.2085 5.7256 1.4766
+#> 322: 93.0531 -6.0130 -1.9827 -4.4491 -0.9507 0.1797 6.6073 3.9201 1.0797 3.0400 0.2021 0.2082 5.7250 1.4759
+#> 323: 93.0477 -6.0123 -1.9828 -4.4493 -0.9506 0.1794 6.6255 3.9149 1.0804 3.0420 0.2021 0.2080 5.7249 1.4756
+#> 324: 93.0425 -6.0107 -1.9829 -4.4498 -0.9504 0.1792 6.6282 3.9060 1.0813 3.0457 0.2022 0.2078 5.7250 1.4754
+#> 325: 93.0389 -6.0090 -1.9830 -4.4504 -0.9503 0.1792 6.6252 3.8965 1.0819 3.0496 0.2022 0.2077 5.7246 1.4749
+#> 326: 93.0411 -6.0093 -1.9832 -4.4509 -0.9503 0.1795 6.6358 3.8976 1.0827 3.0516 0.2022 0.2076 5.7248 1.4738
+#> 327: 93.0418 -6.0095 -1.9834 -4.4514 -0.9503 0.1797 6.6415 3.8962 1.0834 3.0533 0.2022 0.2075 5.7237 1.4737
+#> 328: 93.0434 -6.0093 -1.9835 -4.4520 -0.9503 0.1798 6.6621 3.8957 1.0841 3.0550 0.2022 0.2074 5.7247 1.4731
+#> 329: 93.0446 -6.0109 -1.9836 -4.4522 -0.9503 0.1798 6.6763 3.9048 1.0847 3.0543 0.2022 0.2072 5.7259 1.4725
+#> 330: 93.0451 -6.0133 -1.9838 -4.4518 -0.9503 0.1799 6.6859 3.9192 1.0852 3.0521 0.2022 0.2070 5.7252 1.4719
+#> 331: 93.0456 -6.0136 -1.9838 -4.4516 -0.9503 0.1799 6.6773 3.9217 1.0858 3.0505 0.2022 0.2067 5.7250 1.4715
+#> 332: 93.0463 -6.0133 -1.9839 -4.4515 -0.9504 0.1799 6.6560 3.9195 1.0863 3.0494 0.2022 0.2063 5.7255 1.4710
+#> 333: 93.0496 -6.0122 -1.9839 -4.4513 -0.9505 0.1800 6.6484 3.9134 1.0869 3.0474 0.2022 0.2060 5.7253 1.4705
+#> 334: 93.0520 -6.0105 -1.9838 -4.4513 -0.9505 0.1801 6.6314 3.9035 1.0877 3.0462 0.2022 0.2056 5.7259 1.4702
+#> 335: 93.0550 -6.0088 -1.9836 -4.4510 -0.9507 0.1800 6.6194 3.8941 1.0887 3.0451 0.2022 0.2051 5.7263 1.4702
+#> 336: 93.0554 -6.0081 -1.9834 -4.4509 -0.9508 0.1800 6.6100 3.8896 1.0896 3.0444 0.2022 0.2048 5.7266 1.4705
+#> 337: 93.0582 -6.0067 -1.9832 -4.4507 -0.9509 0.1800 6.6089 3.8805 1.0904 3.0445 0.2021 0.2044 5.7260 1.4706
+#> 338: 93.0631 -6.0073 -1.9831 -4.4507 -0.9511 0.1801 6.5993 3.8798 1.0908 3.0443 0.2021 0.2040 5.7250 1.4711
+#> 339: 93.0689 -6.0071 -1.9831 -4.4508 -0.9513 0.1803 6.5976 3.8749 1.0911 3.0442 0.2021 0.2037 5.7240 1.4714
+#> 340: 93.0694 -6.0085 -1.9831 -4.4507 -0.9516 0.1804 6.5915 3.8779 1.0914 3.0436 0.2022 0.2032 5.7227 1.4711
+#> 341: 93.0709 -6.0097 -1.9830 -4.4508 -0.9518 0.1804 6.5862 3.8803 1.0915 3.0429 0.2023 0.2026 5.7213 1.4715
+#> 342: 93.0741 -6.0104 -1.9829 -4.4507 -0.9521 0.1804 6.5894 3.8812 1.0918 3.0417 0.2024 0.2022 5.7204 1.4714
+#> 343: 93.0781 -6.0122 -1.9829 -4.4505 -0.9523 0.1804 6.5907 3.8870 1.0921 3.0410 0.2024 0.2016 5.7202 1.4712
+#> 344: 93.0818 -6.0134 -1.9829 -4.4503 -0.9525 0.1804 6.5908 3.8895 1.0926 3.0400 0.2025 0.2011 5.7182 1.4712
+#> 345: 93.0850 -6.0148 -1.9829 -4.4500 -0.9528 0.1806 6.5984 3.8931 1.0926 3.0387 0.2026 0.2006 5.7169 1.4712
+#> 346: 93.0849 -6.0155 -1.9831 -4.4502 -0.9529 0.1807 6.6079 3.8986 1.0931 3.0401 0.2028 0.2002 5.7172 1.4716
+#> 347: 93.0859 -6.0161 -1.9832 -4.4503 -0.9530 0.1809 6.6307 3.9028 1.0941 3.0404 0.2029 0.1998 5.7170 1.4712
+#> 348: 93.0885 -6.0173 -1.9833 -4.4503 -0.9532 0.1809 6.6470 3.9096 1.0951 3.0404 0.2030 0.1993 5.7174 1.4708
+#> 349: 93.0894 -6.0189 -1.9835 -4.4503 -0.9534 0.1810 6.6443 3.9190 1.0955 3.0410 0.2031 0.1989 5.7175 1.4707
+#> 350: 93.0924 -6.0196 -1.9836 -4.4502 -0.9535 0.1813 6.6543 3.9218 1.0957 3.0409 0.2032 0.1983 5.7182 1.4705
+#> 351: 93.0938 -6.0203 -1.9838 -4.4503 -0.9536 0.1814 6.6630 3.9233 1.0963 3.0417 0.2032 0.1977 5.7189 1.4703
+#> 352: 93.0946 -6.0210 -1.9838 -4.4505 -0.9537 0.1816 6.6698 3.9263 1.0968 3.0432 0.2033 0.1973 5.7196 1.4701
+#> 353: 93.0969 -6.0214 -1.9839 -4.4505 -0.9538 0.1818 6.6837 3.9270 1.0973 3.0442 0.2034 0.1968 5.7199 1.4701
+#> 354: 93.1014 -6.0199 -1.9839 -4.4504 -0.9539 0.1817 6.7040 3.9204 1.0978 3.0438 0.2034 0.1962 5.7191 1.4703
+#> 355: 93.1035 -6.0197 -1.9838 -4.4502 -0.9539 0.1816 6.7119 3.9222 1.0983 3.0433 0.2034 0.1957 5.7194 1.4706
+#> 356: 93.1055 -6.0198 -1.9839 -4.4496 -0.9539 0.1815 6.7302 3.9277 1.0989 3.0409 0.2035 0.1952 5.7206 1.4707
+#> 357: 93.1080 -6.0188 -1.9837 -4.4490 -0.9540 0.1813 6.7558 3.9243 1.0997 3.0386 0.2035 0.1948 5.7217 1.4706
+#> 358: 93.1111 -6.0182 -1.9835 -4.4484 -0.9541 0.1812 6.7733 3.9204 1.1005 3.0365 0.2035 0.1944 5.7209 1.4700
+#> 359: 93.1148 -6.0175 -1.9834 -4.4481 -0.9542 0.1811 6.7997 3.9151 1.1012 3.0355 0.2035 0.1940 5.7191 1.4696
+#> 360: 93.1157 -6.0176 -1.9832 -4.4478 -0.9543 0.1810 6.8133 3.9155 1.1017 3.0340 0.2035 0.1937 5.7158 1.4691
+#> 361: 93.1169 -6.0185 -1.9830 -4.4476 -0.9544 0.1808 6.8098 3.9232 1.1022 3.0328 0.2035 0.1934 5.7143 1.4690
+#> 362: 93.1173 -6.0205 -1.9829 -4.4472 -0.9545 0.1805 6.8125 3.9361 1.1024 3.0319 0.2035 0.1931 5.7137 1.4693
+#> 363: 93.1162 -6.0230 -1.9828 -4.4467 -0.9545 0.1801 6.8240 3.9524 1.1025 3.0312 0.2035 0.1928 5.7125 1.4695
+#> 364: 93.1173 -6.0240 -1.9826 -4.4464 -0.9546 0.1799 6.8341 3.9575 1.1027 3.0307 0.2035 0.1924 5.7092 1.4695
+#> 365: 93.1199 -6.0259 -1.9824 -4.4462 -0.9547 0.1796 6.8476 3.9687 1.1028 3.0316 0.2036 0.1920 5.7073 1.4695
+#> 366: 93.1220 -6.0277 -1.9821 -4.4461 -0.9548 0.1793 6.8542 3.9777 1.1032 3.0319 0.2037 0.1916 5.7060 1.4694
+#> 367: 93.1230 -6.0287 -1.9819 -4.4460 -0.9548 0.1791 6.8633 3.9829 1.1038 3.0331 0.2038 0.1914 5.7056 1.4693
+#> 368: 93.1255 -6.0276 -1.9816 -4.4459 -0.9549 0.1789 6.8734 3.9764 1.1038 3.0341 0.2038 0.1912 5.7050 1.4695
+#> 369: 93.1258 -6.0263 -1.9814 -4.4461 -0.9549 0.1787 6.8756 3.9698 1.1039 3.0357 0.2039 0.1910 5.7031 1.4697
+#> 370: 93.1288 -6.0252 -1.9811 -4.4463 -0.9548 0.1785 6.8892 3.9639 1.1039 3.0375 0.2040 0.1909 5.7029 1.4701
+#> 371: 93.1317 -6.0245 -1.9810 -4.4467 -0.9548 0.1784 6.8974 3.9601 1.1037 3.0391 0.2040 0.1907 5.7037 1.4700
+#> 372: 93.1346 -6.0233 -1.9811 -4.4465 -0.9548 0.1781 6.9042 3.9536 1.1035 3.0386 0.2040 0.1905 5.7038 1.4700
+#> 373: 93.1340 -6.0234 -1.9810 -4.4461 -0.9547 0.1778 6.9034 3.9548 1.1034 3.0371 0.2039 0.1903 5.7040 1.4698
+#> 374: 93.1324 -6.0230 -1.9811 -4.4456 -0.9547 0.1775 6.9080 3.9527 1.1034 3.0349 0.2038 0.1901 5.7055 1.4691
+#> 375: 93.1309 -6.0226 -1.9812 -4.4451 -0.9546 0.1773 6.9093 3.9493 1.1034 3.0334 0.2037 0.1899 5.7063 1.4683
+#> 376: 93.1298 -6.0215 -1.9811 -4.4447 -0.9546 0.1770 6.9039 3.9432 1.1035 3.0319 0.2036 0.1897 5.7064 1.4678
+#> 377: 93.1296 -6.0209 -1.9811 -4.4443 -0.9546 0.1768 6.8932 3.9390 1.1036 3.0305 0.2035 0.1895 5.7056 1.4672
+#> 378: 93.1292 -6.0200 -1.9810 -4.4438 -0.9545 0.1764 6.8850 3.9349 1.1037 3.0288 0.2034 0.1892 5.7068 1.4667
+#> 379: 93.1284 -6.0196 -1.9808 -4.4432 -0.9544 0.1760 6.8766 3.9318 1.1038 3.0266 0.2033 0.1890 5.7072 1.4665
+#> 380: 93.1304 -6.0182 -1.9806 -4.4425 -0.9543 0.1756 6.8737 3.9249 1.1040 3.0236 0.2033 0.1888 5.7074 1.4662
+#> 381: 93.1315 -6.0169 -1.9804 -4.4417 -0.9542 0.1754 6.8707 3.9193 1.1040 3.0210 0.2032 0.1886 5.7066 1.4661
+#> 382: 93.1331 -6.0160 -1.9801 -4.4409 -0.9542 0.1750 6.8645 3.9150 1.1040 3.0187 0.2032 0.1885 5.7063 1.4664
+#> 383: 93.1334 -6.0153 -1.9800 -4.4403 -0.9542 0.1746 6.8599 3.9123 1.1037 3.0167 0.2032 0.1882 5.7074 1.4665
+#> 384: 93.1328 -6.0140 -1.9801 -4.4397 -0.9540 0.1742 6.8600 3.9074 1.1034 3.0149 0.2031 0.1879 5.7072 1.4667
+#> 385: 93.1306 -6.0137 -1.9801 -4.4392 -0.9539 0.1739 6.8449 3.9073 1.1031 3.0137 0.2030 0.1876 5.7084 1.4665
+#> 386: 93.1281 -6.0134 -1.9801 -4.4388 -0.9539 0.1735 6.8356 3.9088 1.1028 3.0123 0.2029 0.1872 5.7087 1.4667
+#> 387: 93.1267 -6.0141 -1.9801 -4.4384 -0.9537 0.1732 6.8364 3.9150 1.1025 3.0110 0.2028 0.1869 5.7101 1.4669
+#> 388: 93.1252 -6.0142 -1.9801 -4.4380 -0.9536 0.1730 6.8374 3.9192 1.1022 3.0097 0.2028 0.1866 5.7110 1.4670
+#> 389: 93.1223 -6.0140 -1.9801 -4.4375 -0.9535 0.1728 6.8334 3.9209 1.1019 3.0083 0.2028 0.1862 5.7105 1.4674
+#> 390: 93.1221 -6.0144 -1.9800 -4.4371 -0.9534 0.1726 6.8248 3.9256 1.1014 3.0068 0.2028 0.1859 5.7098 1.4675
+#> 391: 93.1210 -6.0149 -1.9799 -4.4365 -0.9533 0.1725 6.8339 3.9293 1.1011 3.0054 0.2028 0.1856 5.7109 1.4678
+#> 392: 93.1193 -6.0145 -1.9799 -4.4360 -0.9532 0.1724 6.8360 3.9279 1.1009 3.0040 0.2028 0.1852 5.7107 1.4678
+#> 393: 93.1200 -6.0149 -1.9799 -4.4357 -0.9532 0.1723 6.8461 3.9287 1.1005 3.0019 0.2028 0.1849 5.7100 1.4678
+#> 394: 93.1202 -6.0138 -1.9799 -4.4355 -0.9532 0.1723 6.8520 3.9229 1.1006 3.0003 0.2028 0.1846 5.7085 1.4679
+#> 395: 93.1203 -6.0134 -1.9800 -4.4354 -0.9532 0.1723 6.8583 3.9200 1.1005 2.9987 0.2027 0.1844 5.7072 1.4680
+#> 396: 93.1195 -6.0131 -1.9800 -4.4353 -0.9532 0.1724 6.8593 3.9169 1.1004 2.9969 0.2027 0.1842 5.7062 1.4676
+#> 397: 93.1195 -6.0130 -1.9801 -4.4352 -0.9532 0.1724 6.8591 3.9143 1.1004 2.9958 0.2027 0.1839 5.7046 1.4675
+#> 398: 93.1200 -6.0128 -1.9801 -4.4352 -0.9532 0.1725 6.8522 3.9125 1.1004 2.9945 0.2028 0.1836 5.7032 1.4675
+#> 399: 93.1200 -6.0135 -1.9803 -4.4351 -0.9531 0.1726 6.8471 3.9166 1.1003 2.9933 0.2028 0.1833 5.7032 1.4673
+#> 400: 93.1204 -6.0139 -1.9803 -4.4351 -0.9531 0.1727 6.8438 3.9191 1.1003 2.9918 0.2027 0.1832 5.7026 1.4671
+#> 401: 93.1198 -6.0139 -1.9804 -4.4351 -0.9530 0.1728 6.8373 3.9186 1.1004 2.9901 0.2027 0.1831 5.7015 1.4670
+#> 402: 93.1199 -6.0141 -1.9804 -4.4351 -0.9530 0.1729 6.8357 3.9194 1.1005 2.9882 0.2027 0.1830 5.7003 1.4671
+#> 403: 93.1196 -6.0155 -1.9804 -4.4350 -0.9530 0.1730 6.8285 3.9255 1.1007 2.9863 0.2026 0.1829 5.7001 1.4671
+#> 404: 93.1183 -6.0164 -1.9805 -4.4350 -0.9531 0.1732 6.8204 3.9308 1.1009 2.9843 0.2026 0.1829 5.7008 1.4670
+#> 405: 93.1178 -6.0161 -1.9805 -4.4350 -0.9532 0.1733 6.8205 3.9286 1.1012 2.9823 0.2025 0.1829 5.7013 1.4669
+#> 406: 93.1176 -6.0171 -1.9806 -4.4348 -0.9533 0.1735 6.8253 3.9319 1.1013 2.9801 0.2025 0.1828 5.7026 1.4666
+#> 407: 93.1168 -6.0185 -1.9807 -4.4348 -0.9533 0.1736 6.8290 3.9373 1.1015 2.9788 0.2024 0.1830 5.7033 1.4664
+#> 408: 93.1165 -6.0198 -1.9808 -4.4349 -0.9534 0.1738 6.8217 3.9428 1.1017 2.9773 0.2023 0.1830 5.7047 1.4663
+#> 409: 93.1165 -6.0210 -1.9809 -4.4350 -0.9534 0.1741 6.8208 3.9505 1.1019 2.9761 0.2021 0.1830 5.7055 1.4661
+#> 410: 93.1169 -6.0230 -1.9810 -4.4351 -0.9535 0.1745 6.8239 3.9617 1.1020 2.9751 0.2020 0.1829 5.7052 1.4658
+#> 411: 93.1166 -6.0237 -1.9811 -4.4353 -0.9536 0.1748 6.8234 3.9664 1.1020 2.9741 0.2019 0.1829 5.7043 1.4657
+#> 412: 93.1164 -6.0235 -1.9812 -4.4355 -0.9536 0.1751 6.8205 3.9643 1.1020 2.9735 0.2017 0.1827 5.7053 1.4654
+#> 413: 93.1182 -6.0232 -1.9814 -4.4356 -0.9537 0.1755 6.8133 3.9615 1.1020 2.9726 0.2016 0.1825 5.7070 1.4650
+#> 414: 93.1190 -6.0226 -1.9815 -4.4360 -0.9537 0.1760 6.8113 3.9578 1.1021 2.9726 0.2015 0.1825 5.7081 1.4648
+#> 415: 93.1183 -6.0226 -1.9817 -4.4364 -0.9538 0.1765 6.8081 3.9557 1.1021 2.9725 0.2014 0.1824 5.7085 1.4646
+#> 416: 93.1185 -6.0238 -1.9818 -4.4369 -0.9538 0.1768 6.8134 3.9617 1.1020 2.9734 0.2013 0.1822 5.7103 1.4645
+#> 417: 93.1190 -6.0245 -1.9819 -4.4373 -0.9540 0.1770 6.8164 3.9664 1.1022 2.9743 0.2012 0.1819 5.7102 1.4650
+#> 418: 93.1219 -6.0256 -1.9818 -4.4376 -0.9542 0.1773 6.8206 3.9710 1.1026 2.9745 0.2011 0.1816 5.7110 1.4655
+#> 419: 93.1255 -6.0261 -1.9817 -4.4381 -0.9543 0.1776 6.8183 3.9714 1.1030 2.9759 0.2010 0.1814 5.7134 1.4659
+#> 420: 93.1294 -6.0262 -1.9816 -4.4385 -0.9546 0.1779 6.8113 3.9704 1.1033 2.9768 0.2009 0.1810 5.7156 1.4666
+#> 421: 93.1319 -6.0259 -1.9815 -4.4392 -0.9547 0.1781 6.7989 3.9685 1.1036 2.9786 0.2008 0.1808 5.7171 1.4676
+#> 422: 93.1338 -6.0263 -1.9814 -4.4398 -0.9548 0.1783 6.7922 3.9681 1.1038 2.9806 0.2006 0.1808 5.7179 1.4681
+#> 423: 93.1353 -6.0266 -1.9813 -4.4406 -0.9550 0.1786 6.7868 3.9674 1.1040 2.9837 0.2006 0.1808 5.7181 1.4687
+#> 424: 93.1374 -6.0270 -1.9811 -4.4414 -0.9550 0.1787 6.7758 3.9674 1.1043 2.9866 0.2004 0.1807 5.7198 1.4693
+#> 425: 93.1383 -6.0270 -1.9811 -4.4420 -0.9551 0.1787 6.7547 3.9674 1.1042 2.9887 0.2003 0.1806 5.7211 1.4702
+#> 426: 93.1400 -6.0268 -1.9811 -4.4427 -0.9551 0.1789 6.7376 3.9654 1.1043 2.9917 0.2002 0.1805 5.7241 1.4706
+#> 427: 93.1391 -6.0268 -1.9811 -4.4433 -0.9552 0.1790 6.7196 3.9634 1.1045 2.9951 0.2001 0.1805 5.7271 1.4710
+#> 428: 93.1404 -6.0268 -1.9810 -4.4442 -0.9552 0.1792 6.7104 3.9628 1.1044 2.9999 0.2000 0.1803 5.7282 1.4712
+#> 429: 93.1431 -6.0265 -1.9810 -4.4450 -0.9553 0.1793 6.7029 3.9612 1.1045 3.0043 0.1999 0.1803 5.7293 1.4716
+#> 430: 93.1464 -6.0263 -1.9809 -4.4457 -0.9554 0.1795 6.6962 3.9606 1.1046 3.0074 0.1999 0.1802 5.7291 1.4724
+#> 431: 93.1485 -6.0267 -1.9809 -4.4460 -0.9555 0.1797 6.6865 3.9623 1.1046 3.0082 0.1998 0.1802 5.7287 1.4726
+#> 432: 93.1509 -6.0277 -1.9808 -4.4462 -0.9556 0.1798 6.6843 3.9658 1.1047 3.0086 0.1998 0.1801 5.7280 1.4727
+#> 433: 93.1528 -6.0289 -1.9806 -4.4464 -0.9557 0.1798 6.6840 3.9714 1.1049 3.0087 0.1998 0.1801 5.7282 1.4729
+#> 434: 93.1555 -6.0286 -1.9804 -4.4467 -0.9557 0.1798 6.6870 3.9693 1.1052 3.0094 0.1997 0.1800 5.7277 1.4729
+#> 435: 93.1574 -6.0290 -1.9803 -4.4467 -0.9558 0.1798 6.6893 3.9712 1.1055 3.0095 0.1996 0.1800 5.7278 1.4727
+#> 436: 93.1594 -6.0299 -1.9802 -4.4468 -0.9558 0.1798 6.6934 3.9749 1.1059 3.0103 0.1996 0.1801 5.7271 1.4727
+#> 437: 93.1600 -6.0311 -1.9800 -4.4469 -0.9558 0.1797 6.7010 3.9812 1.1065 3.0110 0.1996 0.1801 5.7275 1.4727
+#> 438: 93.1617 -6.0318 -1.9799 -4.4471 -0.9559 0.1796 6.7120 3.9865 1.1069 3.0121 0.1995 0.1801 5.7271 1.4727
+#> 439: 93.1634 -6.0329 -1.9798 -4.4472 -0.9559 0.1795 6.7279 3.9930 1.1075 3.0127 0.1995 0.1802 5.7268 1.4727
+#> 440: 93.1644 -6.0332 -1.9797 -4.4473 -0.9559 0.1794 6.7338 3.9962 1.1080 3.0136 0.1994 0.1803 5.7270 1.4726
+#> 441: 93.1654 -6.0335 -1.9795 -4.4477 -0.9558 0.1794 6.7435 3.9988 1.1085 3.0155 0.1994 0.1805 5.7274 1.4728
+#> 442: 93.1670 -6.0340 -1.9792 -4.4480 -0.9558 0.1794 6.7493 4.0028 1.1091 3.0173 0.1993 0.1808 5.7282 1.4729
+#> 443: 93.1685 -6.0346 -1.9790 -4.4485 -0.9558 0.1793 6.7577 4.0073 1.1092 3.0202 0.1992 0.1811 5.7267 1.4732
+#> 444: 93.1671 -6.0346 -1.9789 -4.4491 -0.9558 0.1792 6.7559 4.0069 1.1093 3.0238 0.1992 0.1813 5.7258 1.4733
+#> 445: 93.1655 -6.0355 -1.9789 -4.4497 -0.9557 0.1790 6.7552 4.0127 1.1094 3.0276 0.1992 0.1814 5.7262 1.4733
+#> 446: 93.1641 -6.0361 -1.9787 -4.4501 -0.9557 0.1789 6.7579 4.0169 1.1096 3.0306 0.1991 0.1816 5.7262 1.4732
+#> 447: 93.1628 -6.0363 -1.9786 -4.4503 -0.9556 0.1787 6.7680 4.0196 1.1099 3.0318 0.1991 0.1818 5.7258 1.4729
+#> 448: 93.1629 -6.0371 -1.9787 -4.4509 -0.9556 0.1786 6.7705 4.0248 1.1100 3.0358 0.1990 0.1820 5.7267 1.4725
+#> 449: 93.1626 -6.0381 -1.9785 -4.4510 -0.9556 0.1784 6.7800 4.0298 1.1101 3.0368 0.1989 0.1822 5.7266 1.4722
+#> 450: 93.1614 -6.0386 -1.9782 -4.4514 -0.9556 0.1782 6.7796 4.0316 1.1103 3.0392 0.1989 0.1824 5.7260 1.4720
+#> 451: 93.1603 -6.0397 -1.9779 -4.4518 -0.9556 0.1780 6.7799 4.0381 1.1107 3.0416 0.1988 0.1827 5.7264 1.4720
+#> 452: 93.1610 -6.0406 -1.9775 -4.4522 -0.9556 0.1777 6.7813 4.0424 1.1111 3.0443 0.1988 0.1828 5.7268 1.4719
+#> 453: 93.1618 -6.0414 -1.9771 -4.4523 -0.9556 0.1774 6.7814 4.0490 1.1115 3.0456 0.1987 0.1830 5.7262 1.4721
+#> 454: 93.1625 -6.0415 -1.9767 -4.4525 -0.9555 0.1771 6.7799 4.0499 1.1118 3.0473 0.1986 0.1831 5.7260 1.4723
+#> 455: 93.1636 -6.0412 -1.9765 -4.4528 -0.9555 0.1769 6.7778 4.0489 1.1123 3.0496 0.1985 0.1832 5.7268 1.4722
+#> 456: 93.1653 -6.0401 -1.9762 -4.4532 -0.9554 0.1768 6.7703 4.0441 1.1127 3.0517 0.1983 0.1834 5.7282 1.4725
+#> 457: 93.1672 -6.0396 -1.9760 -4.4535 -0.9554 0.1766 6.7683 4.0427 1.1129 3.0539 0.1982 0.1835 5.7281 1.4727
+#> 458: 93.1692 -6.0398 -1.9757 -4.4539 -0.9554 0.1765 6.7627 4.0450 1.1132 3.0570 0.1981 0.1835 5.7294 1.4729
+#> 459: 93.1708 -6.0402 -1.9756 -4.4542 -0.9554 0.1763 6.7615 4.0483 1.1133 3.0596 0.1980 0.1836 5.7320 1.4728
+#> 460: 93.1710 -6.0401 -1.9755 -4.4544 -0.9553 0.1762 6.7629 4.0487 1.1135 3.0615 0.1979 0.1835 5.7323 1.4730
+#> 461: 93.1708 -6.0403 -1.9755 -4.4546 -0.9552 0.1762 6.7639 4.0492 1.1136 3.0631 0.1978 0.1834 5.7321 1.4729
+#> 462: 93.1707 -6.0405 -1.9755 -4.4548 -0.9552 0.1760 6.7657 4.0506 1.1136 3.0647 0.1977 0.1833 5.7323 1.4727
+#> 463: 93.1690 -6.0403 -1.9755 -4.4548 -0.9551 0.1759 6.7607 4.0494 1.1136 3.0651 0.1976 0.1832 5.7332 1.4726
+#> 464: 93.1673 -6.0400 -1.9755 -4.4548 -0.9551 0.1758 6.7588 4.0480 1.1138 3.0652 0.1975 0.1832 5.7344 1.4724
+#> 465: 93.1657 -6.0399 -1.9755 -4.4548 -0.9550 0.1756 6.7601 4.0474 1.1138 3.0652 0.1974 0.1831 5.7350 1.4724
+#> 466: 93.1656 -6.0406 -1.9754 -4.4548 -0.9549 0.1755 6.7589 4.0514 1.1139 3.0658 0.1973 0.1831 5.7355 1.4723
+#> 467: 93.1657 -6.0408 -1.9753 -4.4548 -0.9549 0.1754 6.7558 4.0525 1.1139 3.0664 0.1972 0.1831 5.7358 1.4725
+#> 468: 93.1664 -6.0411 -1.9752 -4.4551 -0.9548 0.1753 6.7546 4.0551 1.1140 3.0679 0.1971 0.1832 5.7358 1.4723
+#> 469: 93.1667 -6.0412 -1.9751 -4.4552 -0.9547 0.1752 6.7547 4.0554 1.1141 3.0676 0.1970 0.1833 5.7354 1.4721
+#> 470: 93.1664 -6.0413 -1.9750 -4.4552 -0.9546 0.1751 6.7579 4.0564 1.1143 3.0676 0.1969 0.1833 5.7352 1.4718
+#> 471: 93.1656 -6.0411 -1.9750 -4.4553 -0.9545 0.1750 6.7611 4.0555 1.1142 3.0681 0.1968 0.1834 5.7354 1.4715
+#> 472: 93.1644 -6.0408 -1.9751 -4.4554 -0.9544 0.1749 6.7577 4.0542 1.1142 3.0686 0.1968 0.1834 5.7362 1.4712
+#> 473: 93.1632 -6.0405 -1.9751 -4.4554 -0.9543 0.1749 6.7527 4.0526 1.1141 3.0686 0.1967 0.1835 5.7363 1.4708
+#> 474: 93.1619 -6.0405 -1.9752 -4.4555 -0.9542 0.1748 6.7479 4.0521 1.1140 3.0689 0.1967 0.1835 5.7366 1.4705
+#> 475: 93.1609 -6.0413 -1.9753 -4.4557 -0.9542 0.1748 6.7469 4.0558 1.1139 3.0698 0.1967 0.1835 5.7379 1.4702
+#> 476: 93.1607 -6.0411 -1.9754 -4.4556 -0.9542 0.1747 6.7414 4.0549 1.1139 3.0697 0.1966 0.1835 5.7388 1.4698
+#> 477: 93.1597 -6.0413 -1.9754 -4.4560 -0.9542 0.1747 6.7321 4.0560 1.1137 3.0733 0.1966 0.1836 5.7392 1.4697
+#> 478: 93.1591 -6.0421 -1.9754 -4.4563 -0.9542 0.1745 6.7239 4.0608 1.1137 3.0765 0.1965 0.1836 5.7399 1.4697
+#> 479: 93.1589 -6.0438 -1.9754 -4.4564 -0.9542 0.1744 6.7150 4.0719 1.1136 3.0785 0.1964 0.1838 5.7421 1.4695
+#> 480: 93.1594 -6.0459 -1.9754 -4.4566 -0.9542 0.1742 6.7102 4.0895 1.1135 3.0807 0.1964 0.1839 5.7446 1.4695
+#> 481: 93.1604 -6.0472 -1.9754 -4.4570 -0.9542 0.1741 6.7104 4.1016 1.1135 3.0848 0.1964 0.1841 5.7456 1.4693
+#> 482: 93.1584 -6.0486 -1.9754 -4.4573 -0.9542 0.1739 6.7061 4.1152 1.1136 3.0877 0.1964 0.1842 5.7464 1.4690
+#> 483: 93.1561 -6.0501 -1.9754 -4.4576 -0.9541 0.1737 6.7067 4.1286 1.1135 3.0903 0.1963 0.1843 5.7475 1.4688
+#> 484: 93.1545 -6.0507 -1.9754 -4.4578 -0.9541 0.1737 6.7113 4.1362 1.1134 3.0918 0.1963 0.1845 5.7488 1.4687
+#> 485: 93.1524 -6.0507 -1.9754 -4.4583 -0.9540 0.1736 6.7094 4.1381 1.1134 3.0970 0.1964 0.1847 5.7496 1.4685
+#> 486: 93.1510 -6.0508 -1.9754 -4.4586 -0.9540 0.1735 6.7118 4.1405 1.1134 3.0996 0.1964 0.1847 5.7502 1.4682
+#> 487: 93.1495 -6.0507 -1.9755 -4.4591 -0.9539 0.1734 6.7128 4.1406 1.1134 3.1037 0.1965 0.1848 5.7510 1.4680
+#> 488: 93.1494 -6.0502 -1.9756 -4.4597 -0.9538 0.1734 6.7171 4.1384 1.1135 3.1081 0.1965 0.1848 5.7508 1.4677
+#> 489: 93.1497 -6.0497 -1.9756 -4.4604 -0.9538 0.1734 6.7188 4.1358 1.1135 3.1133 0.1966 0.1847 5.7499 1.4675
+#> 490: 93.1507 -6.0486 -1.9757 -4.4607 -0.9538 0.1735 6.7206 4.1319 1.1136 3.1157 0.1967 0.1847 5.7498 1.4672
+#> 491: 93.1507 -6.0476 -1.9757 -4.4612 -0.9537 0.1735 6.7141 4.1270 1.1136 3.1187 0.1968 0.1846 5.7503 1.4672
+#> 492: 93.1507 -6.0470 -1.9758 -4.4618 -0.9536 0.1735 6.7140 4.1238 1.1139 3.1218 0.1969 0.1846 5.7511 1.4669
+#> 493: 93.1513 -6.0468 -1.9758 -4.4623 -0.9535 0.1736 6.7214 4.1232 1.1141 3.1246 0.1970 0.1845 5.7514 1.4668
+#> 494: 93.1511 -6.0467 -1.9759 -4.4629 -0.9534 0.1737 6.7332 4.1232 1.1144 3.1278 0.1971 0.1845 5.7512 1.4664
+#> 495: 93.1511 -6.0464 -1.9761 -4.4635 -0.9533 0.1738 6.7377 4.1218 1.1145 3.1309 0.1972 0.1845 5.7515 1.4661
+#> 496: 93.1498 -6.0465 -1.9762 -4.4639 -0.9532 0.1739 6.7412 4.1241 1.1147 3.1325 0.1974 0.1845 5.7514 1.4657
+#> 497: 93.1482 -6.0467 -1.9764 -4.4644 -0.9532 0.1741 6.7506 4.1259 1.1149 3.1346 0.1975 0.1846 5.7513 1.4652
+#> 498: 93.1479 -6.0465 -1.9765 -4.4647 -0.9531 0.1743 6.7588 4.1263 1.1150 3.1357 0.1977 0.1846 5.7511 1.4648
+#> 499: 93.1462 -6.0455 -1.9766 -4.4651 -0.9530 0.1745 6.7659 4.1219 1.1152 3.1374 0.1978 0.1847 5.7515 1.4645
+#> 500: 93.1455 -6.0439 -1.9768 -4.4657 -0.9529 0.1747 6.7747 4.1151 1.1154 3.1404 0.1980 0.1848 5.7516 1.4641
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_k1 |
+#> |.....................| log_k2 | g_qlogis |sigma_parent | sigma_A1 |
+#> |.....................| o1 | o2 | o3 | o4 |
+#> |.....................| o5 | o6 |...........|...........|
+#> | 1| 488.12318 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 488.12318 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 488.12318 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | G| Gill Diff. | 52.24 | 2.364 | -0.1419 | 0.08101 |
+#> |.....................| -0.5200 | 0.08781 | -28.20 | -16.37 |
+#> |.....................| 14.83 | 13.24 | -12.01 | -2.482 |
+#> |.....................| 5.466 | -10.09 |...........|...........|
+#> | 2| 2642.5634 | 0.2192 | -1.035 | -0.9096 | -0.9332 |
+#> |.....................| -0.9743 | -0.8898 | -0.4296 | -0.6255 |
+#> |.....................| -1.099 | -1.073 | -0.6891 | -0.8357 |
+#> |.....................| -0.9567 | -0.7180 |...........|...........|
+#> | U| 2642.5634 | 20.48 | -5.348 | -0.9517 | -1.954 |
+#> |.....................| -4.421 | 0.1928 | 2.469 | 1.224 |
+#> |.....................| 0.5606 | 0.7036 | 1.386 | 1.005 |
+#> |.....................| 0.7896 | 1.336 |...........|...........|
+#> | X| 2642.5634 | 20.48 | 0.004759 | 0.2785 | 0.1417 |
+#> |.....................| 0.01202 | 0.5480 | 2.469 | 1.224 |
+#> |.....................| 0.5606 | 0.7036 | 1.386 | 1.005 |
+#> |.....................| 0.7896 | 1.336 |...........|...........|
+#> | 3| 546.98314 | 0.9219 | -1.004 | -0.9115 | -0.9321 |
+#> |.....................| -0.9813 | -0.8886 | -0.8089 | -0.8458 |
+#> |.....................| -0.9000 | -0.8944 | -0.8506 | -0.8691 |
+#> |.....................| -0.8831 | -0.8538 |...........|...........|
+#> | U| 546.98314 | 86.13 | -5.316 | -0.9535 | -1.953 |
+#> |.....................| -4.428 | 0.1930 | 2.082 | 1.104 |
+#> |.....................| 0.7044 | 0.8599 | 1.196 | 0.9723 |
+#> |.....................| 0.8529 | 1.178 |...........|...........|
+#> | X| 546.98314 | 86.13 | 0.004913 | 0.2782 | 0.1419 |
+#> |.....................| 0.01193 | 0.5481 | 2.082 | 1.104 |
+#> |.....................| 0.7044 | 0.8599 | 1.196 | 0.9723 |
+#> |.....................| 0.8529 | 1.178 |...........|...........|
+#> | 4| 506.37737 | 0.9922 | -1.000 | -0.9117 | -0.9320 |
+#> |.....................| -0.9820 | -0.8885 | -0.8469 | -0.8679 |
+#> |.....................| -0.8800 | -0.8766 | -0.8668 | -0.8724 |
+#> |.....................| -0.8758 | -0.8674 |...........|...........|
+#> | U| 506.37737 | 92.70 | -5.313 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.043 | 1.092 |
+#> |.....................| 0.7187 | 0.8755 | 1.177 | 0.9691 |
+#> |.....................| 0.8592 | 1.163 |...........|...........|
+#> | X| 506.37737 | 92.70 | 0.004928 | 0.2781 | 0.1419 |
+#> |.....................| 0.01193 | 0.5481 | 2.043 | 1.092 |
+#> |.....................| 0.7187 | 0.8755 | 1.177 | 0.9691 |
+#> |.....................| 0.8592 | 1.163 |...........|...........|
+#> | 5| 506.42840 | 0.9992 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8507 | -0.8701 |
+#> |.....................| -0.8780 | -0.8748 | -0.8684 | -0.8727 |
+#> |.....................| -0.8751 | -0.8687 |...........|...........|
+#> | U| 506.4284 | 93.35 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.091 |
+#> |.....................| 0.7202 | 0.8771 | 1.175 | 0.9688 |
+#> |.....................| 0.8598 | 1.161 |...........|...........|
+#> | X| 506.4284 | 93.35 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.091 |
+#> |.....................| 0.7202 | 0.8771 | 1.175 | 0.9688 |
+#> |.....................| 0.8598 | 1.161 |...........|...........|
+#> | 6| 506.47762 | 0.9999 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.47762 | 93.42 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.47762 | 93.42 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 7| 506.48298 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48298 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48298 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 8| 506.48363 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48363 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48363 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 9| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 10| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 11| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 12| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 13| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 14| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 15| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 16| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | 17| 506.48371 | 1.000 | -1.000 | -0.9117 | -0.9319 |
+#> |.....................| -0.9821 | -0.8885 | -0.8511 | -0.8703 |
+#> |.....................| -0.8778 | -0.8746 | -0.8686 | -0.8728 |
+#> |.....................| -0.8750 | -0.8689 |...........|...........|
+#> | U| 506.48371 | 93.43 | -5.312 | -0.9537 | -1.953 |
+#> |.....................| -4.429 | 0.1930 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> | X| 506.48371 | 93.43 | 0.004930 | 0.2781 | 0.1419 |
+#> |.....................| 0.01192 | 0.5481 | 2.039 | 1.090 |
+#> |.....................| 0.7203 | 0.8772 | 1.175 | 0.9687 |
+#> |.....................| 0.8599 | 1.161 |...........|...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[5]+THETA[5];
-#> rx_expr_14~exp(-(rx_expr_8));
-#> rx_expr_16~t*rx_expr_14;
-#> rx_expr_17~1+rx_expr_16;
-#> rx_expr_19~rx_expr_7-(rx_expr_8);
-#> rx_expr_21~exp(rx_expr_19);
-#> d/dt(parent)=-rx_expr_21*parent/(rx_expr_17);
-#> rx_expr_9~ETA[2]+THETA[2];
-#> rx_expr_11~exp(rx_expr_9);
-#> d/dt(A1)=-rx_expr_11*A1+rx_expr_21*parent*f_parent_to_A1/(rx_expr_17);
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_15~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_15+rx_expr_3;
-#> rx_hi_~rx_expr_15+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_10~parent*(rx_expr_2);
-#> rx_expr_18~rx_expr_10*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_18)*(rx_expr_0)+(rx_expr_4+rx_expr_18)*(rx_expr_2)*(rx_expr_1);
-#> rx_expr_12~Rx_pow_di(THETA[7],2);
-#> rx_expr_13~Rx_pow_di(THETA[6],2);
-#> rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_18)*(rx_expr_0)+(rx_expr_4+rx_expr_18)*(rx_expr_2)*(rx_expr_1)),2)*rx_expr_12+rx_expr_13)*(rx_expr_0)+(rx_expr_12*Rx_pow_di(((rx_expr_4+rx_expr_18)*(rx_expr_1)),2)+rx_expr_13)*(rx_expr_2)*(rx_expr_1);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_alpha=THETA[4];
-#> log_beta=THETA[5];
-#> sigma_low=THETA[6];
-#> rsd_high=THETA[7];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_alpha=ETA[4];
-#> eta.log_beta=ETA[5];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_11;
-#> alpha=exp(rx_expr_7);
-#> beta=exp(rx_expr_8);
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.455 0.377 8.841
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[6]+THETA[6];
-#> rx_expr_9~ETA[5]+THETA[5];
-#> rx_expr_12~exp(rx_expr_7);
-#> rx_expr_13~exp(rx_expr_9);
-#> rx_expr_15~t*rx_expr_12;
-#> rx_expr_16~t*rx_expr_13;
-#> rx_expr_19~exp(-(rx_expr_8));
-#> rx_expr_21~1+rx_expr_19;
-#> rx_expr_26~1/(rx_expr_21);
-#> rx_expr_28~(rx_expr_26);
-#> rx_expr_29~1-rx_expr_28;
-#> d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));
-#> rx_expr_10~ETA[2]+THETA[2];
-#> rx_expr_14~exp(rx_expr_10);
-#> d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_21)+exp(rx_expr_9-rx_expr_16)*(rx_expr_29))/(exp(-t*rx_expr_12)/(rx_expr_21)+exp(-t*rx_expr_13)*(rx_expr_29));
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_20~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_20+rx_expr_3;
-#> rx_hi_~rx_expr_20+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_11~parent*(rx_expr_2);
-#> rx_expr_24~rx_expr_11*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1);
-#> rx_expr_17~Rx_pow_di(THETA[8],2);
-#> rx_expr_18~Rx_pow_di(THETA[7],2);
-#> rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_0)+(rx_expr_4+rx_expr_24)*(rx_expr_2)*(rx_expr_1)),2)*rx_expr_17+rx_expr_18)*(rx_expr_0)+(rx_expr_17*Rx_pow_di(((rx_expr_4+rx_expr_24)*(rx_expr_1)),2)+rx_expr_18)*(rx_expr_2)*(rx_expr_1);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_k1=THETA[4];
-#> log_k2=THETA[5];
-#> g_qlogis=THETA[6];
-#> sigma_low=THETA[7];
-#> rsd_high=THETA[8];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_k1=ETA[4];
-#> eta.log_k2=ETA[5];
-#> eta.g_qlogis=ETA[6];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_14;
-#> k1=rx_expr_12;
-#> k2=rx_expr_13;
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> g=1/(rx_expr_21);
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.73 0.679 18.41
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_alpha |
+#> |.....................| log_beta | sigma_low | rsd_high | o1 |
+#> |.....................| o2 | o3 | o4 | o5 |
+#> | 1| 504.82714 | 1.000 | -1.000 | -0.9114 | -0.8944 |
+#> |.....................| -0.8457 | -0.8687 | -0.8916 | -0.8768 |
+#> |.....................| -0.8745 | -0.8676 | -0.8705 | -0.8704 |
+#> | U| 504.82714 | 93.12 | -5.303 | -0.9442 | -0.1065 |
+#> |.....................| 2.291 | 1.160 | 0.03005 | 0.7578 |
+#> |.....................| 0.8738 | 1.213 | 1.069 | 1.072 |
+#> | X| 504.82714 | 93.12 | 0.004975 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.160 | 0.03005 | 0.7578 |
+#> |.....................| 0.8738 | 1.213 | 1.069 | 1.072 |
+#> | G| Gill Diff. | 73.79 | 2.406 | 0.05615 | 0.2285 |
+#> |.....................| 0.009051 | -72.42 | -25.46 | 1.201 |
+#> |.....................| 11.89 | -10.88 | -9.982 | -10.81 |
+#> | 2| 4107.3121 | 0.3213 | -1.022 | -0.9119 | -0.8965 |
+#> |.....................| -0.8458 | -0.2026 | -0.6574 | -0.8879 |
+#> |.....................| -0.9839 | -0.7675 | -0.7787 | -0.7710 |
+#> | U| 4107.3121 | 29.92 | -5.326 | -0.9447 | -0.1086 |
+#> |.....................| 2.291 | 1.546 | 0.03357 | 0.7494 |
+#> |.....................| 0.7782 | 1.335 | 1.167 | 1.179 |
+#> | X| 4107.3121 | 29.92 | 0.004866 | 0.2800 | 0.8971 |
+#> |.....................| 9.883 | 1.546 | 0.03357 | 0.7494 |
+#> |.....................| 0.7782 | 1.335 | 1.167 | 1.179 |
+#> | 3| 528.17103 | 0.9321 | -1.002 | -0.9115 | -0.8946 |
+#> |.....................| -0.8457 | -0.8021 | -0.8682 | -0.8779 |
+#> |.....................| -0.8854 | -0.8576 | -0.8613 | -0.8605 |
+#> | U| 528.17103 | 86.80 | -5.306 | -0.9442 | -0.1067 |
+#> |.....................| 2.291 | 1.198 | 0.03041 | 0.7570 |
+#> |.....................| 0.8642 | 1.226 | 1.079 | 1.083 |
+#> | X| 528.17103 | 86.80 | 0.004964 | 0.2800 | 0.8988 |
+#> |.....................| 9.884 | 1.198 | 0.03041 | 0.7570 |
+#> |.....................| 0.8642 | 1.226 | 1.079 | 1.083 |
+#> | 4| 503.95550 | 0.9892 | -1.000 | -0.9114 | -0.8944 |
+#> |.....................| -0.8457 | -0.8581 | -0.8879 | -0.8770 |
+#> |.....................| -0.8762 | -0.8660 | -0.8691 | -0.8689 |
+#> | U| 503.9555 | 92.11 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.166 | 0.03011 | 0.7577 |
+#> |.....................| 0.8723 | 1.215 | 1.070 | 1.074 |
+#> | X| 503.9555 | 92.11 | 0.004973 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.166 | 0.03011 | 0.7577 |
+#> |.....................| 0.8723 | 1.215 | 1.070 | 1.074 |
+#> | F| Forward Diff. | -82.12 | 2.266 | -0.2557 | 0.1457 |
+#> |.....................| -0.3150 | -70.09 | -26.27 | 1.274 |
+#> |.....................| 9.305 | -11.84 | -9.592 | -10.45 |
+#> | 5| 503.06948 | 1.000 | -1.001 | -0.9114 | -0.8944 |
+#> |.....................| -0.8456 | -0.8479 | -0.8841 | -0.8772 |
+#> |.....................| -0.8776 | -0.8643 | -0.8677 | -0.8674 |
+#> | U| 503.06948 | 93.16 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.172 | 0.03017 | 0.7575 |
+#> |.....................| 0.8711 | 1.217 | 1.072 | 1.075 |
+#> | X| 503.06948 | 93.16 | 0.004971 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.172 | 0.03017 | 0.7575 |
+#> |.....................| 0.8711 | 1.217 | 1.072 | 1.075 |
+#> | F| Forward Diff. | 78.20 | 2.380 | 0.07920 | 0.2489 |
+#> |.....................| 0.04185 | -69.32 | -24.13 | 1.306 |
+#> |.....................| 9.997 | -11.88 | -9.541 | -10.51 |
+#> | 6| 502.21512 | 0.9895 | -1.001 | -0.9114 | -0.8945 |
+#> |.....................| -0.8456 | -0.8375 | -0.8805 | -0.8774 |
+#> |.....................| -0.8791 | -0.8625 | -0.8662 | -0.8658 |
+#> | U| 502.21512 | 92.14 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.178 | 0.03022 | 0.7574 |
+#> |.....................| 0.8698 | 1.220 | 1.073 | 1.077 |
+#> | X| 502.21512 | 92.14 | 0.004969 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.178 | 0.03022 | 0.7574 |
+#> |.....................| 0.8698 | 1.220 | 1.073 | 1.077 |
+#> | F| Forward Diff. | -79.18 | 2.245 | -0.2400 | 0.1569 |
+#> |.....................| -0.2882 | -67.02 | -25.09 | 1.000 |
+#> |.....................| 9.365 | -11.67 | -9.440 | -10.32 |
+#> | 7| 501.33312 | 1.000 | -1.001 | -0.9114 | -0.8945 |
+#> |.....................| -0.8456 | -0.8270 | -0.8765 | -0.8775 |
+#> |.....................| -0.8805 | -0.8607 | -0.8647 | -0.8642 |
+#> | U| 501.33312 | 93.14 | -5.305 | -0.9441 | -0.1067 |
+#> |.....................| 2.291 | 1.184 | 0.03028 | 0.7573 |
+#> |.....................| 0.8685 | 1.222 | 1.075 | 1.079 |
+#> | X| 501.33312 | 93.14 | 0.004968 | 0.2801 | 0.8988 |
+#> |.....................| 9.884 | 1.184 | 0.03028 | 0.7573 |
+#> |.....................| 0.8685 | 1.222 | 1.075 | 1.079 |
+#> | F| Forward Diff. | 73.96 | 2.351 | 0.08380 | 0.2565 |
+#> |.....................| 0.05289 | -66.42 | -23.08 | 0.9343 |
+#> |.....................| 11.48 | -11.71 | -9.377 | -10.38 |
+#> | 8| 500.50460 | 0.9897 | -1.002 | -0.9114 | -0.8946 |
+#> |.....................| -0.8456 | -0.8163 | -0.8728 | -0.8777 |
+#> |.....................| -0.8824 | -0.8588 | -0.8632 | -0.8625 |
+#> | U| 500.5046 | 92.16 | -5.305 | -0.9442 | -0.1067 |
+#> |.....................| 2.291 | 1.190 | 0.03034 | 0.7572 |
+#> |.....................| 0.8669 | 1.224 | 1.077 | 1.081 |
+#> | X| 500.5046 | 92.16 | 0.004966 | 0.2801 | 0.8988 |
+#> |.....................| 9.884 | 1.190 | 0.03034 | 0.7572 |
+#> |.....................| 0.8669 | 1.224 | 1.077 | 1.081 |
+#> | F| Forward Diff. | -76.85 | 2.219 | -0.2273 | 0.1675 |
+#> |.....................| -0.2752 | -63.09 | -23.56 | 1.068 |
+#> |.....................| 8.794 | -11.52 | -9.279 | -10.19 |
+#> | 9| 499.65692 | 1.000 | -1.002 | -0.9113 | -0.8946 |
+#> |.....................| -0.8456 | -0.8056 | -0.8689 | -0.8779 |
+#> |.....................| -0.8839 | -0.8568 | -0.8617 | -0.8608 |
+#> | U| 499.65692 | 93.14 | -5.306 | -0.9441 | -0.1067 |
+#> |.....................| 2.291 | 1.196 | 0.03040 | 0.7570 |
+#> |.....................| 0.8655 | 1.226 | 1.078 | 1.082 |
+#> | X| 499.65692 | 93.14 | 0.004964 | 0.2801 | 0.8988 |
+#> |.....................| 9.885 | 1.196 | 0.03040 | 0.7570 |
+#> |.....................| 0.8655 | 1.226 | 1.078 | 1.082 |
+#> | F| Forward Diff. | 72.32 | 2.320 | 0.09176 | 0.2615 |
+#> |.....................| 0.06934 | -62.36 | -21.54 | 1.140 |
+#> |.....................| 9.404 | -11.56 | -9.216 | -10.24 |
+#> | 10| 498.81870 | 0.9902 | -1.003 | -0.9114 | -0.8946 |
+#> |.....................| -0.8456 | -0.7946 | -0.8650 | -0.8781 |
+#> |.....................| -0.8856 | -0.8548 | -0.8600 | -0.8589 |
+#> | U| 498.8187 | 92.21 | -5.306 | -0.9441 | -0.1068 |
+#> |.....................| 2.291 | 1.203 | 0.03045 | 0.7569 |
+#> |.....................| 0.8641 | 1.229 | 1.080 | 1.084 |
+#> | X| 498.8187 | 92.21 | 0.004962 | 0.2801 | 0.8987 |
+#> |.....................| 9.885 | 1.203 | 0.03045 | 0.7569 |
+#> |.....................| 0.8641 | 1.229 | 1.080 | 1.084 |
+#> | F| Forward Diff. | -70.56 | 2.198 | -0.2057 | 0.1798 |
+#> |.....................| -0.2468 | -59.74 | -22.28 | 0.8150 |
+#> |.....................| 7.180 | -11.33 | -9.109 | -10.05 |
+#> | 11| 497.99655 | 1.000 | -1.003 | -0.9113 | -0.8947 |
+#> |.....................| -0.8455 | -0.7835 | -0.8609 | -0.8782 |
+#> |.....................| -0.8869 | -0.8527 | -0.8583 | -0.8571 |
+#> | U| 497.99655 | 93.13 | -5.306 | -0.9441 | -0.1068 |
+#> |.....................| 2.291 | 1.209 | 0.03052 | 0.7568 |
+#> |.....................| 0.8629 | 1.231 | 1.082 | 1.086 |
+#> | X| 497.99655 | 93.13 | 0.004960 | 0.2801 | 0.8987 |
+#> |.....................| 9.885 | 1.209 | 0.03052 | 0.7568 |
+#> |.....................| 0.8629 | 1.231 | 1.082 | 1.086 |
+#> | F| Forward Diff. | 69.16 | 2.293 | 0.1087 | 0.2725 |
+#> |.....................| 0.08752 | -59.63 | -20.54 | 0.7584 |
+#> |.....................| 10.86 | -11.45 | -9.094 | -10.13 |
+#> | 12| 497.16410 | 0.9907 | -1.003 | -0.9113 | -0.8947 |
+#> |.....................| -0.8455 | -0.7720 | -0.8569 | -0.8784 |
+#> |.....................| -0.8889 | -0.8505 | -0.8566 | -0.8551 |
+#> | U| 497.1641 | 92.25 | -5.307 | -0.9441 | -0.1069 |
+#> |.....................| 2.291 | 1.216 | 0.03058 | 0.7566 |
+#> |.....................| 0.8612 | 1.234 | 1.084 | 1.088 |
+#> | X| 497.1641 | 92.25 | 0.004958 | 0.2801 | 0.8987 |
+#> |.....................| 9.885 | 1.216 | 0.03058 | 0.7566 |
+#> |.....................| 0.8612 | 1.234 | 1.084 | 1.088 |
+#> | F| Forward Diff. | -65.09 | 2.175 | -0.1829 | 0.1920 |
+#> |.....................| -0.2233 | -56.76 | -21.02 | 0.6415 |
+#> |.....................| 9.983 | -11.18 | -8.930 | -9.895 |
+#> | 13| 496.40281 | 1.000 | -1.004 | -0.9113 | -0.8948 |
+#> |.....................| -0.8455 | -0.7609 | -0.8528 | -0.8785 |
+#> |.....................| -0.8909 | -0.8483 | -0.8548 | -0.8532 |
+#> | U| 496.40281 | 93.15 | -5.307 | -0.9441 | -0.1069 |
+#> |.....................| 2.291 | 1.222 | 0.03064 | 0.7566 |
+#> |.....................| 0.8594 | 1.237 | 1.086 | 1.091 |
+#> | X| 496.40281 | 93.15 | 0.004955 | 0.2801 | 0.8986 |
+#> |.....................| 9.885 | 1.222 | 0.03064 | 0.7566 |
+#> |.....................| 0.8594 | 1.237 | 1.086 | 1.091 |
+#> | F| Forward Diff. | 70.05 | 2.265 | 0.1236 | 0.2851 |
+#> |.....................| 0.1152 | -55.71 | -19.12 | 0.8701 |
+#> |.....................| 7.394 | -11.22 | -8.890 | -9.949 |
+#> | 14| 495.59236 | 0.9910 | -1.004 | -0.9113 | -0.8948 |
+#> |.....................| -0.8455 | -0.7494 | -0.8488 | -0.8787 |
+#> |.....................| -0.8926 | -0.8459 | -0.8530 | -0.8511 |
+#> | U| 495.59236 | 92.28 | -5.308 | -0.9441 | -0.1070 |
+#> |.....................| 2.291 | 1.229 | 0.03070 | 0.7564 |
+#> |.....................| 0.8580 | 1.240 | 1.088 | 1.093 |
+#> | X| 495.59236 | 92.28 | 0.004953 | 0.2801 | 0.8986 |
+#> |.....................| 9.885 | 1.229 | 0.03070 | 0.7564 |
+#> |.....................| 0.8580 | 1.240 | 1.088 | 1.093 |
+#> | F| Forward Diff. | -61.97 | 2.150 | -0.1619 | 0.2028 |
+#> |.....................| -0.2007 | -53.46 | -19.76 | 0.5341 |
+#> |.....................| 9.715 | -10.96 | -8.745 | -9.729 |
+#> | 15| 494.82198 | 1.000 | -1.005 | -0.9113 | -0.8949 |
+#> |.....................| -0.8455 | -0.7378 | -0.8446 | -0.8788 |
+#> |.....................| -0.8946 | -0.8435 | -0.8510 | -0.8489 |
+#> | U| 494.82198 | 93.11 | -5.308 | -0.9441 | -0.1070 |
+#> |.....................| 2.291 | 1.235 | 0.03076 | 0.7563 |
+#> |.....................| 0.8562 | 1.243 | 1.090 | 1.095 |
+#> | X| 494.82198 | 93.11 | 0.004951 | 0.2801 | 0.8985 |
+#> |.....................| 9.886 | 1.235 | 0.03076 | 0.7563 |
+#> |.....................| 0.8562 | 1.243 | 1.090 | 1.095 |
+#> | F| Forward Diff. | 62.35 | 2.229 | 0.1203 | 0.2879 |
+#> |.....................| 0.1180 | -52.16 | -17.88 | 0.7550 |
+#> |.....................| 8.431 | -10.99 | -8.665 | -9.736 |
+#> | 16| 494.07821 | 0.9910 | -1.005 | -0.9113 | -0.8949 |
+#> |.....................| -0.8455 | -0.7261 | -0.8406 | -0.8789 |
+#> |.....................| -0.8966 | -0.8410 | -0.8490 | -0.8467 |
+#> | U| 494.07821 | 92.28 | -5.309 | -0.9441 | -0.1071 |
+#> |.....................| 2.291 | 1.242 | 0.03082 | 0.7562 |
+#> |.....................| 0.8544 | 1.246 | 1.092 | 1.098 |
+#> | X| 494.07821 | 92.28 | 0.004948 | 0.2801 | 0.8985 |
+#> |.....................| 9.885 | 1.242 | 0.03082 | 0.7562 |
+#> |.....................| 0.8544 | 1.246 | 1.092 | 1.098 |
+#> | F| Forward Diff. | -62.97 | 2.119 | -0.1628 | 0.2103 |
+#> |.....................| -0.1835 | -49.97 | -18.50 | 0.4855 |
+#> |.....................| 6.275 | -10.75 | -8.529 | -9.546 |
+#> | 17| 493.31030 | 0.9997 | -1.006 | -0.9113 | -0.8950 |
+#> |.....................| -0.8455 | -0.7143 | -0.8363 | -0.8790 |
+#> |.....................| -0.8981 | -0.8383 | -0.8469 | -0.8443 |
+#> | U| 493.3103 | 93.08 | -5.309 | -0.9441 | -0.1071 |
+#> |.....................| 2.291 | 1.249 | 0.03089 | 0.7561 |
+#> |.....................| 0.8531 | 1.249 | 1.094 | 1.100 |
+#> | X| 493.3103 | 93.08 | 0.004946 | 0.2801 | 0.8984 |
+#> |.....................| 9.886 | 1.249 | 0.03089 | 0.7561 |
+#> |.....................| 0.8531 | 1.249 | 1.094 | 1.100 |
+#> | F| Forward Diff. | 56.08 | 2.195 | 0.1067 | 0.2931 |
+#> |.....................| 0.1254 | -49.64 | -16.98 | 0.3491 |
+#> |.....................| 8.549 | -10.78 | -8.455 | -9.552 |
+#> | 18| 492.59068 | 0.9914 | -1.006 | -0.9113 | -0.8951 |
+#> |.....................| -0.8455 | -0.7023 | -0.8321 | -0.8791 |
+#> |.....................| -0.9000 | -0.8355 | -0.8448 | -0.8419 |
+#> | U| 492.59068 | 92.32 | -5.310 | -0.9441 | -0.1072 |
+#> |.....................| 2.291 | 1.256 | 0.03095 | 0.7561 |
+#> |.....................| 0.8514 | 1.252 | 1.096 | 1.103 |
+#> | X| 492.59068 | 92.32 | 0.004943 | 0.2801 | 0.8983 |
+#> |.....................| 9.885 | 1.256 | 0.03095 | 0.7561 |
+#> |.....................| 0.8514 | 1.252 | 1.096 | 1.103 |
+#> | F| Forward Diff. | -58.13 | 2.097 | -0.1289 | 0.2246 |
+#> |.....................| -0.1582 | -47.13 | -17.33 | 0.3097 |
+#> |.....................| 7.738 | -10.54 | -8.304 | -9.345 |
+#> | 19| 491.88063 | 0.9998 | -1.007 | -0.9113 | -0.8951 |
+#> |.....................| -0.8455 | -0.6905 | -0.8279 | -0.8791 |
+#> |.....................| -0.9022 | -0.8327 | -0.8426 | -0.8394 |
+#> | U| 491.88063 | 93.10 | -5.310 | -0.9441 | -0.1073 |
+#> |.....................| 2.291 | 1.263 | 0.03101 | 0.7561 |
+#> |.....................| 0.8496 | 1.256 | 1.099 | 1.105 |
+#> | X| 491.88063 | 93.10 | 0.004940 | 0.2801 | 0.8983 |
+#> |.....................| 9.886 | 1.263 | 0.03101 | 0.7561 |
+#> |.....................| 0.8496 | 1.256 | 1.099 | 1.105 |
+#> | F| Forward Diff. | 56.71 | 2.166 | 0.1292 | 0.3076 |
+#> |.....................| 0.1542 | -45.57 | -15.60 | 0.4873 |
+#> |.....................| 6.413 | -10.51 | -8.202 | -9.332 |
+#> | 20| 491.19020 | 0.9917 | -1.008 | -0.9113 | -0.8952 |
+#> |.....................| -0.8455 | -0.6785 | -0.8237 | -0.8792 |
+#> |.....................| -0.9039 | -0.8296 | -0.8402 | -0.8366 |
+#> | U| 491.1902 | 92.34 | -5.311 | -0.9441 | -0.1074 |
+#> |.....................| 2.291 | 1.270 | 0.03107 | 0.7560 |
+#> |.....................| 0.8481 | 1.259 | 1.101 | 1.108 |
+#> | X| 491.1902 | 92.34 | 0.004937 | 0.2801 | 0.8982 |
+#> |.....................| 9.885 | 1.270 | 0.03107 | 0.7560 |
+#> |.....................| 0.8481 | 1.259 | 1.101 | 1.108 |
+#> | F| Forward Diff. | -55.56 | 2.070 | -0.1130 | 0.2359 |
+#> |.....................| -0.1346 | -44.07 | -16.23 | 0.1008 |
+#> |.....................| 7.464 | -10.26 | -8.060 | -9.125 |
+#> | 21| 490.47868 | 0.9993 | -1.008 | -0.9113 | -0.8953 |
+#> |.....................| -0.8455 | -0.6665 | -0.8194 | -0.8791 |
+#> |.....................| -0.9059 | -0.8264 | -0.8377 | -0.8337 |
+#> | U| 490.47868 | 93.05 | -5.312 | -0.9441 | -0.1075 |
+#> |.....................| 2.291 | 1.277 | 0.03114 | 0.7561 |
+#> |.....................| 0.8463 | 1.263 | 1.104 | 1.111 |
+#> | X| 490.47868 | 93.05 | 0.004934 | 0.2801 | 0.8981 |
+#> |.....................| 9.885 | 1.277 | 0.03114 | 0.7561 |
+#> |.....................| 0.8463 | 1.263 | 1.104 | 1.111 |
+#> | F| Forward Diff. | 47.93 | 2.132 | 0.1269 | 0.3117 |
+#> |.....................| 0.1562 | -43.27 | -14.78 | 0.06906 |
+#> |.....................| 9.295 | -10.26 | -7.955 | -9.092 |
+#> | 22| 489.84765 | 0.9918 | -1.009 | -0.9114 | -0.8954 |
+#> |.....................| -0.8456 | -0.6545 | -0.8153 | -0.8790 |
+#> |.....................| -0.9090 | -0.8231 | -0.8352 | -0.8308 |
+#> | U| 489.84765 | 92.35 | -5.312 | -0.9441 | -0.1076 |
+#> |.....................| 2.291 | 1.284 | 0.03120 | 0.7562 |
+#> |.....................| 0.8436 | 1.267 | 1.107 | 1.115 |
+#> | X| 489.84765 | 92.35 | 0.004930 | 0.2801 | 0.8980 |
+#> |.....................| 9.885 | 1.284 | 0.03120 | 0.7562 |
+#> |.....................| 0.8436 | 1.267 | 1.107 | 1.115 |
+#> | F| Forward Diff. | -55.71 | 2.038 | -0.1283 | 0.2328 |
+#> |.....................| -0.1164 | -41.15 | -15.14 | 0.009736 |
+#> |.....................| 8.505 | -10.03 | -7.805 | -8.885 |
+#> | 23| 489.17644 | 0.9994 | -1.010 | -0.9113 | -0.8955 |
+#> |.....................| -0.8456 | -0.6429 | -0.8112 | -0.8788 |
+#> |.....................| -0.9126 | -0.8197 | -0.8325 | -0.8278 |
+#> | U| 489.17644 | 93.06 | -5.313 | -0.9441 | -0.1077 |
+#> |.....................| 2.291 | 1.290 | 0.03126 | 0.7563 |
+#> |.....................| 0.8405 | 1.272 | 1.109 | 1.118 |
+#> | X| 489.17644 | 93.06 | 0.004927 | 0.2801 | 0.8979 |
+#> |.....................| 9.885 | 1.290 | 0.03126 | 0.7563 |
+#> |.....................| 0.8405 | 1.272 | 1.109 | 1.118 |
+#> | F| Forward Diff. | 46.87 | 2.093 | 0.1493 | 0.3243 |
+#> |.....................| 0.1838 | -40.03 | -13.57 | 0.1411 |
+#> |.....................| 5.593 | -9.957 | -7.669 | -8.831 |
+#> | 24| 488.58015 | 0.9920 | -1.011 | -0.9114 | -0.8957 |
+#> |.....................| -0.8457 | -0.6309 | -0.8071 | -0.8787 |
+#> |.....................| -0.9147 | -0.8159 | -0.8297 | -0.8244 |
+#> | U| 488.58015 | 92.37 | -5.314 | -0.9442 | -0.1078 |
+#> |.....................| 2.291 | 1.297 | 0.03132 | 0.7564 |
+#> |.....................| 0.8386 | 1.276 | 1.112 | 1.121 |
+#> | X| 488.58015 | 92.37 | 0.004923 | 0.2801 | 0.8978 |
+#> |.....................| 9.884 | 1.297 | 0.03132 | 0.7564 |
+#> |.....................| 0.8386 | 1.276 | 1.112 | 1.121 |
+#> | F| Forward Diff. | -53.50 | 2.005 | -0.1078 | 0.2446 |
+#> |.....................| -0.09190 | -37.89 | -13.87 | 0.05672 |
+#> |.....................| 4.909 | -9.713 | -7.511 | -8.606 |
+#> | 25| 487.93833 | 0.9991 | -1.011 | -0.9114 | -0.8958 |
+#> |.....................| -0.8457 | -0.6190 | -0.8030 | -0.8785 |
+#> |.....................| -0.9153 | -0.8117 | -0.8266 | -0.8207 |
+#> | U| 487.93833 | 93.04 | -5.315 | -0.9442 | -0.1080 |
+#> |.....................| 2.291 | 1.304 | 0.03139 | 0.7566 |
+#> |.....................| 0.8381 | 1.281 | 1.116 | 1.125 |
+#> | X| 487.93833 | 93.04 | 0.004918 | 0.2801 | 0.8977 |
+#> |.....................| 9.883 | 1.304 | 0.03139 | 0.7566 |
+#> |.....................| 0.8381 | 1.281 | 1.116 | 1.125 |
+#> | F| Forward Diff. | 41.92 | 2.065 | 0.1569 | 0.3320 |
+#> |.....................| 0.1961 | -37.34 | -12.63 | 0.01172 |
+#> |.....................| 5.301 | -9.646 | -7.360 | -8.530 |
+#> | 26| 487.37063 | 0.9925 | -1.012 | -0.9115 | -0.8960 |
+#> |.....................| -0.8458 | -0.6069 | -0.7990 | -0.8783 |
+#> |.....................| -0.9161 | -0.8073 | -0.8233 | -0.8168 |
+#> | U| 487.37063 | 92.42 | -5.316 | -0.9443 | -0.1081 |
+#> |.....................| 2.291 | 1.311 | 0.03145 | 0.7567 |
+#> |.....................| 0.8374 | 1.287 | 1.119 | 1.130 |
+#> | X| 487.37063 | 92.42 | 0.004913 | 0.2800 | 0.8975 |
+#> |.....................| 9.882 | 1.311 | 0.03145 | 0.7567 |
+#> |.....................| 0.8374 | 1.287 | 1.119 | 1.130 |
+#> | F| Forward Diff. | -47.84 | 1.989 | -0.08553 | 0.2559 |
+#> |.....................| -0.06263 | -35.59 | -12.91 | -0.09336 |
+#> |.....................| 8.020 | -9.356 | -7.180 | -8.291 |
+#> | 27| 486.76802 | 0.9991 | -1.014 | -0.9115 | -0.8962 |
+#> |.....................| -0.8459 | -0.5954 | -0.7952 | -0.8779 |
+#> |.....................| -0.9197 | -0.8027 | -0.8200 | -0.8127 |
+#> | U| 486.76802 | 93.03 | -5.317 | -0.9443 | -0.1083 |
+#> |.....................| 2.291 | 1.318 | 0.03150 | 0.7570 |
+#> |.....................| 0.8342 | 1.292 | 1.123 | 1.134 |
+#> | X| 486.76802 | 93.03 | 0.004908 | 0.2800 | 0.8973 |
+#> |.....................| 9.881 | 1.318 | 0.03150 | 0.7570 |
+#> |.....................| 0.8342 | 1.292 | 1.123 | 1.134 |
+#> | F| Forward Diff. | 39.28 | 2.032 | 0.1697 | 0.3409 |
+#> |.....................| 0.2161 | -34.26 | -11.60 | -0.04206 |
+#> |.....................| 6.414 | -9.258 | -7.014 | -8.183 |
+#> | 28| 486.25961 | 0.9924 | -1.015 | -0.9116 | -0.8964 |
+#> |.....................| -0.8461 | -0.5843 | -0.7916 | -0.8775 |
+#> |.....................| -0.9242 | -0.7980 | -0.8166 | -0.8086 |
+#> | U| 486.25961 | 92.41 | -5.318 | -0.9444 | -0.1086 |
+#> |.....................| 2.290 | 1.324 | 0.03156 | 0.7573 |
+#> |.....................| 0.8303 | 1.298 | 1.126 | 1.138 |
+#> | X| 486.25961 | 92.41 | 0.004902 | 0.2800 | 0.8971 |
+#> |.....................| 9.880 | 1.324 | 0.03156 | 0.7573 |
+#> |.....................| 0.8303 | 1.298 | 1.126 | 1.138 |
+#> | F| Forward Diff. | -50.63 | 1.945 | -0.07307 | 0.2626 |
+#> |.....................| -0.04930 | -33.11 | -12.03 | -0.1686 |
+#> |.....................| 7.510 | -8.984 | -6.802 | -7.934 |
+#> | 29| 485.66844 | 0.9985 | -1.016 | -0.9117 | -0.8967 |
+#> |.....................| -0.8462 | -0.5738 | -0.7881 | -0.8769 |
+#> |.....................| -0.9293 | -0.7927 | -0.8129 | -0.8039 |
+#> | U| 485.66844 | 92.98 | -5.319 | -0.9445 | -0.1089 |
+#> |.....................| 2.290 | 1.331 | 0.03161 | 0.7578 |
+#> |.....................| 0.8259 | 1.304 | 1.130 | 1.143 |
+#> | X| 485.66844 | 92.98 | 0.004895 | 0.2800 | 0.8969 |
+#> |.....................| 9.878 | 1.331 | 0.03161 | 0.7578 |
+#> |.....................| 0.8259 | 1.304 | 1.130 | 1.143 |
+#> | F| Forward Diff. | 30.24 | 1.977 | 0.1746 | 0.3455 |
+#> |.....................| 0.2218 | -32.22 | -10.87 | -0.2249 |
+#> |.....................| 4.336 | -8.820 | -6.615 | -7.812 |
+#> | 30| 485.23968 | 0.9921 | -1.017 | -0.9119 | -0.8970 |
+#> |.....................| -0.8465 | -0.5622 | -0.7845 | -0.8762 |
+#> |.....................| -0.9314 | -0.7876 | -0.8094 | -0.7994 |
+#> | U| 485.23968 | 92.38 | -5.321 | -0.9447 | -0.1091 |
+#> |.....................| 2.290 | 1.337 | 0.03166 | 0.7583 |
+#> |.....................| 0.8240 | 1.310 | 1.134 | 1.148 |
+#> | X| 485.23968 | 92.38 | 0.004889 | 0.2800 | 0.8966 |
+#> |.....................| 9.876 | 1.337 | 0.03166 | 0.7583 |
+#> |.....................| 0.8240 | 1.310 | 1.134 | 1.148 |
+#> | F| Forward Diff. | -56.59 | 1.902 | -0.07536 | 0.2678 |
+#> |.....................| -0.04797 | -30.46 | -11.14 | -0.09043 |
+#> |.....................| 3.742 | -8.533 | -6.412 | -7.541 |
+#> | 31| 484.69662 | 0.9984 | -1.019 | -0.9121 | -0.8974 |
+#> |.....................| -0.8467 | -0.5517 | -0.7813 | -0.8754 |
+#> |.....................| -0.9289 | -0.7816 | -0.8053 | -0.7941 |
+#> | U| 484.69662 | 92.97 | -5.322 | -0.9448 | -0.1095 |
+#> |.....................| 2.290 | 1.343 | 0.03171 | 0.7589 |
+#> |.....................| 0.8262 | 1.318 | 1.138 | 1.154 |
+#> | X| 484.69662 | 92.97 | 0.004881 | 0.2799 | 0.8963 |
+#> |.....................| 9.873 | 1.343 | 0.03171 | 0.7589 |
+#> |.....................| 0.8262 | 1.318 | 1.138 | 1.154 |
+#> | F| Forward Diff. | 27.47 | 1.960 | 0.1737 | 0.3487 |
+#> |.....................| 0.2320 | -29.84 | -10.04 | -0.2714 |
+#> |.....................| 5.731 | -8.337 | -6.228 | -7.371 |
+#> | 32| 484.27605 | 0.9928 | -1.021 | -0.9123 | -0.8978 |
+#> |.....................| -0.8471 | -0.5404 | -0.7779 | -0.8746 |
+#> |.....................| -0.9302 | -0.7757 | -0.8014 | -0.7889 |
+#> | U| 484.27605 | 92.45 | -5.324 | -0.9451 | -0.1099 |
+#> |.....................| 2.289 | 1.350 | 0.03176 | 0.7595 |
+#> |.....................| 0.8251 | 1.325 | 1.143 | 1.159 |
+#> | X| 484.27605 | 92.45 | 0.004872 | 0.2799 | 0.8959 |
+#> |.....................| 9.870 | 1.350 | 0.03176 | 0.7595 |
+#> |.....................| 0.8251 | 1.325 | 1.143 | 1.159 |
+#> | F| Forward Diff. | -48.28 | 1.894 | -0.05804 | 0.2769 |
+#> |.....................| -0.01457 | -28.21 | -10.24 | -0.1977 |
+#> |.....................| 5.253 | -8.027 | -5.998 | -7.085 |
+#> | 33| 483.77365 | 0.9986 | -1.023 | -0.9126 | -0.8983 |
+#> |.....................| -0.8475 | -0.5309 | -0.7752 | -0.8734 |
+#> |.....................| -0.9343 | -0.7690 | -0.7970 | -0.7831 |
+#> | U| 483.77365 | 92.99 | -5.326 | -0.9453 | -0.1104 |
+#> |.....................| 2.289 | 1.355 | 0.03180 | 0.7604 |
+#> |.....................| 0.8215 | 1.333 | 1.147 | 1.166 |
+#> | X| 483.77365 | 92.99 | 0.004861 | 0.2798 | 0.8954 |
+#> |.....................| 9.866 | 1.355 | 0.03180 | 0.7604 |
+#> |.....................| 0.8215 | 1.333 | 1.147 | 1.166 |
+#> | F| Forward Diff. | 28.59 | 1.923 | 0.1952 | 0.3548 |
+#> |.....................| 0.2608 | -27.76 | -9.333 | -0.3645 |
+#> |.....................| 3.958 | -7.814 | -5.777 | -6.894 |
+#> | 34| 483.37086 | 0.9934 | -1.025 | -0.9129 | -0.8989 |
+#> |.....................| -0.8480 | -0.5203 | -0.7721 | -0.8720 |
+#> |.....................| -0.9349 | -0.7624 | -0.7928 | -0.7774 |
+#> | U| 483.37086 | 92.51 | -5.329 | -0.9456 | -0.1110 |
+#> |.....................| 2.289 | 1.362 | 0.03185 | 0.7615 |
+#> |.....................| 0.8209 | 1.341 | 1.152 | 1.172 |
+#> | X| 483.37086 | 92.51 | 0.004850 | 0.2798 | 0.8949 |
+#> |.....................| 9.861 | 1.362 | 0.03185 | 0.7615 |
+#> |.....................| 0.8209 | 1.341 | 1.152 | 1.172 |
+#> | F| Forward Diff. | -41.16 | 1.862 | -0.03265 | 0.2828 |
+#> |.....................| 0.01951 | -26.43 | -9.488 | -0.2833 |
+#> |.....................| 3.545 | -7.469 | -5.528 | -6.584 |
+#> | 35| 482.96272 | 0.9987 | -1.028 | -0.9132 | -0.8995 |
+#> |.....................| -0.8485 | -0.5103 | -0.7694 | -0.8702 |
+#> |.....................| -0.9315 | -0.7558 | -0.7888 | -0.7716 |
+#> | U| 482.96272 | 92.99 | -5.332 | -0.9459 | -0.1117 |
+#> |.....................| 2.288 | 1.367 | 0.03189 | 0.7629 |
+#> |.....................| 0.8240 | 1.349 | 1.156 | 1.178 |
+#> | X| 482.96272 | 92.99 | 0.004836 | 0.2797 | 0.8943 |
+#> |.....................| 9.856 | 1.367 | 0.03189 | 0.7629 |
+#> |.....................| 0.8240 | 1.349 | 1.156 | 1.178 |
+#> | F| Forward Diff. | 28.21 | 1.908 | 0.1917 | 0.3504 |
+#> |.....................| 0.2712 | -25.82 | -8.599 | -0.3385 |
+#> |.....................| 4.050 | -7.278 | -5.334 | -6.398 |
+#> | 36| 482.60011 | 0.9939 | -1.032 | -0.9136 | -0.9003 |
+#> |.....................| -0.8492 | -0.4998 | -0.7669 | -0.8684 |
+#> |.....................| -0.9296 | -0.7490 | -0.7849 | -0.7659 |
+#> | U| 482.60011 | 92.55 | -5.335 | -0.9462 | -0.1124 |
+#> |.....................| 2.287 | 1.373 | 0.03193 | 0.7642 |
+#> |.....................| 0.8256 | 1.357 | 1.160 | 1.184 |
+#> | X| 482.60011 | 92.55 | 0.004820 | 0.2796 | 0.8937 |
+#> |.....................| 9.849 | 1.373 | 0.03193 | 0.7642 |
+#> |.....................| 0.8256 | 1.357 | 1.160 | 1.184 |
+#> | F| Forward Diff. | -36.31 | 1.855 | -0.03781 | 0.2769 |
+#> |.....................| 0.03076 | -24.99 | -8.890 | -0.4685 |
+#> |.....................| 7.176 | -6.892 | -5.117 | -6.081 |
+#> | 37| 482.21198 | 0.9982 | -1.035 | -0.9138 | -0.9009 |
+#> |.....................| -0.8497 | -0.4920 | -0.7653 | -0.8661 |
+#> |.....................| -0.9399 | -0.7441 | -0.7821 | -0.7617 |
+#> | U| 482.21198 | 92.95 | -5.338 | -0.9465 | -0.1130 |
+#> |.....................| 2.287 | 1.378 | 0.03195 | 0.7659 |
+#> |.....................| 0.8166 | 1.363 | 1.163 | 1.189 |
+#> | X| 482.21198 | 92.95 | 0.004805 | 0.2796 | 0.8931 |
+#> |.....................| 9.844 | 1.378 | 0.03195 | 0.7659 |
+#> |.....................| 0.8166 | 1.363 | 1.163 | 1.189 |
+#> | F| Forward Diff. | 20.01 | 1.850 | 0.1852 | 0.3312 |
+#> |.....................| 0.2616 | -23.95 | -7.997 | -0.3393 |
+#> |.....................| 4.985 | -6.711 | -4.923 | -5.940 |
+#> | 38| 481.96846 | 0.9924 | -1.037 | -0.9141 | -0.9014 |
+#> |.....................| -0.8503 | -0.4828 | -0.7630 | -0.8646 |
+#> |.....................| -0.9490 | -0.7399 | -0.7795 | -0.7579 |
+#> | U| 481.96846 | 92.41 | -5.341 | -0.9468 | -0.1136 |
+#> |.....................| 2.286 | 1.383 | 0.03199 | 0.7671 |
+#> |.....................| 0.8087 | 1.368 | 1.166 | 1.193 |
+#> | X| 481.96846 | 92.41 | 0.004793 | 0.2795 | 0.8927 |
+#> |.....................| 9.838 | 1.383 | 0.03199 | 0.7671 |
+#> |.....................| 0.8087 | 1.368 | 1.166 | 1.193 |
+#> | F| Forward Diff. | -59.26 | 1.761 | -0.08116 | 0.2547 |
+#> |.....................| -0.02692 | -22.78 | -8.366 | -0.2344 |
+#> |.....................| 4.087 | -6.524 | -4.792 | -5.748 |
+#> | 39| 481.52549 | 0.9980 | -1.042 | -0.9148 | -0.9024 |
+#> |.....................| -0.8514 | -0.4755 | -0.7621 | -0.8625 |
+#> |.....................| -0.9558 | -0.7333 | -0.7761 | -0.7520 |
+#> | U| 481.52549 | 92.93 | -5.345 | -0.9474 | -0.1146 |
+#> |.....................| 2.285 | 1.388 | 0.03200 | 0.7686 |
+#> |.....................| 0.8027 | 1.376 | 1.170 | 1.199 |
+#> | X| 481.52549 | 92.93 | 0.004770 | 0.2794 | 0.8917 |
+#> |.....................| 9.827 | 1.388 | 0.03200 | 0.7686 |
+#> |.....................| 0.8027 | 1.376 | 1.170 | 1.199 |
+#> | F| Forward Diff. | 14.56 | 1.771 | 0.1903 | 0.3270 |
+#> |.....................| 0.2641 | -22.44 | -7.508 | -0.4496 |
+#> |.....................| 2.566 | -6.373 | -4.622 | -5.584 |
+#> | 40| 481.26396 | 0.9932 | -1.045 | -0.9155 | -0.9032 |
+#> |.....................| -0.8523 | -0.4642 | -0.7593 | -0.8605 |
+#> |.....................| -0.9543 | -0.7272 | -0.7727 | -0.7469 |
+#> | U| 481.26396 | 92.49 | -5.349 | -0.9480 | -0.1154 |
+#> |.....................| 2.284 | 1.394 | 0.03204 | 0.7702 |
+#> |.....................| 0.8040 | 1.384 | 1.173 | 1.205 |
+#> | X| 481.26396 | 92.49 | 0.004753 | 0.2793 | 0.8910 |
+#> |.....................| 9.818 | 1.394 | 0.03204 | 0.7702 |
+#> |.....................| 0.8040 | 1.384 | 1.173 | 1.205 |
+#> | F| Forward Diff. | -49.84 | 1.721 | -0.06329 | 0.2500 |
+#> |.....................| 0.003387 | -21.58 | -7.808 | -0.4470 |
+#> |.....................| 3.805 | -6.020 | -4.412 | -5.292 |
+#> | 41| 480.91101 | 0.9981 | -1.051 | -0.9163 | -0.9044 |
+#> |.....................| -0.8537 | -0.4552 | -0.7584 | -0.8559 |
+#> |.....................| -0.9510 | -0.7207 | -0.7698 | -0.7416 |
+#> | U| 480.91101 | 92.94 | -5.355 | -0.9488 | -0.1166 |
+#> |.....................| 2.283 | 1.399 | 0.03206 | 0.7737 |
+#> |.....................| 0.8069 | 1.392 | 1.176 | 1.210 |
+#> | X| 480.91101 | 92.94 | 0.004727 | 0.2791 | 0.8900 |
+#> |.....................| 9.804 | 1.399 | 0.03206 | 0.7737 |
+#> |.....................| 0.8069 | 1.392 | 1.176 | 1.210 |
+#> | F| Forward Diff. | 16.05 | 1.751 | 0.1631 | 0.3020 |
+#> |.....................| 0.2540 | -20.90 | -6.928 | -0.3893 |
+#> |.....................| 4.288 | -5.817 | -4.263 | -5.144 |
+#> | 42| 480.64341 | 0.9941 | -1.056 | -0.9169 | -0.9053 |
+#> |.....................| -0.8549 | -0.4456 | -0.7571 | -0.8527 |
+#> |.....................| -0.9585 | -0.7158 | -0.7673 | -0.7373 |
+#> | U| 480.64341 | 92.57 | -5.360 | -0.9493 | -0.1175 |
+#> |.....................| 2.282 | 1.405 | 0.03208 | 0.7761 |
+#> |.....................| 0.8004 | 1.398 | 1.179 | 1.215 |
+#> | X| 480.64341 | 92.57 | 0.004703 | 0.2790 | 0.8892 |
+#> |.....................| 9.793 | 1.405 | 0.03208 | 0.7761 |
+#> |.....................| 0.8004 | 1.398 | 1.179 | 1.215 |
+#> | F| Forward Diff. | -40.16 | 1.680 | -0.01378 | 0.2424 |
+#> |.....................| 0.03021 | -20.27 | -7.228 | -0.4675 |
+#> |.....................| 4.140 | -5.523 | -4.100 | -4.903 |
+#> | 43| 480.34062 | 0.9982 | -1.062 | -0.9177 | -0.9064 |
+#> |.....................| -0.8561 | -0.4387 | -0.7572 | -0.8486 |
+#> |.....................| -0.9687 | -0.7122 | -0.7655 | -0.7338 |
+#> | U| 480.34062 | 92.95 | -5.365 | -0.9501 | -0.1185 |
+#> |.....................| 2.280 | 1.409 | 0.03207 | 0.7792 |
+#> |.....................| 0.7914 | 1.402 | 1.181 | 1.219 |
+#> | X| 480.34062 | 92.95 | 0.004675 | 0.2789 | 0.8883 |
+#> |.....................| 9.781 | 1.409 | 0.03207 | 0.7792 |
+#> |.....................| 0.7914 | 1.402 | 1.181 | 1.219 |
+#> | 44| 480.11354 | 0.9982 | -1.069 | -0.9186 | -0.9075 |
+#> |.....................| -0.8576 | -0.4327 | -0.7582 | -0.8437 |
+#> |.....................| -0.9807 | -0.7086 | -0.7639 | -0.7301 |
+#> | U| 480.11354 | 92.95 | -5.372 | -0.9510 | -0.1197 |
+#> |.....................| 2.279 | 1.412 | 0.03206 | 0.7829 |
+#> |.....................| 0.7810 | 1.406 | 1.183 | 1.223 |
+#> | X| 480.11354 | 92.95 | 0.004643 | 0.2787 | 0.8872 |
+#> |.....................| 9.767 | 1.412 | 0.03206 | 0.7829 |
+#> |.....................| 0.7810 | 1.406 | 1.183 | 1.223 |
+#> | 45| 479.24256 | 0.9982 | -1.100 | -0.9228 | -0.9129 |
+#> |.....................| -0.8642 | -0.4061 | -0.7626 | -0.8221 |
+#> |.....................| -1.034 | -0.6924 | -0.7565 | -0.7138 |
+#> | U| 479.24256 | 92.95 | -5.404 | -0.9550 | -0.1250 |
+#> |.....................| 2.272 | 1.428 | 0.03199 | 0.7993 |
+#> |.....................| 0.7344 | 1.426 | 1.191 | 1.240 |
+#> | X| 479.24256 | 92.95 | 0.004500 | 0.2779 | 0.8825 |
+#> |.....................| 9.702 | 1.428 | 0.03199 | 0.7993 |
+#> |.....................| 0.7344 | 1.426 | 1.191 | 1.240 |
+#> | 46| 477.60836 | 1.003 | -1.228 | -0.9400 | -0.9346 |
+#> |.....................| -0.8912 | -0.2901 | -0.7784 | -0.7332 |
+#> |.....................| -1.206 | -0.6258 | -0.7257 | -0.6466 |
+#> | U| 477.60836 | 93.40 | -5.531 | -0.9712 | -0.1467 |
+#> |.....................| 2.245 | 1.495 | 0.03176 | 0.8667 |
+#> |.....................| 0.5843 | 1.507 | 1.224 | 1.312 |
+#> | X| 477.60836 | 93.40 | 0.003961 | 0.2746 | 0.8635 |
+#> |.....................| 9.444 | 1.495 | 0.03176 | 0.8667 |
+#> |.....................| 0.5843 | 1.507 | 1.224 | 1.312 |
+#> | F| Forward Diff. | 50.81 | 0.8332 | 0.6263 | 0.04339 |
+#> |.....................| 0.5543 | -9.740 | -2.969 | 0.1978 |
+#> |.....................| -10.28 | -2.761 | -1.505 | -1.849 |
+#> | 47| 476.77966 | 1.006 | -1.398 | -0.9862 | -0.9532 |
+#> |.....................| -0.9413 | -0.07616 | -0.7687 | -0.6374 |
+#> |.....................| -0.9573 | -0.5395 | -0.7103 | -0.5930 |
+#> | U| 476.77966 | 93.71 | -5.701 | -1.015 | -0.1654 |
+#> |.....................| 2.195 | 1.619 | 0.03190 | 0.9393 |
+#> |.....................| 0.8014 | 1.612 | 1.240 | 1.369 |
+#> | X| 476.77966 | 93.71 | 0.003342 | 0.2660 | 0.8476 |
+#> |.....................| 8.982 | 1.619 | 0.03190 | 0.9393 |
+#> |.....................| 0.8014 | 1.612 | 1.240 | 1.369 |
+#> | F| Forward Diff. | 100.8 | 0.5681 | -2.148 | -0.2910 |
+#> |.....................| -0.6169 | 0.8458 | 0.8586 | 0.3650 |
+#> |.....................| 3.820 | 1.443 | -0.7364 | 0.2440 |
+#> | 48| 478.65806 | 0.9952 | -1.512 | -0.6913 | -0.9031 |
+#> |.....................| -0.8317 | -0.01918 | -0.7109 | -0.6555 |
+#> |.....................| -0.9083 | -0.7021 | -0.6121 | -0.6260 |
+#> | U| 478.65806 | 92.67 | -5.815 | -0.7363 | -0.1152 |
+#> |.....................| 2.305 | 1.652 | 0.03277 | 0.9255 |
+#> |.....................| 0.8442 | 1.414 | 1.345 | 1.334 |
+#> | X| 478.65806 | 92.67 | 0.002982 | 0.3238 | 0.8912 |
+#> |.....................| 10.02 | 1.652 | 0.03277 | 0.9255 |
+#> |.....................| 0.8442 | 1.414 | 1.345 | 1.334 |
+#> | 49| 476.83500 | 0.9931 | -1.426 | -0.9118 | -0.9406 |
+#> |.....................| -0.9137 | -0.06192 | -0.7543 | -0.6420 |
+#> |.....................| -0.9454 | -0.5805 | -0.6855 | -0.6013 |
+#> | U| 476.835 | 92.48 | -5.730 | -0.9445 | -0.1527 |
+#> |.....................| 2.223 | 1.627 | 0.03212 | 0.9358 |
+#> |.....................| 0.8118 | 1.562 | 1.267 | 1.361 |
+#> | X| 476.835 | 92.48 | 0.003247 | 0.2800 | 0.8584 |
+#> |.....................| 9.234 | 1.627 | 0.03212 | 0.9358 |
+#> |.....................| 0.8118 | 1.562 | 1.267 | 1.361 |
+#> | 50| 476.86775 | 0.9928 | -1.411 | -0.9513 | -0.9473 |
+#> |.....................| -0.9284 | -0.06958 | -0.7620 | -0.6396 |
+#> |.....................| -0.9520 | -0.5587 | -0.6987 | -0.5969 |
+#> | U| 476.86775 | 92.44 | -5.715 | -0.9819 | -0.1595 |
+#> |.....................| 2.208 | 1.623 | 0.03200 | 0.9376 |
+#> |.....................| 0.8060 | 1.588 | 1.252 | 1.365 |
+#> | X| 476.86775 | 92.44 | 0.003297 | 0.2725 | 0.8526 |
+#> |.....................| 9.099 | 1.623 | 0.03200 | 0.9376 |
+#> |.....................| 0.8060 | 1.588 | 1.252 | 1.365 |
+#> | 51| 476.94436 | 0.9926 | -1.403 | -0.9724 | -0.9509 |
+#> |.....................| -0.9362 | -0.07366 | -0.7662 | -0.6383 |
+#> |.....................| -0.9556 | -0.5471 | -0.7057 | -0.5945 |
+#> | U| 476.94436 | 92.42 | -5.706 | -1.002 | -0.1630 |
+#> |.....................| 2.200 | 1.621 | 0.03194 | 0.9386 |
+#> |.....................| 0.8029 | 1.602 | 1.245 | 1.368 |
+#> | X| 476.94436 | 92.42 | 0.003324 | 0.2686 | 0.8496 |
+#> |.....................| 9.028 | 1.621 | 0.03194 | 0.9386 |
+#> |.....................| 0.8029 | 1.602 | 1.245 | 1.368 |
+#> | 52| 476.64580 | 0.9959 | -1.398 | -0.9860 | -0.9532 |
+#> |.....................| -0.9413 | -0.07625 | -0.7688 | -0.6374 |
+#> |.....................| -0.9577 | -0.5396 | -0.7102 | -0.5930 |
+#> | U| 476.6458 | 92.74 | -5.701 | -1.015 | -0.1653 |
+#> |.....................| 2.195 | 1.619 | 0.03190 | 0.9392 |
+#> |.....................| 0.8011 | 1.611 | 1.240 | 1.369 |
+#> | X| 476.6458 | 92.74 | 0.003342 | 0.2661 | 0.8476 |
+#> |.....................| 8.983 | 1.619 | 0.03190 | 0.9392 |
+#> |.....................| 0.8011 | 1.611 | 1.240 | 1.369 |
+#> | F| Forward Diff. | -76.03 | 0.4748 | -3.401 | -0.5335 |
+#> |.....................| -1.858 | 1.570 | -0.1336 | 0.2990 |
+#> |.....................| 3.107 | 1.921 | -0.6340 | 0.6252 |
+#> | 53| 476.45477 | 1.000 | -1.400 | -0.9787 | -0.9521 |
+#> |.....................| -0.9380 | -0.07508 | -0.7683 | -0.6381 |
+#> |.....................| -0.9567 | -0.5427 | -0.7079 | -0.5935 |
+#> | U| 476.45477 | 93.14 | -5.704 | -1.008 | -0.1642 |
+#> |.....................| 2.199 | 1.620 | 0.03191 | 0.9387 |
+#> |.....................| 0.8019 | 1.608 | 1.243 | 1.369 |
+#> | X| 476.45477 | 93.14 | 0.003334 | 0.2674 | 0.8486 |
+#> |.....................| 9.012 | 1.620 | 0.03191 | 0.9387 |
+#> |.....................| 0.8019 | 1.608 | 1.243 | 1.369 |
+#> | F| Forward Diff. | 0.2803 | 0.4975 | -2.426 | -0.4122 |
+#> |.....................| -1.237 | 1.245 | 0.3711 | 0.1250 |
+#> |.....................| 4.601 | 1.480 | -0.5654 | 0.4236 |
+#> | 54| 476.38303 | 0.9998 | -1.401 | -0.9743 | -0.9513 |
+#> |.....................| -0.9358 | -0.07732 | -0.7690 | -0.6383 |
+#> |.....................| -0.9650 | -0.5454 | -0.7069 | -0.5943 |
+#> | U| 476.38303 | 93.10 | -5.704 | -1.004 | -0.1635 |
+#> |.....................| 2.201 | 1.618 | 0.03190 | 0.9385 |
+#> |.....................| 0.7947 | 1.604 | 1.244 | 1.368 |
+#> | X| 476.38303 | 93.10 | 0.003331 | 0.2682 | 0.8492 |
+#> |.....................| 9.032 | 1.618 | 0.03190 | 0.9385 |
+#> |.....................| 0.7947 | 1.604 | 1.244 | 1.368 |
+#> | 55| 476.22864 | 0.9983 | -1.404 | -0.9612 | -0.9491 |
+#> |.....................| -0.9291 | -0.08404 | -0.7710 | -0.6390 |
+#> |.....................| -0.9898 | -0.5533 | -0.7039 | -0.5966 |
+#> | U| 476.22864 | 92.96 | -5.707 | -0.9912 | -0.1612 |
+#> |.....................| 2.207 | 1.614 | 0.03187 | 0.9380 |
+#> |.....................| 0.7730 | 1.595 | 1.247 | 1.366 |
+#> | X| 476.22864 | 92.96 | 0.003322 | 0.2707 | 0.8511 |
+#> |.....................| 9.093 | 1.614 | 0.03187 | 0.9380 |
+#> |.....................| 0.7730 | 1.595 | 1.247 | 1.366 |
+#> | 56| 476.57199 | 0.9958 | -1.445 | -0.8532 | -0.9271 |
+#> |.....................| -0.8725 | -0.06353 | -0.7679 | -0.6421 |
+#> |.....................| -0.9751 | -0.5970 | -0.6712 | -0.6082 |
+#> | U| 476.57199 | 92.73 | -5.749 | -0.8892 | -0.1393 |
+#> |.....................| 2.264 | 1.626 | 0.03191 | 0.9357 |
+#> |.....................| 0.7859 | 1.542 | 1.282 | 1.353 |
+#> | X| 476.57199 | 92.73 | 0.003186 | 0.2913 | 0.8700 |
+#> |.....................| 9.623 | 1.626 | 0.03191 | 0.9357 |
+#> |.....................| 0.7859 | 1.542 | 1.282 | 1.353 |
+#> | F| Forward Diff. | -32.75 | 0.5399 | -1.515 | -0.3941 |
+#> |.....................| -1.151 | 1.245 | 0.03890 | 0.2327 |
+#> |.....................| 2.518 | 0.9004 | -0.2852 | 0.3306 |
+#> | 57| 476.21990 | 0.9982 | -1.515 | -0.9538 | -0.8974 |
+#> |.....................| -0.8289 | -0.1020 | -0.7526 | -0.6734 |
+#> |.....................| -0.9899 | -0.5334 | -0.6863 | -0.5986 |
+#> | U| 476.2199 | 92.95 | -5.819 | -0.9842 | -0.1096 |
+#> |.....................| 2.308 | 1.604 | 0.03214 | 0.9120 |
+#> |.....................| 0.7729 | 1.619 | 1.266 | 1.364 |
+#> | X| 476.2199 | 92.95 | 0.002972 | 0.2721 | 0.8962 |
+#> |.....................| 10.05 | 1.604 | 0.03214 | 0.9120 |
+#> |.....................| 0.7729 | 1.619 | 1.266 | 1.364 |
+#> | F| Forward Diff. | -17.29 | 0.1752 | -1.213 | 0.7541 |
+#> |.....................| 1.907 | 0.8055 | -0.1948 | -0.02118 |
+#> |.....................| 1.522 | 1.784 | 0.5826 | 0.3001 |
+#> | 58| 476.15328 | 0.9997 | -1.587 | -0.9380 | -0.8926 |
+#> |.....................| -0.8393 | -0.1057 | -0.7294 | -0.6920 |
+#> |.....................| -0.9908 | -0.5546 | -0.6943 | -0.5998 |
+#> | U| 476.15328 | 93.09 | -5.890 | -0.9693 | -0.1048 |
+#> |.....................| 2.297 | 1.602 | 0.03249 | 0.8979 |
+#> |.....................| 0.7721 | 1.593 | 1.257 | 1.362 |
+#> | X| 476.15328 | 93.09 | 0.002766 | 0.2750 | 0.9005 |
+#> |.....................| 9.947 | 1.602 | 0.03249 | 0.8979 |
+#> |.....................| 0.7721 | 1.593 | 1.257 | 1.362 |
+#> | F| Forward Diff. | 9.478 | -0.04668 | -0.07764 | 0.8847 |
+#> |.....................| 1.686 | 1.059 | 0.2200 | -0.09397 |
+#> |.....................| 3.078 | 0.7416 | 0.1570 | 0.2315 |
+#> | 59| 476.01802 | 1.000 | -1.651 | -0.9570 | -0.8992 |
+#> |.....................| -0.8607 | -0.1274 | -0.7088 | -0.7141 |
+#> |.....................| -1.015 | -0.5543 | -0.6984 | -0.6027 |
+#> | U| 476.01802 | 93.12 | -5.954 | -0.9872 | -0.1113 |
+#> |.....................| 2.276 | 1.589 | 0.03280 | 0.8811 |
+#> |.....................| 0.7512 | 1.594 | 1.253 | 1.359 |
+#> | X| 476.01802 | 93.12 | 0.002594 | 0.2715 | 0.8947 |
+#> |.....................| 9.736 | 1.589 | 0.03280 | 0.8811 |
+#> |.....................| 0.7512 | 1.594 | 1.253 | 1.359 |
+#> | 60| 476.22711 | 1.004 | -1.844 | -1.014 | -0.9185 |
+#> |.....................| -0.9244 | -0.1921 | -0.6470 | -0.7805 |
+#> |.....................| -1.085 | -0.5529 | -0.7106 | -0.6114 |
+#> | U| 476.22711 | 93.52 | -6.147 | -1.041 | -0.1307 |
+#> |.....................| 2.212 | 1.552 | 0.03373 | 0.8308 |
+#> |.....................| 0.6895 | 1.595 | 1.240 | 1.350 |
+#> | X| 476.22711 | 93.52 | 0.002140 | 0.2610 | 0.8775 |
+#> |.....................| 9.136 | 1.552 | 0.03373 | 0.8308 |
+#> |.....................| 0.6895 | 1.595 | 1.240 | 1.350 |
+#> | F| Forward Diff. | 11.37 | -0.1053 | -1.010 | 0.7448 |
+#> |.....................| 1.048 | 0.2820 | 0.2022 | -0.3140 |
+#> |.....................| 0.8239 | 0.7199 | -0.08354 | 0.05077 |
+#> | 61| 477.73164 | 0.9986 | -1.783 | -0.8482 | -1.092 |
+#> |.....................| -0.9355 | -0.2068 | -0.7199 | -0.6608 |
+#> |.....................| -1.022 | -0.4554 | -0.5612 | -0.5707 |
+#> | U| 477.73164 | 92.99 | -6.086 | -0.8845 | -0.3044 |
+#> |.....................| 2.201 | 1.543 | 0.03264 | 0.9215 |
+#> |.....................| 0.7445 | 1.714 | 1.399 | 1.393 |
+#> | X| 477.73164 | 92.99 | 0.002274 | 0.2922 | 0.7376 |
+#> |.....................| 9.035 | 1.543 | 0.03264 | 0.9215 |
+#> |.....................| 0.7445 | 1.714 | 1.399 | 1.393 |
+#> | 62| 476.07192 | 0.9962 | -1.664 | -0.9459 | -0.9184 |
+#> |.....................| -0.8684 | -0.1353 | -0.7100 | -0.7087 |
+#> |.....................| -1.016 | -0.5448 | -0.6848 | -0.5995 |
+#> | U| 476.07192 | 92.76 | -5.967 | -0.9768 | -0.1306 |
+#> |.....................| 2.268 | 1.585 | 0.03278 | 0.8852 |
+#> |.....................| 0.7503 | 1.605 | 1.267 | 1.362 |
+#> | X| 476.07192 | 92.76 | 0.002561 | 0.2735 | 0.8776 |
+#> |.....................| 9.662 | 1.585 | 0.03278 | 0.8852 |
+#> |.....................| 0.7503 | 1.605 | 1.267 | 1.362 |
+#> | 63| 476.10587 | 0.9957 | -1.654 | -0.9539 | -0.9043 |
+#> |.....................| -0.8630 | -0.1295 | -0.7092 | -0.7126 |
+#> |.....................| -1.015 | -0.5521 | -0.6949 | -0.6019 |
+#> | U| 476.10587 | 92.72 | -5.958 | -0.9843 | -0.1164 |
+#> |.....................| 2.274 | 1.588 | 0.03280 | 0.8822 |
+#> |.....................| 0.7508 | 1.596 | 1.257 | 1.360 |
+#> | X| 476.10587 | 92.72 | 0.002586 | 0.2720 | 0.8901 |
+#> |.....................| 9.714 | 1.588 | 0.03280 | 0.8822 |
+#> |.....................| 0.7508 | 1.596 | 1.257 | 1.360 |
+#> | 64| 476.02413 | 0.9981 | -1.651 | -0.9568 | -0.8993 |
+#> |.....................| -0.8609 | -0.1274 | -0.7088 | -0.7140 |
+#> |.....................| -1.015 | -0.5544 | -0.6984 | -0.6027 |
+#> | U| 476.02413 | 92.94 | -5.954 | -0.9870 | -0.1114 |
+#> |.....................| 2.276 | 1.589 | 0.03280 | 0.8812 |
+#> |.....................| 0.7511 | 1.593 | 1.253 | 1.359 |
+#> | X| 476.02413 | 92.94 | 0.002594 | 0.2715 | 0.8946 |
+#> |.....................| 9.735 | 1.589 | 0.03280 | 0.8812 |
+#> |.....................| 0.7511 | 1.593 | 1.253 | 1.359 |
+#> | 65| 476.01367 | 0.9993 | -1.651 | -0.9569 | -0.8992 |
+#> |.....................| -0.8608 | -0.1274 | -0.7088 | -0.7141 |
+#> |.....................| -1.015 | -0.5543 | -0.6984 | -0.6027 |
+#> | U| 476.01367 | 93.05 | -5.954 | -0.9871 | -0.1114 |
+#> |.....................| 2.276 | 1.589 | 0.03280 | 0.8812 |
+#> |.....................| 0.7512 | 1.594 | 1.253 | 1.359 |
+#> | X| 476.01367 | 93.05 | 0.002594 | 0.2715 | 0.8946 |
+#> |.....................| 9.736 | 1.589 | 0.03280 | 0.8812 |
+#> |.....................| 0.7512 | 1.594 | 1.253 | 1.359 |
+#> | F| Forward Diff. | -0.2880 | -0.1104 | -1.088 | 0.7255 |
+#> |.....................| 0.9655 | -0.09765 | 0.02713 | -0.4308 |
+#> |.....................| 1.898 | 0.6709 | -0.08067 | 0.06084 |
+#> | 66| 476.01068 | 0.9993 | -1.651 | -0.9566 | -0.8994 |
+#> |.....................| -0.8610 | -0.1274 | -0.7088 | -0.7139 |
+#> |.....................| -1.015 | -0.5545 | -0.6983 | -0.6027 |
+#> | U| 476.01068 | 93.06 | -5.954 | -0.9868 | -0.1116 |
+#> |.....................| 2.276 | 1.589 | 0.03280 | 0.8813 |
+#> |.....................| 0.7507 | 1.593 | 1.253 | 1.359 |
+#> | X| 476.01068 | 93.06 | 0.002595 | 0.2715 | 0.8944 |
+#> |.....................| 9.733 | 1.589 | 0.03280 | 0.8813 |
+#> |.....................| 0.7507 | 1.593 | 1.253 | 1.359 |
+#> | 67| 476.00249 | 0.9996 | -1.651 | -0.9556 | -0.9000 |
+#> |.....................| -0.8619 | -0.1273 | -0.7089 | -0.7136 |
+#> |.....................| -1.017 | -0.5551 | -0.6983 | -0.6027 |
+#> | U| 476.00249 | 93.08 | -5.954 | -0.9860 | -0.1122 |
+#> |.....................| 2.275 | 1.589 | 0.03280 | 0.8815 |
+#> |.....................| 0.7493 | 1.593 | 1.253 | 1.359 |
+#> | X| 476.00249 | 93.08 | 0.002595 | 0.2717 | 0.8939 |
+#> |.....................| 9.725 | 1.589 | 0.03280 | 0.8815 |
+#> |.....................| 0.7493 | 1.593 | 1.253 | 1.359 |
+#> | 68| 475.98648 | 0.9997 | -1.654 | -0.9518 | -0.9062 |
+#> |.....................| -0.8643 | -0.1288 | -0.7101 | -0.7095 |
+#> |.....................| -1.019 | -0.5521 | -0.6956 | -0.6031 |
+#> | U| 475.98648 | 93.09 | -5.957 | -0.9823 | -0.1183 |
+#> |.....................| 2.272 | 1.589 | 0.03278 | 0.8846 |
+#> |.....................| 0.7477 | 1.596 | 1.256 | 1.359 |
+#> | X| 475.98648 | 93.09 | 0.002587 | 0.2724 | 0.8884 |
+#> |.....................| 9.702 | 1.589 | 0.03278 | 0.8846 |
+#> |.....................| 0.7477 | 1.596 | 1.256 | 1.359 |
+#> | 69| 475.97179 | 0.9994 | -1.666 | -0.9399 | -0.9282 |
+#> |.....................| -0.8710 | -0.1347 | -0.7147 | -0.6948 |
+#> |.....................| -1.020 | -0.5387 | -0.6854 | -0.6045 |
+#> | U| 475.97179 | 93.06 | -5.969 | -0.9711 | -0.1404 |
+#> |.....................| 2.266 | 1.585 | 0.03271 | 0.8957 |
+#> |.....................| 0.7463 | 1.612 | 1.267 | 1.357 |
+#> | X| 475.97179 | 93.06 | 0.002557 | 0.2747 | 0.8690 |
+#> |.....................| 9.637 | 1.585 | 0.03271 | 0.8957 |
+#> |.....................| 0.7463 | 1.612 | 1.267 | 1.357 |
+#> | F| Forward Diff. | 1.543 | -0.1187 | -0.09427 | 0.04746 |
+#> |.....................| 0.7019 | 0.1743 | 0.004057 | -0.1664 |
+#> |.....................| 1.824 | 1.487 | 0.8060 | -0.1087 |
+#> | 70| 475.93640 | 0.9984 | -1.664 | -0.9398 | -0.9470 |
+#> |.....................| -0.8662 | -0.1315 | -0.7271 | -0.6595 |
+#> |.....................| -1.030 | -0.5499 | -0.6986 | -0.5913 |
+#> | U| 475.9364 | 92.96 | -5.967 | -0.9710 | -0.1592 |
+#> |.....................| 2.270 | 1.587 | 0.03253 | 0.9225 |
+#> |.....................| 0.7382 | 1.599 | 1.253 | 1.371 |
+#> | X| 475.9364 | 92.96 | 0.002561 | 0.2747 | 0.8529 |
+#> |.....................| 9.682 | 1.587 | 0.03253 | 0.9225 |
+#> |.....................| 0.7382 | 1.599 | 1.253 | 1.371 |
+#> | F| Forward Diff. | -18.02 | -0.07507 | -0.1675 | -0.4306 |
+#> |.....................| 0.8222 | -0.4249 | -0.3576 | -0.06909 |
+#> |.....................| -0.1553 | 0.7789 | -0.06902 | 0.4423 |
+#> | 71| 475.93449 | 0.9995 | -1.655 | -0.9484 | -0.9330 |
+#> |.....................| -0.8784 | -0.1258 | -0.7357 | -0.6330 |
+#> |.....................| -1.033 | -0.5716 | -0.6758 | -0.5988 |
+#> | U| 475.93449 | 93.07 | -5.959 | -0.9791 | -0.1451 |
+#> |.....................| 2.258 | 1.590 | 0.03240 | 0.9426 |
+#> |.....................| 0.7351 | 1.573 | 1.277 | 1.363 |
+#> | X| 475.93449 | 93.07 | 0.002583 | 0.2731 | 0.8649 |
+#> |.....................| 9.566 | 1.590 | 0.03240 | 0.9426 |
+#> |.....................| 0.7351 | 1.573 | 1.277 | 1.363 |
+#> | F| Forward Diff. | -1.432 | -0.03245 | -0.4539 | -0.04331 |
+#> |.....................| 0.5695 | -0.03993 | -0.2223 | 0.1396 |
+#> |.....................| -0.3709 | -0.08203 | 1.409 | 0.03273 |
+#> | 72| 475.92305 | 1.001 | -1.648 | -0.9418 | -0.9189 |
+#> |.....................| -0.8867 | -0.1240 | -0.7358 | -0.6284 |
+#> |.....................| -1.035 | -0.5652 | -0.6857 | -0.6066 |
+#> | U| 475.92305 | 93.18 | -5.952 | -0.9729 | -0.1311 |
+#> |.....................| 2.250 | 1.591 | 0.03240 | 0.9461 |
+#> |.....................| 0.7335 | 1.580 | 1.266 | 1.355 |
+#> | X| 475.92305 | 93.18 | 0.002602 | 0.2743 | 0.8772 |
+#> |.....................| 9.486 | 1.591 | 0.03240 | 0.9461 |
+#> |.....................| 0.7335 | 1.580 | 1.266 | 1.355 |
+#> | F| Forward Diff. | 18.31 | 0.001701 | 0.03033 | 0.3531 |
+#> |.....................| 0.4204 | 0.05655 | -0.08057 | 0.1734 |
+#> |.....................| -0.4632 | 0.1099 | 0.8178 | -0.3689 |
+#> | 73| 475.91938 | 0.9986 | -1.638 | -0.9366 | -0.9070 |
+#> |.....................| -0.8945 | -0.1236 | -0.7244 | -0.6267 |
+#> |.....................| -1.037 | -0.5623 | -0.6914 | -0.6147 |
+#> | U| 475.91938 | 92.99 | -5.941 | -0.9680 | -0.1192 |
+#> |.....................| 2.242 | 1.592 | 0.03257 | 0.9474 |
+#> |.....................| 0.7320 | 1.584 | 1.260 | 1.346 |
+#> | X| 475.91938 | 92.99 | 0.002629 | 0.2753 | 0.8877 |
+#> |.....................| 9.412 | 1.592 | 0.03257 | 0.9474 |
+#> |.....................| 0.7320 | 1.584 | 1.260 | 1.346 |
+#> | F| Forward Diff. | -15.99 | 0.01876 | 0.07238 | 0.5908 |
+#> |.....................| -0.09055 | 0.2914 | -0.2119 | 0.1409 |
+#> |.....................| 0.4365 | 0.1061 | 0.4376 | -0.5157 |
+#> | 74| 475.91938 | 0.9986 | -1.638 | -0.9366 | -0.9070 |
+#> |.....................| -0.8945 | -0.1236 | -0.7244 | -0.6267 |
+#> |.....................| -1.037 | -0.5623 | -0.6914 | -0.6147 |
+#> | U| 475.91938 | 92.99 | -5.941 | -0.9680 | -0.1192 |
+#> |.....................| 2.242 | 1.592 | 0.03257 | 0.9474 |
+#> |.....................| 0.7320 | 1.584 | 1.260 | 1.346 |
+#> | X| 475.91938 | 92.99 | 0.002629 | 0.2753 | 0.8877 |
+#> |.....................| 9.412 | 1.592 | 0.03257 | 0.9474 |
+#> |.....................| 0.7320 | 1.584 | 1.260 | 1.346 |
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_k1 |
+#> |.....................| log_k2 | g_qlogis | sigma_low | rsd_high |
+#> |.....................| o1 | o2 | o3 | o4 |
+#> |.....................| o5 | o6 |...........|...........|
+#> | 1| 495.80376 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 495.80376 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 495.80376 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | G| Gill Diff. | 40.10 | 2.344 | -0.09792 | 0.01304 |
+#> |.....................| -0.4854 | 0.6353 | -29.93 | -20.00 |
+#> |.....................| 1.261 | 9.993 | -12.68 | -0.7774 |
+#> |.....................| 8.106 | -12.55 |...........|...........|
+#> | 2| 2936.2793 | 0.3119 | -1.040 | -0.9093 | -0.9382 |
+#> |.....................| -0.9801 | -0.8941 | -0.3619 | -0.5483 |
+#> |.....................| -0.8992 | -1.046 | -0.6506 | -0.8594 |
+#> |.....................| -1.014 | -0.6521 |...........|...........|
+#> | U| 2936.2793 | 28.54 | -5.229 | -0.8860 | -2.190 |
+#> |.....................| -4.622 | 0.4539 | 1.041 | 0.06759 |
+#> |.....................| 0.7138 | 0.7431 | 1.443 | 0.9756 |
+#> |.....................| 0.7388 | 1.478 |...........|...........|
+#> | X| 2936.2793 | 28.54 | 0.005360 | 0.2919 | 0.1119 |
+#> |.....................| 0.009832 | 0.6116 | 1.041 | 0.06759 |
+#> |.....................| 0.7138 | 0.7431 | 1.443 | 0.9756 |
+#> |.....................| 0.7388 | 1.478 |...........|...........|
+#> | 3| 515.54714 | 0.9312 | -1.004 | -0.9108 | -0.9380 |
+#> |.....................| -0.9876 | -0.8843 | -0.8242 | -0.8571 |
+#> |.....................| -0.8797 | -0.8912 | -0.8464 | -0.8714 |
+#> |.....................| -0.8888 | -0.8460 |...........|...........|
+#> | U| 515.54714 | 85.19 | -5.193 | -0.8873 | -2.190 |
+#> |.....................| -4.630 | 0.4584 | 0.8493 | 0.05868 |
+#> |.....................| 0.7280 | 0.8815 | 1.211 | 0.9641 |
+#> |.....................| 0.8462 | 1.242 |...........|...........|
+#> | X| 515.54714 | 85.19 | 0.005557 | 0.2917 | 0.1119 |
+#> |.....................| 0.009758 | 0.6126 | 0.8493 | 0.05868 |
+#> |.....................| 0.7280 | 0.8815 | 1.211 | 0.9641 |
+#> |.....................| 0.8462 | 1.242 |...........|...........|
+#> | 4| 501.46574 | 0.9922 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9884 | -0.8833 | -0.8697 | -0.8876 |
+#> |.....................| -0.8778 | -0.8761 | -0.8657 | -0.8726 |
+#> |.....................| -0.8765 | -0.8650 |...........|...........|
+#> | U| 501.46574 | 90.77 | -5.189 | -0.8874 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8304 | 0.05781 |
+#> |.....................| 0.7294 | 0.8952 | 1.188 | 0.9629 |
+#> |.....................| 0.8568 | 1.219 |...........|...........|
+#> | X| 501.46574 | 90.77 | 0.005577 | 0.2916 | 0.1119 |
+#> |.....................| 0.009751 | 0.6127 | 0.8304 | 0.05781 |
+#> |.....................| 0.7294 | 0.8952 | 1.188 | 0.9629 |
+#> |.....................| 0.8568 | 1.219 |...........|...........|
+#> | 5| 501.84206 | 0.9992 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9884 | -0.8832 | -0.8749 | -0.8911 |
+#> |.....................| -0.8776 | -0.8743 | -0.8679 | -0.8727 |
+#> |.....................| -0.8751 | -0.8673 |...........|...........|
+#> | U| 501.84206 | 91.41 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8283 | 0.05771 |
+#> |.....................| 0.7296 | 0.8967 | 1.185 | 0.9628 |
+#> |.....................| 0.8580 | 1.216 |...........|...........|
+#> | X| 501.84206 | 91.41 | 0.005579 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8283 | 0.05771 |
+#> |.....................| 0.7296 | 0.8967 | 1.185 | 0.9628 |
+#> |.....................| 0.8580 | 1.216 |...........|...........|
+#> | 6| 501.90183 | 0.9999 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8914 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90183 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05770 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90183 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05770 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 7| 501.90808 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90808 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90808 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 8| 501.90873 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90873 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90873 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 9| 501.90880 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.9088 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.9088 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 10| 501.90881 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90881 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90881 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 11| 501.90882 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90882 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90882 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 12| 501.90882 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90882 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90882 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 13| 501.90882 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90882 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90882 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 14| 501.90882 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90882 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90882 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 15| 501.90882 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90882 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90882 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 16| 501.90883 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90883 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90883 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | 17| 501.90883 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8776 | -0.8741 | -0.8681 | -0.8727 |
+#> |.....................| -0.8749 | -0.8675 |...........|...........|
+#> | U| 501.90883 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> | X| 501.90883 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.7296 | 0.8969 | 1.185 | 0.9628 |
+#> |.....................| 0.8582 | 1.216 |...........|...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.775 0.024 0.799
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 92.2740 -5.2361 0.2113 1.9393 -2.0029 2.8805 1.6298 0.7279 0.7192 0.4382 6.7264 0.4769 7.2363 0.6178
+#> 2: 93.1532 -5.3060 0.0602 2.0735 -2.0177 2.7365 1.5483 0.6915 0.8577 0.4163 7.5229 0.0003 8.5494 0.0006
+#> 3: 9.3232e+01 -5.5491e+00 5.1555e-02 2.4627e+00 -1.4981e+00 2.5997e+00 1.4709e+00 6.5697e-01 8.1480e-01 3.9549e-01 4.6581e+00 4.3492e-05 5.3112e+00 1.7818e-04
+#> 4: 9.3109e+01 -5.6749e+00 3.7928e-02 2.4274e+00 -1.3355e+00 2.4697e+00 1.3973e+00 6.2412e-01 7.7406e-01 3.7572e-01 3.5252e+00 9.5643e-05 4.0990e+00 4.6584e-05
+#> 5: 9.3327e+01 -5.8341e+00 -1.6798e-02 2.4024e+00 -1.2129e+00 2.3462e+00 1.3274e+00 5.9292e-01 7.3536e-01 3.5693e-01 3.3259e+00 1.6901e-05 3.5218e+00 4.0075e-05
+#> 6: 9.3449e+01 -6.0745e+00 -6.1031e-02 2.3458e+00 -1.2034e+00 2.2289e+00 1.8700e+00 5.6327e-01 6.9859e-01 3.3908e-01 2.9533e+00 6.5587e-07 3.1056e+00 2.1346e-02
+#> 7: 93.2519 -6.0564 -0.0590 2.3588 -1.1293 2.1174 1.8910 0.5351 0.6637 0.3221 2.8211 0.0082 2.8507 0.0251
+#> 8: 93.0343 -5.9362 -0.0851 2.2949 -1.0760 2.0116 1.7964 0.5084 0.6305 0.3060 2.5340 0.0181 2.6368 0.0243
+#> 9: 93.1444 -6.1910 -0.1199 2.2709 -1.1077 1.9110 1.8664 0.4829 0.5990 0.2907 2.3768 0.0191 2.3601 0.0284
+#> 10: 93.2748 -6.4970 -0.1598 2.2235 -1.1034 2.1024 3.1968 0.4588 0.5690 0.2762 2.1991 0.0255 2.2790 0.0316
+#> 11: 93.4141 -6.4463 -0.1698 2.1876 -1.0890 1.9973 3.0370 0.4358 0.5406 0.2624 2.1469 0.0266 2.1681 0.0325
+#> 12: 93.4935 -6.5467 -0.1715 2.1666 -1.0952 1.8974 3.7848 0.4141 0.5135 0.2493 1.9137 0.0292 2.0701 0.0331
+#> 13: 93.6730 -6.4173 -0.1752 2.1387 -1.0753 1.8026 3.7278 0.3934 0.4879 0.2368 1.9084 0.0272 2.0289 0.0369
+#> 14: 93.5721 -6.2146 -0.1738 2.1854 -1.0740 2.0902 3.5415 0.3737 0.4635 0.2250 1.9861 0.0239 2.0052 0.0347
+#> 15: 93.6638 -6.3103 -0.1693 2.1828 -1.0327 2.0702 3.3644 0.3720 0.4403 0.2137 1.8947 0.0247 1.9865 0.0375
+#> 16: 93.4156 -6.0957 -0.1666 2.1755 -1.0737 2.6391 3.1962 0.3691 0.4183 0.2030 1.9089 0.0241 2.0159 0.0360
+#> 17: 93.4257 -6.1494 -0.1705 2.1664 -1.0589 2.5072 3.0714 0.3697 0.3974 0.1929 1.8253 0.0268 2.0391 0.0301
+#> 18: 93.5593 -6.1696 -0.1780 2.1670 -1.0129 2.3818 3.7604 0.3725 0.3775 0.1832 1.8529 0.0304 1.8784 0.0298
+#> 19: 93.5027 -6.2960 -0.1791 2.1543 -1.0325 2.6052 4.5501 0.3942 0.3586 0.1741 1.8082 0.0328 1.8654 0.0335
+#> 20: 93.4480 -6.4389 -0.1776 2.1772 -1.0485 2.6607 5.1881 0.3894 0.3554 0.1654 1.8032 0.0322 1.9018 0.0312
+#> 21: 93.6411 -6.2893 -0.1750 2.1759 -1.0350 2.5276 4.9287 0.3817 0.3386 0.1605 1.8533 0.0264 1.9317 0.0301
+#> 22: 93.9320 -6.1469 -0.1750 2.1910 -1.0527 2.4013 4.6823 0.3720 0.3642 0.1525 1.8949 0.0273 1.8977 0.0310
+#> 23: 93.6074 -6.3097 -0.1502 2.2111 -1.0155 2.2812 4.6643 0.3832 0.4236 0.1449 1.7075 0.0340 1.7367 0.0337
+#> 24: 93.7425 -6.4598 -0.1446 2.2249 -1.0011 2.7056 6.0597 0.3949 0.4075 0.1479 1.7180 0.0360 1.7786 0.0302
+#> 25: 94.1822 -6.3674 -0.1496 2.1917 -1.0011 3.4724 5.7567 0.3897 0.4355 0.1465 1.6977 0.0356 1.8373 0.0328
+#> 26: 94.0446 -6.3235 -0.1496 2.2004 -1.0414 3.5912 5.4688 0.3897 0.4438 0.1405 1.6765 0.0344 1.8262 0.0355
+#> 27: 94.4454 -6.2148 -0.1370 2.2360 -1.0220 4.6238 5.1954 0.3702 0.4216 0.1335 1.7209 0.0349 1.7702 0.0336
+#> 28: 94.1837 -6.1301 -0.1376 2.2253 -1.0261 4.3926 4.9356 0.3644 0.4005 0.1345 1.6968 0.0290 1.8540 0.0316
+#> 29: 94.0681 -5.8726 -0.1440 2.2237 -1.0400 4.1730 4.6889 0.3750 0.4055 0.1464 1.7084 0.0329 1.7379 0.0407
+#> 30: 94.5866 -5.9141 -0.1416 2.2045 -1.0350 3.9896 4.4544 0.3770 0.3852 0.1769 1.6009 0.0326 1.8718 0.0350
+#> 31: 94.1640 -6.0370 -0.1382 2.2140 -1.0189 5.4942 4.2317 0.3759 0.3809 0.1680 1.5887 0.0386 1.8918 0.0286
+#> 32: 94.5952 -5.8349 -0.1373 2.2374 -1.0283 5.2195 4.0201 0.3745 0.3835 0.1636 1.6451 0.0375 1.7459 0.0382
+#> 33: 95.0936 -5.8145 -0.1356 2.2325 -1.0037 4.9634 3.8191 0.3614 0.3644 0.1677 1.6313 0.0414 1.6809 0.0399
+#> 34: 94.7033 -5.8916 -0.1208 2.2687 -0.9896 5.4935 3.6281 0.3741 0.3536 0.1701 1.5923 0.0376 1.2962 0.0644
+#> 35: 94.8127 -5.9839 -0.1122 2.2615 -0.9983 5.2188 3.7348 0.3817 0.3661 0.1712 1.5848 0.0313 1.1651 0.0752
+#> 36: 94.6798 -5.8938 -0.1203 2.2441 -1.0009 4.9578 3.5480 0.3835 0.3478 0.1708 1.5525 0.0313 1.1527 0.0712
+#> 37: 93.9759 -5.8017 -0.1274 2.2346 -1.0021 4.7100 3.3706 0.3868 0.3350 0.1622 1.6278 0.0256 1.7263 0.0372
+#> 38: 94.2013 -5.8617 -0.1206 2.2570 -1.0125 4.4745 3.2021 0.3754 0.3520 0.1574 1.5396 0.0290 1.0653 0.0746
+#> 39: 94.1314 -5.7645 -0.1261 2.2381 -1.0361 4.2507 3.0420 0.3804 0.3521 0.1543 1.6280 0.0267 1.1461 0.0755
+#> 40: 93.7934 -5.8654 -0.1206 2.2417 -1.0503 4.0382 2.8899 0.3624 0.3413 0.1747 1.6231 0.0239 1.5698 0.0513
+#> 41: 93.8756 -6.0150 -0.1171 2.2581 -1.0313 3.8363 3.3629 0.3809 0.3369 0.1944 1.6461 0.0217 1.7762 0.0345
+#> 42: 94.0644 -5.9723 -0.1136 2.2769 -1.0295 3.6445 3.2171 0.3702 0.3394 0.1920 1.5035 0.0416 1.5148 0.0475
+#> 43: 93.7394 -5.9927 -0.1233 2.2650 -1.0374 3.4622 3.0562 0.3735 0.3370 0.1824 1.6022 0.0379 1.5080 0.0468
+#> 44: 93.5428 -5.9784 -0.1187 2.2780 -1.0279 3.2891 2.9495 0.3732 0.3289 0.1742 1.5456 0.0471 1.4361 0.0517
+#> 45: 93.2885 -5.9836 -0.1273 2.2650 -1.0100 3.1247 3.2884 0.3768 0.3719 0.1655 1.6579 0.0336 1.4031 0.0585
+#> 46: 93.4080 -5.9261 -0.1371 2.2513 -1.0159 3.4180 3.1630 0.3709 0.3762 0.1711 1.7365 0.0269 1.4612 0.0530
+#> 47: 93.4548 -5.8101 -0.1372 2.2650 -1.0058 3.2471 3.0049 0.3703 0.3921 0.1797 1.7161 0.0300 1.4813 0.0524
+#> 48: 93.1829 -5.6877 -0.1391 2.2594 -1.0035 3.0848 2.8546 0.3690 0.3901 0.1707 1.7558 0.0292 1.5856 0.0487
+#> 49: 93.1860 -5.8153 -0.1349 2.2793 -0.9905 2.9305 2.7119 0.3619 0.3877 0.1690 1.7255 0.0299 1.6143 0.0465
+#> 50: 93.5597 -5.7551 -0.1334 2.2669 -0.9808 2.7840 2.5763 0.3652 0.3795 0.1716 1.6690 0.0290 1.4895 0.0536
+#> 51: 93.5952 -5.8089 -0.1358 2.2626 -1.0100 2.6448 2.4475 0.3640 0.4246 0.1630 1.5892 0.0344 1.3958 0.0604
+#> 52: 93.3111 -5.9181 -0.1323 2.2489 -0.9909 2.5126 2.8739 0.3695 0.4337 0.1549 1.5200 0.0329 1.2246 0.0685
+#> 53: 93.4921 -6.0837 -0.1307 2.2513 -1.0031 2.3869 3.6029 0.3678 0.4363 0.1682 1.4683 0.0336 1.2917 0.0665
+#> 54: 93.4808 -6.2019 -0.1488 2.2068 -1.0207 2.2676 4.1833 0.3952 0.4145 0.1598 1.6478 0.0325 1.2418 0.0659
+#> 55: 93.5453 -6.2747 -0.1411 2.2297 -1.0122 2.1542 4.5107 0.3941 0.4044 0.1556 1.5685 0.0358 1.3236 0.0654
+#> 56: 94.0212 -6.2713 -0.1355 2.2228 -1.0205 2.0465 5.1718 0.3901 0.4101 0.1516 1.5568 0.0341 1.1952 0.0736
+#> 57: 93.7155 -6.2511 -0.1574 2.1899 -1.0374 1.9442 4.9132 0.3991 0.3974 0.1442 1.5528 0.0364 1.5497 0.0485
+#> 58: 93.9064 -6.2021 -0.1543 2.1935 -1.0277 1.8470 4.6676 0.3935 0.3944 0.1458 1.5590 0.0354 1.3512 0.0613
+#> 59: 93.9059 -6.3971 -0.1550 2.1899 -1.0124 1.7546 5.8885 0.3925 0.3943 0.1446 1.5641 0.0373 1.4293 0.0550
+#> 60: 93.8600 -6.2474 -0.1552 2.1978 -0.9930 1.7661 5.5941 0.3905 0.4078 0.1532 1.5235 0.0364 1.5442 0.0477
+#> 61: 93.8936 -6.3077 -0.1568 2.2022 -1.0084 1.7122 5.3507 0.3946 0.4146 0.1455 1.5154 0.0342 1.3664 0.0587
+#> 62: 93.6133 -6.1446 -0.1473 2.2277 -1.0195 1.6266 5.0832 0.3794 0.4254 0.1383 1.5586 0.0330 1.1663 0.0705
+#> 63: 93.5549 -6.3005 -0.1437 2.2302 -1.0096 1.5452 5.0969 0.3651 0.4262 0.1349 1.5730 0.0323 1.2501 0.0668
+#> 64: 93.3212 -6.1190 -0.1428 2.2309 -1.0005 1.4826 4.8421 0.3661 0.4181 0.1443 1.6657 0.0259 1.3409 0.0627
+#> 65: 93.2534 -5.9614 -0.1492 2.2310 -0.9865 1.4084 4.6000 0.3735 0.4186 0.1695 1.6883 0.0235 1.4446 0.0563
+#> 66: 93.3429 -5.9786 -0.1401 2.2198 -0.9934 1.3380 4.3700 0.3807 0.4094 0.1610 1.6697 0.0270 1.1164 0.0778
+#> 67: 93.5657 -6.2158 -0.1405 2.2326 -0.9891 1.2711 4.4653 0.3827 0.4063 0.1530 1.5851 0.0316 1.3581 0.0590
+#> 68: 93.4898 -5.9763 -0.1375 2.2431 -0.9837 1.2076 4.2420 0.3771 0.4127 0.1453 1.6134 0.0325 1.1459 0.0744
+#> 69: 93.4995 -6.1375 -0.1412 2.2423 -1.0003 1.3178 4.3907 0.3746 0.4202 0.1403 1.6223 0.0304 1.3354 0.0608
+#> 70: 93.4369 -6.1690 -0.1395 2.2472 -1.0047 1.6239 4.5654 0.3793 0.4087 0.1400 1.6317 0.0349 1.4812 0.0494
+#> 71: 93.4041 -6.3637 -0.1489 2.2348 -1.0125 1.5427 5.3897 0.3603 0.3883 0.1330 1.5954 0.0303 1.3502 0.0612
+#> 72: 93.1755 -6.4067 -0.1441 2.2492 -0.9859 1.4656 6.3554 0.3423 0.3688 0.1388 1.6135 0.0287 1.6402 0.0435
+#> 73: 93.0023 -6.7319 -0.1526 2.2550 -0.9800 1.3923 7.6438 0.3341 0.3504 0.1462 1.5491 0.0312 1.3997 0.0554
+#> 74: 92.8952 -6.7189 -0.1530 2.2393 -0.9936 1.5478 7.2616 0.3344 0.3329 0.1503 1.5626 0.0326 1.3340 0.0634
+#> 75: 93.0812 -6.8015 -0.1546 2.2265 -0.9751 1.4704 8.9537 0.3501 0.3162 0.1438 1.6019 0.0268 1.1663 0.0715
+#> 76: 93.1080 -6.1728 -0.1515 2.2259 -1.0010 1.3969 8.5060 0.3407 0.3015 0.1398 1.6484 0.0279 1.3118 0.0637
+#> 77: 92.9248 -6.3432 -0.1573 2.2221 -0.9819 1.4456 8.0807 0.3506 0.3002 0.1442 1.5947 0.0294 1.6368 0.0407
+#> 78: 93.0194 -6.1448 -0.1611 2.2228 -0.9831 1.3733 7.6767 0.3487 0.3046 0.1369 1.6471 0.0254 1.4261 0.0529
+#> 79: 92.9378 -6.6970 -0.1593 2.2313 -0.9910 1.3046 10.0158 0.3460 0.2999 0.1386 1.6108 0.0267 1.5818 0.0420
+#> 80: 93.0293 -6.3275 -0.1579 2.2290 -0.9753 1.3191 9.5150 0.3543 0.2960 0.1490 1.6570 0.0259 1.5435 0.0431
+#> 81: 93.1417 -6.2258 -0.1607 2.2285 -0.9399 1.4131 9.0393 0.3514 0.3020 0.1415 1.6990 0.0236 1.6875 0.0364
+#> 82: 92.9115 -6.1764 -0.1555 2.2204 -0.9471 1.3424 8.5873 0.3502 0.2954 0.1540 1.6780 0.0216 1.2280 0.0687
+#> 83: 93.0528 -6.3505 -0.1559 2.2391 -0.9651 1.2753 8.1579 0.3499 0.2903 0.1706 1.6924 0.0242 1.6807 0.0465
+#> 84: 93.0032 -6.2300 -0.1596 2.2300 -0.9232 1.2115 7.9391 0.3470 0.2995 0.1858 1.7153 0.0259 1.7160 0.0406
+#> 85: 93.0518 -6.3704 -0.1434 2.2696 -0.9330 1.1510 8.3071 0.3504 0.2916 0.1765 1.7072 0.0275 1.5494 0.0490
+#> 86: 93.1344 -6.3566 -0.1424 2.2595 -0.9512 1.0934 9.2972 0.3520 0.2869 0.1677 1.6609 0.0253 1.5022 0.0508
+#> 87: 93.2468 -6.3860 -0.1449 2.2505 -0.9601 1.0387 8.8323 0.3474 0.3046 0.1593 1.6326 0.0262 1.3048 0.0626
+#> 88: 93.2286 -6.3886 -0.1466 2.2452 -0.9870 0.9868 8.3907 0.3474 0.2894 0.1513 1.6554 0.0245 1.6330 0.0376
+#> 89: 93.2892 -6.0277 -0.1469 2.2403 -0.9694 0.9375 7.9712 0.3451 0.2904 0.1438 1.6795 0.0251 1.6691 0.0365
+#> 90: 93.1766 -6.1076 -0.1460 2.2502 -0.9729 0.8906 7.5726 0.3458 0.2932 0.1481 1.6182 0.0331 1.5854 0.0401
+#> 91: 93.3300 -6.0932 -0.1559 2.2356 -0.9551 0.8461 7.1940 0.3771 0.2883 0.1512 1.6728 0.0272 1.6098 0.0401
+#> 92: 93.2470 -6.4839 -0.1592 2.2265 -1.0016 0.8038 6.8343 0.3813 0.2923 0.1597 1.7017 0.0300 1.6084 0.0423
+#> 93: 93.2272 -6.2819 -0.1612 2.2356 -1.0073 0.7636 6.4926 0.3849 0.2816 0.1722 1.5422 0.0420 1.4772 0.0493
+#> 94: 93.1441 -6.1805 -0.1571 2.2274 -1.0106 0.7254 6.1680 0.3878 0.2811 0.1636 1.5998 0.0403 1.4386 0.0535
+#> 95: 92.7747 -6.2274 -0.1709 2.2191 -1.0042 0.6891 5.8596 0.3909 0.2905 0.1591 1.7184 0.0282 1.6086 0.0519
+#> 96: 92.9830 -6.3291 -0.1603 2.2297 -1.0053 0.6547 5.5666 0.3774 0.2850 0.1512 1.7427 0.0284 1.7548 0.0384
+#> 97: 92.9302 -6.3943 -0.1608 2.2211 -0.9643 0.6219 5.2882 0.3817 0.2828 0.1589 1.7080 0.0295 1.7102 0.0398
+#> 98: 92.7704 -6.3554 -0.1679 2.1894 -0.9736 0.5908 5.4196 0.3864 0.2813 0.1560 1.7234 0.0240 1.2269 0.0685
+#> 99: 92.7596 -6.2138 -0.1687 2.2088 -0.9744 0.5613 5.1486 0.3939 0.2983 0.1482 1.6732 0.0250 1.5718 0.0497
+#> 100: 92.6608 -6.2662 -0.1687 2.2180 -1.0107 0.5332 5.1471 0.3939 0.2927 0.1408 1.8434 0.0232 1.7316 0.0413
+#> 101: 92.7024 -6.1288 -0.1643 2.2096 -1.0032 0.5066 4.8898 0.3934 0.2807 0.1349 1.7055 0.0253 1.5883 0.0439
+#> 102: 92.8885 -6.3175 -0.1697 2.2208 -0.9967 0.4812 4.9699 0.3888 0.2912 0.1371 1.7311 0.0284 1.6455 0.0402
+#> 103: 92.9487 -6.2493 -0.1677 2.1861 -0.9874 0.4572 4.9605 0.3907 0.2844 0.1626 1.6898 0.0279 1.6252 0.0409
+#> 104: 92.9633 -6.2534 -0.1731 2.1797 -0.9790 0.4343 4.8675 0.4015 0.2784 0.1758 1.6516 0.0268 1.6901 0.0360
+#> 105: 93.0513 -6.0656 -0.1748 2.1802 -0.9876 0.4126 4.6241 0.4041 0.2801 0.1670 1.6863 0.0269 1.6208 0.0366
+#> 106: 93.0600 -6.2162 -0.1860 2.1783 -0.9702 0.4570 4.5504 0.4451 0.2761 0.1586 1.6859 0.0274 1.5273 0.0437
+#> 107: 93.1856 -6.1826 -0.1801 2.1796 -0.9813 0.4341 4.7286 0.4517 0.2807 0.1575 1.6268 0.0341 1.2548 0.0630
+#> 108: 93.2401 -6.2943 -0.1783 2.1808 -0.9806 0.4124 5.3114 0.4502 0.2786 0.1496 1.6676 0.0291 1.4627 0.0484
+#> 109: 93.0988 -6.1669 -0.1655 2.2018 -0.9682 0.4036 5.0458 0.4302 0.3195 0.1435 1.6524 0.0295 1.5759 0.0447
+#> 110: 93.2129 -6.3104 -0.1748 2.1876 -0.9837 0.4825 5.6408 0.4430 0.3306 0.1595 1.6068 0.0326 1.6295 0.0388
+#> 111: 93.1292 -5.9096 -0.1740 2.1932 -0.9674 0.5262 5.3587 0.4444 0.3233 0.1646 1.5777 0.0334 1.6590 0.0374
+#> 112: 93.2723 -5.8153 -0.1706 2.1920 -0.9761 0.5109 5.0908 0.4486 0.3180 0.1634 1.6128 0.0321 1.6551 0.0396
+#> 113: 93.3171 -6.0458 -0.1666 2.1879 -0.9740 0.5530 4.8362 0.4508 0.3303 0.1607 1.5862 0.0325 1.2705 0.0643
+#> 114: 93.1717 -5.9615 -0.1655 2.1638 -0.9773 0.5254 4.5944 0.4472 0.3283 0.1657 1.6307 0.0287 1.2995 0.0677
+#> 115: 93.1917 -6.0856 -0.1592 2.1576 -1.0269 0.4991 4.3647 0.4349 0.3464 0.1574 1.6430 0.0354 1.2812 0.0714
+#> 116: 93.1287 -5.9635 -0.1609 2.1640 -0.9985 0.4741 4.1465 0.4237 0.3408 0.1495 1.6910 0.0269 1.2338 0.0738
+#> 117: 93.1184 -5.8768 -0.1603 2.1842 -0.9557 0.4504 3.9392 0.4211 0.3293 0.1420 1.6447 0.0257 1.2680 0.0705
+#> 118: 93.2207 -5.7436 -0.1654 2.1709 -0.9816 0.4279 3.7422 0.4158 0.3298 0.1349 1.6860 0.0238 1.1436 0.0780
+#> 119: 93.3064 -5.8397 -0.1713 2.1722 -1.0093 0.4065 3.5551 0.4100 0.3429 0.1384 1.6612 0.0262 1.6491 0.0458
+#> 120: 93.2749 -5.8221 -0.1737 2.1643 -1.0166 0.3862 3.3773 0.4044 0.3305 0.1527 1.6516 0.0232 1.7832 0.0410
+#> 121: 93.1620 -5.9756 -0.1579 2.2018 -1.0007 0.3818 3.2992 0.3841 0.3433 0.1620 1.6648 0.0251 1.3408 0.0665
+#> 122: 93.2070 -6.0164 -0.1540 2.2154 -1.0196 0.4217 3.5598 0.3649 0.3436 0.1539 1.6757 0.0287 1.3019 0.0652
+#> 123: 93.1588 -5.7424 -0.1581 2.2142 -0.9985 0.5270 3.3818 0.3491 0.3584 0.1655 1.6321 0.0237 1.3494 0.0644
+#> 124: 93.1496 -5.6257 -0.1463 2.2264 -0.9767 0.5914 3.2127 0.3347 0.3738 0.1573 1.6553 0.0226 1.5964 0.0544
+#> 125: 93.0224 -5.8536 -0.1742 2.1859 -0.9939 0.6381 3.0521 0.3840 0.3692 0.1664 1.6009 0.0246 1.4169 0.0652
+#> 126: 93.0788 -5.6973 -0.1778 2.1772 -0.9574 0.6062 2.8995 0.3710 0.3630 0.1839 1.5256 0.0312 1.5566 0.0518
+#> 127: 93.1613 -5.5833 -0.1729 2.1806 -0.9588 0.5759 2.7545 0.3532 0.3464 0.1878 1.5708 0.0307 1.6405 0.0476
+#> 128: 93.2043 -5.6742 -0.1746 2.1919 -0.9814 0.7099 2.6168 0.3569 0.3422 0.1848 1.6236 0.0312 1.5066 0.0517
+#> 129: 93.1963 -5.7026 -0.1770 2.1853 -0.9814 0.6744 2.4859 0.3544 0.3390 0.1774 1.6150 0.0293 1.5712 0.0479
+#> 130: 93.1669 -5.7260 -0.1826 2.1565 -0.9959 0.6407 2.3616 0.3750 0.3249 0.1685 1.6347 0.0215 1.5556 0.0535
+#> 131: 93.0792 -5.7201 -0.1971 2.1339 -1.0057 0.7376 2.2436 0.3901 0.3086 0.1616 1.7653 0.0206 1.6640 0.0458
+#> 132: 92.8580 -5.8266 -0.1877 2.1512 -0.9940 0.7008 2.3272 0.3895 0.3161 0.1863 1.6050 0.0231 1.5123 0.0558
+#> 133: 92.8479 -5.8397 -0.1834 2.1637 -0.9815 0.7195 2.4732 0.3875 0.3060 0.1877 1.6197 0.0217 1.4131 0.0617
+#> 134: 92.9218 -5.8317 -0.1903 2.1709 -0.9903 0.6835 2.5070 0.3808 0.3147 0.1857 1.7298 0.0225 1.5493 0.0521
+#> 135: 92.7533 -5.7287 -0.1909 2.1670 -0.9674 0.6493 2.3817 0.3792 0.3156 0.1981 1.7074 0.0222 1.2776 0.0718
+#> 136: 92.7255 -5.9071 -0.1787 2.1826 -0.9826 0.6169 2.8147 0.3603 0.3172 0.1882 1.6242 0.0288 1.2313 0.0682
+#> 137: 92.7882 -5.9574 -0.1847 2.1549 -0.9848 0.5860 3.0538 0.3651 0.3206 0.1787 1.5640 0.0277 1.1609 0.0716
+#> 138: 92.8155 -5.9445 -0.1719 2.1750 -0.9838 0.5567 3.3525 0.3568 0.3390 0.1698 1.5507 0.0259 1.0634 0.0816
+#> 139: 92.9393 -6.0638 -0.1726 2.1840 -0.9888 0.5289 4.1627 0.3562 0.3453 0.1613 1.5792 0.0259 1.5189 0.0533
+#> 140: 93.0330 -6.1823 -0.1726 2.1984 -0.9850 0.5024 4.3153 0.3562 0.3506 0.1533 1.6467 0.0248 1.5734 0.0459
+#> 141: 93.0651 -6.1847 -0.1702 2.2183 -0.9749 0.4773 4.1656 0.3604 0.3626 0.1527 1.5887 0.0272 1.5613 0.0433
+#> 142: 93.0350 -5.9581 -0.1641 2.2133 -0.9707 0.4535 3.9574 0.3642 0.3541 0.1662 1.5904 0.0246 1.4665 0.0556
+#> 143: 92.9215 -5.7798 -0.1642 2.2269 -0.9665 0.5015 3.7595 0.3665 0.3626 0.1667 1.6019 0.0275 1.3379 0.0563
+#> 144: 93.0132 -5.6752 -0.1629 2.2273 -0.9468 0.4764 3.5715 0.3648 0.3555 0.1648 1.5218 0.0320 1.1736 0.0695
+#> 145: 92.9596 -5.8104 -0.1449 2.2498 -0.9730 0.4526 3.3929 0.3465 0.3524 0.1670 1.5918 0.0284 1.3067 0.0630
+#> 146: 92.7925 -5.7223 -0.1458 2.2463 -0.9569 0.5591 3.2233 0.3443 0.3492 0.1587 1.6175 0.0260 1.0691 0.0729
+#> 147: 92.8399 -5.8322 -0.1478 2.2485 -0.9474 0.5312 3.2015 0.3422 0.3536 0.1507 1.6257 0.0255 1.2184 0.0622
+#> 148: 92.8390 -5.9554 -0.1498 2.2490 -0.9550 0.5046 3.6305 0.3387 0.3597 0.1615 1.5994 0.0263 1.2274 0.0638
+#> 149: 92.8158 -5.9697 -0.1511 2.2337 -0.9812 0.4794 3.8244 0.3386 0.3894 0.1559 1.5723 0.0255 1.0661 0.0760
+#> 150: 92.8379 -6.0841 -0.1532 2.2323 -0.9832 0.4554 4.3416 0.3340 0.3840 0.1575 1.5375 0.0272 1.1589 0.0677
+#> 151: 92.6741 -6.3268 -0.1572 2.2252 -0.9782 0.4327 5.9395 0.3389 0.3859 0.1584 1.5384 0.0252 1.2809 0.0638
+#> 152: 92.7165 -6.3594 -0.1527 2.2233 -1.0007 0.4210 5.8433 0.3384 0.3915 0.1324 1.5861 0.0254 1.0728 0.0756
+#> 153: 92.6823 -6.2114 -0.1640 2.2160 -0.9861 0.5285 5.4117 0.3473 0.3878 0.1376 1.6150 0.0255 1.2105 0.0659
+#> 154: 92.4787 -6.1829 -0.1622 2.2055 -0.9571 0.5031 5.7087 0.3490 0.3748 0.1345 1.5749 0.0250 1.0579 0.0741
+#> 155: 92.4780 -6.4925 -0.1675 2.2190 -0.9301 0.4020 7.4764 0.3587 0.3785 0.1287 1.5959 0.0258 1.1342 0.0709
+#> 156: 92.5151 -6.2825 -0.1673 2.2194 -0.9174 0.3603 5.6463 0.3589 0.3848 0.1202 1.5413 0.0301 1.1866 0.0674
+#> 157: 92.5140 -6.0058 -0.1644 2.2312 -0.9298 0.3857 4.2481 0.3610 0.3706 0.1281 1.5944 0.0292 1.2712 0.0631
+#> 158: 92.5669 -5.8692 -0.1673 2.2493 -0.9413 0.4751 3.7632 0.3600 0.3572 0.1383 1.6202 0.0323 1.4797 0.0499
+#> 159: 92.4844 -6.0078 -0.1540 2.2464 -0.9423 0.4626 4.6774 0.3587 0.3603 0.1450 1.6404 0.0280 1.3577 0.0587
+#> 160: 92.5182 -6.1231 -0.1504 2.2518 -0.9274 0.4153 5.0466 0.3616 0.3633 0.1373 1.5891 0.0297 1.2392 0.0653
+#> 161: 92.5665 -5.9062 -0.1569 2.2563 -0.9412 0.3989 4.3594 0.3541 0.3719 0.1433 1.6242 0.0314 1.2822 0.0627
+#> 162: 92.5749 -6.0936 -0.1507 2.2752 -0.9474 0.3140 4.4065 0.3438 0.3921 0.1320 1.5013 0.0378 1.1647 0.0662
+#> 163: 92.6248 -6.1392 -0.1565 2.2499 -0.9499 0.2129 4.6022 0.3512 0.3890 0.1425 1.4936 0.0336 1.4339 0.0494
+#> 164: 92.6486 -6.3898 -0.1590 2.2519 -0.9574 0.1948 5.7817 0.3564 0.3925 0.1308 1.5218 0.0326 1.2197 0.0630
+#> 165: 92.6600 -6.3261 -0.1606 2.2464 -0.9815 0.3054 5.9162 0.3611 0.3979 0.1433 1.5747 0.0316 1.2062 0.0632
+#> 166: 92.7951 -6.3068 -0.1630 2.2428 -0.9542 0.3144 5.7041 0.3597 0.3766 0.1612 1.5464 0.0317 1.2649 0.0617
+#> 167: 92.8541 -6.4919 -0.1642 2.2275 -0.9505 0.3509 6.3858 0.3639 0.3713 0.1581 1.5543 0.0315 1.3546 0.0574
+#> 168: 92.6848 -6.3299 -0.1618 2.2329 -0.9494 0.4645 5.7127 0.3700 0.3698 0.1544 1.5058 0.0340 1.1747 0.0685
+#> 169: 92.5817 -6.0236 -0.1572 2.2583 -0.9510 0.6725 3.9864 0.3672 0.3812 0.1763 1.4445 0.0386 1.3230 0.0583
+#> 170: 92.7223 -5.9170 -0.1609 2.2456 -0.9485 0.5137 3.7991 0.3712 0.3714 0.1601 1.5502 0.0385 1.3393 0.0547
+#> 171: 92.6532 -5.9417 -0.1544 2.2294 -0.9448 0.6206 3.9052 0.3789 0.3634 0.1487 1.5809 0.0314 1.1226 0.0711
+#> 172: 92.4803 -5.7302 -0.1414 2.2679 -0.9255 0.7853 2.7901 0.3598 0.3666 0.1508 1.5531 0.0341 1.1785 0.0667
+#> 173: 92.3172 -5.7462 -0.1405 2.2823 -0.9193 1.2505 2.9155 0.3579 0.3678 0.1480 1.4894 0.0434 1.2288 0.0618
+#> 174: 92.4674 -5.6638 -0.1415 2.2775 -0.9054 1.0653 2.8138 0.3623 0.3740 0.1371 1.5301 0.0393 1.0790 0.0669
+#> 175: 92.5581 -5.6388 -0.1338 2.2878 -0.9154 0.6617 2.5216 0.3471 0.3719 0.1546 1.5231 0.0361 1.0672 0.0723
+#> 176: 92.7218 -5.7548 -0.1249 2.3099 -0.9203 0.4464 2.8226 0.3570 0.3978 0.1570 1.4938 0.0354 1.1125 0.0655
+#> 177: 92.7655 -5.6769 -0.1232 2.3114 -0.9257 0.5291 2.5249 0.3571 0.4023 0.1657 1.4392 0.0386 1.1149 0.0663
+#> 178: 92.7966 -5.6766 -0.1219 2.3202 -0.9142 0.4897 2.3359 0.3605 0.3944 0.1720 1.4792 0.0401 1.1665 0.0637
+#> 179: 92.8304 -5.7678 -0.1133 2.3352 -0.9262 0.5428 2.8512 0.3552 0.4191 0.1716 1.4994 0.0410 1.0651 0.0701
+#> 180: 92.8413 -5.7485 -0.1124 2.3452 -0.9494 0.5179 2.6552 0.3555 0.4025 0.1778 1.5102 0.0383 1.1541 0.0670
+#> 181: 92.7078 -5.7437 -0.1145 2.3257 -0.9482 0.6237 2.5673 0.3564 0.3851 0.1897 1.5373 0.0335 1.1413 0.0698
+#> 182: 92.6278 -5.7965 -0.1115 2.3341 -0.9763 0.7558 2.7421 0.3541 0.3850 0.1625 1.5720 0.0309 1.1164 0.0758
+#> 183: 92.4359 -5.7826 -0.1211 2.3204 -0.9481 1.2089 3.0954 0.3598 0.3813 0.1384 1.6391 0.0333 1.2142 0.0646
+#> 184: 92.4840 -5.9143 -0.1218 2.2965 -0.9330 1.2610 4.0248 0.3752 0.3549 0.1597 1.6019 0.0292 1.0945 0.0767
+#> 185: 92.5659 -5.8333 -0.1223 2.2914 -0.9090 1.0578 3.9752 0.3706 0.3640 0.1769 1.5858 0.0287 1.7070 0.0404
+#> 186: 92.5157 -5.9540 -0.1274 2.2967 -0.9678 1.0199 3.7413 0.3625 0.3766 0.1354 1.5905 0.0321 1.2521 0.0660
+#> 187: 92.6988 -5.8607 -0.1193 2.2922 -0.9685 1.1721 2.9764 0.3511 0.3823 0.1347 1.5790 0.0352 1.1477 0.0746
+#> 188: 92.7427 -5.9073 -0.1166 2.3166 -0.9529 1.3606 2.9747 0.3487 0.3981 0.1322 1.5315 0.0344 1.3014 0.0594
+#> 189: 92.6288 -5.8326 -0.1075 2.3268 -0.9543 1.3459 3.2341 0.3388 0.3983 0.1622 1.5374 0.0334 1.5390 0.0504
+#> 190: 92.8047 -5.6198 -0.1064 2.3212 -0.9148 1.6280 2.5774 0.3319 0.4086 0.1656 1.5159 0.0321 1.5423 0.0515
+#> 191: 92.7642 -5.5780 -0.1105 2.3041 -0.9414 1.5723 2.6038 0.3402 0.4111 0.1612 1.5254 0.0321 1.1206 0.0792
+#> 192: 92.7137 -5.5650 -0.1087 2.3014 -0.9399 1.1968 2.0552 0.3412 0.4267 0.1418 1.4910 0.0332 0.9683 0.0834
+#> 193: 93.0503 -5.6414 -0.1060 2.3050 -0.9563 1.0067 2.2362 0.3434 0.4179 0.1371 1.5947 0.0279 1.0349 0.0813
+#> 194: 93.1071 -5.6349 -0.1048 2.3170 -0.9613 1.1495 2.6224 0.3451 0.4086 0.1419 1.6235 0.0276 1.0558 0.0792
+#> 195: 93.0741 -5.7863 -0.1052 2.3293 -0.9605 1.1597 3.0814 0.3440 0.4342 0.1394 1.5248 0.0348 1.0554 0.0771
+#> 196: 93.0768 -5.6986 -0.0911 2.3395 -0.9537 1.1388 2.7165 0.3463 0.4303 0.1467 1.5960 0.0324 1.1195 0.0755
+#> 197: 92.8638 -5.7840 -0.1009 2.3420 -0.9699 1.0231 2.8293 0.3625 0.4272 0.1849 1.5366 0.0360 1.3691 0.0602
+#> 198: 92.8979 -5.8328 -0.0905 2.3497 -0.9668 0.8847 2.7469 0.3509 0.4357 0.1842 1.5501 0.0361 1.1744 0.0715
+#> 199: 92.7817 -6.0173 -0.0946 2.3477 -0.9729 0.8131 3.4886 0.3517 0.4471 0.1906 1.4350 0.0393 1.2311 0.0693
+#> 200: 92.6353 -6.0362 -0.0924 2.3396 -0.9621 0.8259 3.3916 0.3556 0.4569 0.1867 1.4397 0.0350 1.0910 0.0793
+#> 201: 92.6908 -6.0423 -0.0917 2.3400 -0.9564 0.6766 3.6159 0.3552 0.4565 0.1735 1.4506 0.0362 1.0646 0.0794
+#> 202: 92.6302 -6.0238 -0.0919 2.3443 -0.9546 0.5824 3.6723 0.3555 0.4576 0.1716 1.4800 0.0363 1.0519 0.0791
+#> 203: 92.6040 -6.0387 -0.0944 2.3405 -0.9579 0.5710 3.9080 0.3583 0.4476 0.1752 1.4934 0.0373 1.0842 0.0762
+#> 204: 92.6042 -6.0088 -0.0965 2.3351 -0.9580 0.6145 3.8412 0.3608 0.4413 0.1720 1.5047 0.0374 1.0694 0.0760
+#> 205: 92.5887 -6.0107 -0.0968 2.3362 -0.9576 0.6432 3.8854 0.3606 0.4405 0.1711 1.4896 0.0380 1.0615 0.0750
+#> 206: 92.6452 -5.9990 -0.0992 2.3311 -0.9581 0.6728 3.8231 0.3636 0.4339 0.1683 1.4904 0.0379 1.0630 0.0747
+#> 207: 92.6867 -5.9760 -0.1012 2.3283 -0.9606 0.6907 3.6867 0.3665 0.4303 0.1665 1.4908 0.0376 1.0656 0.0739
+#> 208: 92.6867 -5.9652 -0.1033 2.3252 -0.9611 0.6656 3.6185 0.3680 0.4271 0.1656 1.4972 0.0369 1.0944 0.0724
+#> 209: 92.6807 -5.9535 -0.1051 2.3225 -0.9621 0.6532 3.5653 0.3669 0.4249 0.1641 1.4992 0.0366 1.1029 0.0721
+#> 210: 92.6772 -5.9392 -0.1067 2.3185 -0.9611 0.6492 3.4774 0.3661 0.4220 0.1620 1.5034 0.0360 1.0982 0.0723
+#> 211: 92.6803 -5.9099 -0.1089 2.3129 -0.9619 0.6462 3.3783 0.3656 0.4218 0.1622 1.5094 0.0354 1.1060 0.0725
+#> 212: 92.7033 -5.9046 -0.1110 2.3085 -0.9606 0.6467 3.3879 0.3653 0.4222 0.1602 1.5099 0.0350 1.1004 0.0726
+#> 213: 92.7143 -5.9026 -0.1135 2.3046 -0.9594 0.6326 3.3887 0.3646 0.4214 0.1585 1.5139 0.0347 1.1050 0.0722
+#> 214: 92.7156 -5.9151 -0.1157 2.3011 -0.9590 0.6186 3.4587 0.3637 0.4205 0.1571 1.5149 0.0344 1.1060 0.0720
+#> 215: 92.7185 -5.9240 -0.1177 2.2984 -0.9585 0.6226 3.5192 0.3630 0.4190 0.1564 1.5155 0.0342 1.1159 0.0713
+#> 216: 92.7133 -5.9331 -0.1197 2.2953 -0.9575 0.6253 3.5505 0.3630 0.4179 0.1552 1.5199 0.0338 1.1276 0.0708
+#> 217: 92.7111 -5.9341 -0.1215 2.2924 -0.9579 0.6200 3.5565 0.3627 0.4170 0.1542 1.5238 0.0337 1.1409 0.0702
+#> 218: 92.7142 -5.9390 -0.1226 2.2901 -0.9588 0.6110 3.5792 0.3623 0.4162 0.1541 1.5236 0.0335 1.1378 0.0704
+#> 219: 92.7121 -5.9351 -0.1233 2.2891 -0.9587 0.6083 3.5562 0.3617 0.4154 0.1535 1.5280 0.0335 1.1518 0.0697
+#> 220: 92.7133 -5.9467 -0.1244 2.2876 -0.9591 0.6158 3.6036 0.3614 0.4147 0.1542 1.5273 0.0334 1.1572 0.0693
+#> 221: 92.7206 -5.9543 -0.1253 2.2856 -0.9602 0.6252 3.6357 0.3610 0.4131 0.1540 1.5272 0.0335 1.1591 0.0692
+#> 222: 92.7267 -5.9436 -0.1262 2.2840 -0.9608 0.6377 3.5725 0.3608 0.4118 0.1540 1.5302 0.0334 1.1735 0.0683
+#> 223: 92.7364 -5.9346 -0.1268 2.2825 -0.9619 0.6430 3.5288 0.3606 0.4117 0.1542 1.5327 0.0332 1.1883 0.0676
+#> 224: 92.7464 -5.9269 -0.1274 2.2822 -0.9621 0.6394 3.4906 0.3604 0.4107 0.1541 1.5342 0.0334 1.2022 0.0667
+#> 225: 92.7572 -5.9244 -0.1278 2.2813 -0.9616 0.6340 3.4677 0.3603 0.4100 0.1535 1.5345 0.0334 1.2129 0.0661
+#> 226: 92.7662 -5.9237 -0.1282 2.2803 -0.9615 0.6336 3.4532 0.3603 0.4101 0.1532 1.5326 0.0334 1.2151 0.0661
+#> 227: 92.7778 -5.9193 -0.1286 2.2792 -0.9628 0.6280 3.4339 0.3604 0.4096 0.1527 1.5323 0.0334 1.2217 0.0658
+#> 228: 92.7824 -5.9112 -0.1289 2.2782 -0.9636 0.6217 3.3964 0.3607 0.4091 0.1525 1.5316 0.0335 1.2255 0.0658
+#> 229: 92.7895 -5.9077 -0.1291 2.2770 -0.9646 0.6178 3.3717 0.3607 0.4096 0.1521 1.5326 0.0334 1.2247 0.0660
+#> 230: 92.7987 -5.9153 -0.1297 2.2758 -0.9648 0.6177 3.4004 0.3603 0.4098 0.1517 1.5333 0.0334 1.2321 0.0656
+#> 231: 92.8081 -5.9176 -0.1308 2.2735 -0.9654 0.6185 3.4195 0.3596 0.4086 0.1513 1.5361 0.0331 1.2359 0.0656
+#> 232: 92.8119 -5.9161 -0.1318 2.2715 -0.9658 0.6140 3.4221 0.3590 0.4075 0.1513 1.5387 0.0330 1.2434 0.0653
+#> 233: 92.8117 -5.9111 -0.1329 2.2694 -0.9662 0.6096 3.4008 0.3586 0.4065 0.1511 1.5410 0.0328 1.2426 0.0654
+#> 234: 92.8132 -5.9040 -0.1339 2.2672 -0.9660 0.6097 3.3787 0.3583 0.4059 0.1506 1.5425 0.0325 1.2463 0.0654
+#> 235: 92.8117 -5.8978 -0.1347 2.2653 -0.9661 0.6020 3.3558 0.3579 0.4051 0.1502 1.5443 0.0324 1.2439 0.0657
+#> 236: 92.8050 -5.8967 -0.1355 2.2638 -0.9663 0.5963 3.3466 0.3575 0.4046 0.1495 1.5453 0.0322 1.2377 0.0661
+#> 237: 92.7975 -5.9004 -0.1362 2.2625 -0.9668 0.5891 3.3624 0.3571 0.4043 0.1491 1.5460 0.0321 1.2334 0.0664
+#> 238: 92.7965 -5.9036 -0.1371 2.2613 -0.9670 0.5828 3.3683 0.3569 0.4037 0.1488 1.5486 0.0320 1.2405 0.0662
+#> 239: 92.8006 -5.9067 -0.1376 2.2607 -0.9677 0.5767 3.3801 0.3568 0.4027 0.1490 1.5487 0.0319 1.2478 0.0658
+#> 240: 92.8061 -5.9102 -0.1382 2.2597 -0.9678 0.5697 3.3876 0.3566 0.4014 0.1489 1.5499 0.0319 1.2545 0.0654
+#> 241: 92.8111 -5.9132 -0.1388 2.2589 -0.9684 0.5647 3.3986 0.3567 0.4004 0.1489 1.5507 0.0319 1.2607 0.0651
+#> 242: 92.8157 -5.9119 -0.1395 2.2577 -0.9686 0.5610 3.3902 0.3568 0.3995 0.1490 1.5524 0.0319 1.2673 0.0647
+#> 243: 92.8204 -5.9142 -0.1401 2.2567 -0.9689 0.5597 3.3991 0.3570 0.3983 0.1492 1.5526 0.0319 1.2728 0.0646
+#> 244: 92.8272 -5.9129 -0.1408 2.2558 -0.9689 0.5598 3.3989 0.3574 0.3972 0.1493 1.5542 0.0319 1.2805 0.0642
+#> 245: 92.8361 -5.9152 -0.1414 2.2548 -0.9693 0.5617 3.4133 0.3580 0.3959 0.1500 1.5541 0.0318 1.2876 0.0638
+#> 246: 92.8432 -5.9122 -0.1420 2.2536 -0.9695 0.5627 3.4039 0.3584 0.3946 0.1507 1.5546 0.0318 1.2944 0.0633
+#> 247: 92.8481 -5.9125 -0.1426 2.2524 -0.9695 0.5574 3.4087 0.3588 0.3931 0.1515 1.5556 0.0318 1.3003 0.0629
+#> 248: 92.8486 -5.9123 -0.1433 2.2515 -0.9693 0.5545 3.4095 0.3594 0.3916 0.1519 1.5583 0.0317 1.3043 0.0626
+#> 249: 92.8515 -5.9123 -0.1439 2.2505 -0.9694 0.5547 3.4088 0.3600 0.3904 0.1523 1.5605 0.0316 1.3087 0.0623
+#> 250: 92.8521 -5.9139 -0.1443 2.2493 -0.9691 0.5589 3.4212 0.3604 0.3894 0.1525 1.5617 0.0316 1.3081 0.0624
+#> 251: 92.8530 -5.9118 -0.1450 2.2484 -0.9683 0.5562 3.4138 0.3612 0.3884 0.1528 1.5615 0.0316 1.3066 0.0625
+#> 252: 92.8568 -5.9075 -0.1457 2.2474 -0.9681 0.5506 3.3889 0.3619 0.3875 0.1531 1.5620 0.0315 1.3067 0.0625
+#> 253: 92.8603 -5.9070 -0.1464 2.2467 -0.9682 0.5476 3.3746 0.3622 0.3867 0.1539 1.5640 0.0314 1.3122 0.0622
+#> 254: 92.8653 -5.9077 -0.1470 2.2457 -0.9688 0.5448 3.3656 0.3626 0.3858 0.1546 1.5641 0.0314 1.3147 0.0620
+#> 255: 92.8686 -5.9059 -0.1477 2.2445 -0.9688 0.5406 3.3533 0.3630 0.3850 0.1549 1.5637 0.0314 1.3155 0.0619
+#> 256: 92.8706 -5.9011 -0.1483 2.2435 -0.9685 0.5384 3.3300 0.3634 0.3841 0.1550 1.5644 0.0313 1.3161 0.0617
+#> 257: 92.8721 -5.8957 -0.1488 2.2426 -0.9683 0.5398 3.3084 0.3638 0.3833 0.1552 1.5647 0.0313 1.3158 0.0617
+#> 258: 92.8725 -5.8928 -0.1493 2.2419 -0.9680 0.5392 3.2921 0.3641 0.3822 0.1552 1.5665 0.0312 1.3184 0.0614
+#> 259: 92.8718 -5.8915 -0.1498 2.2411 -0.9680 0.5367 3.2850 0.3644 0.3815 0.1553 1.5668 0.0312 1.3202 0.0613
+#> 260: 92.8701 -5.8928 -0.1499 2.2409 -0.9679 0.5339 3.2888 0.3652 0.3802 0.1552 1.5675 0.0312 1.3215 0.0612
+#> 261: 92.8700 -5.8961 -0.1499 2.2407 -0.9679 0.5302 3.2976 0.3659 0.3789 0.1551 1.5677 0.0312 1.3197 0.0613
+#> 262: 92.8683 -5.9013 -0.1500 2.2407 -0.9678 0.5282 3.3236 0.3666 0.3778 0.1549 1.5684 0.0312 1.3184 0.0613
+#> 263: 92.8662 -5.9021 -0.1498 2.2407 -0.9677 0.5271 3.3285 0.3670 0.3767 0.1547 1.5682 0.0313 1.3156 0.0615
+#> 264: 92.8631 -5.9059 -0.1495 2.2409 -0.9675 0.5244 3.3527 0.3673 0.3755 0.1547 1.5677 0.0313 1.3139 0.0616
+#> 265: 92.8635 -5.9042 -0.1492 2.2411 -0.9675 0.5220 3.3541 0.3675 0.3745 0.1545 1.5676 0.0313 1.3098 0.0618
+#> 266: 92.8636 -5.9033 -0.1490 2.2411 -0.9673 0.5208 3.3523 0.3680 0.3735 0.1546 1.5679 0.0312 1.3087 0.0619
+#> 267: 92.8639 -5.9035 -0.1489 2.2413 -0.9673 0.5208 3.3566 0.3685 0.3726 0.1546 1.5676 0.0312 1.3072 0.0621
+#> 268: 92.8620 -5.9065 -0.1487 2.2413 -0.9674 0.5191 3.3797 0.3689 0.3717 0.1545 1.5676 0.0312 1.3103 0.0620
+#> 269: 92.8593 -5.9073 -0.1486 2.2416 -0.9672 0.5192 3.3885 0.3693 0.3710 0.1545 1.5685 0.0312 1.3136 0.0618
+#> 270: 92.8549 -5.9087 -0.1487 2.2418 -0.9672 0.5209 3.4007 0.3695 0.3703 0.1544 1.5703 0.0312 1.3177 0.0615
+#> 271: 92.8519 -5.9089 -0.1487 2.2416 -0.9671 0.5227 3.4043 0.3696 0.3697 0.1545 1.5705 0.0312 1.3216 0.0613
+#> 272: 92.8493 -5.9084 -0.1488 2.2416 -0.9669 0.5223 3.3999 0.3698 0.3693 0.1543 1.5707 0.0311 1.3206 0.0614
+#> 273: 92.8479 -5.9090 -0.1486 2.2416 -0.9667 0.5230 3.3980 0.3701 0.3689 0.1544 1.5699 0.0311 1.3192 0.0615
+#> 274: 92.8456 -5.9108 -0.1485 2.2417 -0.9667 0.5249 3.4024 0.3705 0.3684 0.1544 1.5688 0.0311 1.3169 0.0617
+#> 275: 92.8440 -5.9131 -0.1483 2.2422 -0.9666 0.5253 3.4117 0.3707 0.3677 0.1542 1.5690 0.0311 1.3166 0.0616
+#> 276: 92.8425 -5.9132 -0.1482 2.2426 -0.9662 0.5241 3.4171 0.3709 0.3670 0.1540 1.5689 0.0311 1.3142 0.0617
+#> 277: 92.8412 -5.9139 -0.1481 2.2430 -0.9660 0.5214 3.4228 0.3711 0.3663 0.1540 1.5687 0.0311 1.3173 0.0615
+#> 278: 92.8398 -5.9139 -0.1479 2.2432 -0.9659 0.5184 3.4254 0.3712 0.3654 0.1540 1.5684 0.0311 1.3148 0.0617
+#> 279: 92.8386 -5.9156 -0.1478 2.2433 -0.9661 0.5157 3.4338 0.3713 0.3649 0.1539 1.5682 0.0311 1.3136 0.0618
+#> 280: 92.8378 -5.9173 -0.1478 2.2428 -0.9663 0.5127 3.4381 0.3714 0.3643 0.1537 1.5679 0.0311 1.3104 0.0621
+#> 281: 92.8364 -5.9188 -0.1479 2.2423 -0.9666 0.5089 3.4418 0.3716 0.3634 0.1533 1.5674 0.0311 1.3071 0.0623
+#> 282: 92.8377 -5.9179 -0.1481 2.2418 -0.9668 0.5045 3.4355 0.3717 0.3626 0.1530 1.5686 0.0311 1.3055 0.0624
+#> 283: 92.8385 -5.9157 -0.1485 2.2410 -0.9667 0.5014 3.4260 0.3720 0.3616 0.1527 1.5699 0.0311 1.3072 0.0622
+#> 284: 92.8388 -5.9156 -0.1489 2.2403 -0.9666 0.4977 3.4274 0.3723 0.3605 0.1525 1.5705 0.0310 1.3081 0.0621
+#> 285: 92.8374 -5.9156 -0.1492 2.2395 -0.9668 0.4944 3.4215 0.3727 0.3594 0.1525 1.5716 0.0310 1.3103 0.0619
+#> 286: 92.8376 -5.9168 -0.1496 2.2388 -0.9672 0.4915 3.4197 0.3731 0.3583 0.1526 1.5724 0.0310 1.3141 0.0617
+#> 287: 92.8393 -5.9176 -0.1498 2.2380 -0.9673 0.4886 3.4177 0.3735 0.3572 0.1523 1.5737 0.0309 1.3155 0.0615
+#> 288: 92.8400 -5.9206 -0.1502 2.2372 -0.9675 0.4873 3.4259 0.3739 0.3562 0.1523 1.5739 0.0309 1.3160 0.0614
+#> 289: 92.8404 -5.9217 -0.1506 2.2362 -0.9678 0.4845 3.4269 0.3744 0.3552 0.1524 1.5735 0.0309 1.3165 0.0614
+#> 290: 92.8395 -5.9255 -0.1510 2.2354 -0.9680 0.4830 3.4395 0.3748 0.3543 0.1521 1.5737 0.0308 1.3159 0.0615
+#> 291: 92.8384 -5.9274 -0.1513 2.2345 -0.9680 0.4841 3.4460 0.3752 0.3533 0.1518 1.5742 0.0309 1.3173 0.0613
+#> 292: 92.8384 -5.9276 -0.1515 2.2342 -0.9681 0.4865 3.4437 0.3755 0.3525 0.1516 1.5738 0.0309 1.3163 0.0614
+#> 293: 92.8385 -5.9281 -0.1517 2.2338 -0.9681 0.4882 3.4446 0.3757 0.3516 0.1513 1.5738 0.0308 1.3143 0.0614
+#> 294: 92.8400 -5.9277 -0.1519 2.2335 -0.9680 0.4871 3.4449 0.3758 0.3508 0.1512 1.5736 0.0308 1.3149 0.0614
+#> 295: 92.8414 -5.9279 -0.1520 2.2331 -0.9680 0.4842 3.4523 0.3760 0.3502 0.1510 1.5740 0.0308 1.3153 0.0614
+#> 296: 92.8424 -5.9282 -0.1521 2.2329 -0.9681 0.4835 3.4589 0.3760 0.3496 0.1509 1.5743 0.0307 1.3180 0.0613
+#> 297: 92.8409 -5.9281 -0.1522 2.2325 -0.9683 0.4827 3.4636 0.3760 0.3491 0.1509 1.5745 0.0307 1.3216 0.0611
+#> 298: 92.8395 -5.9276 -0.1522 2.2322 -0.9684 0.4819 3.4641 0.3761 0.3486 0.1508 1.5744 0.0307 1.3226 0.0612
+#> 299: 92.8388 -5.9305 -0.1524 2.2321 -0.9686 0.4800 3.4829 0.3761 0.3481 0.1507 1.5745 0.0307 1.3218 0.0612
+#> 300: 92.8375 -5.9329 -0.1524 2.2321 -0.9683 0.4792 3.4982 0.3761 0.3477 0.1505 1.5745 0.0307 1.3205 0.0613
+#> 301: 92.8359 -5.9337 -0.1524 2.2321 -0.9680 0.4788 3.5056 0.3762 0.3473 0.1503 1.5746 0.0306 1.3182 0.0614
+#> 302: 92.8346 -5.9360 -0.1524 2.2322 -0.9678 0.4800 3.5237 0.3763 0.3470 0.1500 1.5744 0.0306 1.3174 0.0614
+#> 303: 92.8338 -5.9387 -0.1524 2.2324 -0.9674 0.4795 3.5444 0.3764 0.3467 0.1501 1.5738 0.0307 1.3181 0.0613
+#> 304: 92.8318 -5.9436 -0.1524 2.2327 -0.9673 0.4787 3.5819 0.3766 0.3464 0.1502 1.5735 0.0307 1.3191 0.0612
+#> 305: 92.8300 -5.9486 -0.1524 2.2327 -0.9673 0.4794 3.6200 0.3766 0.3460 0.1502 1.5726 0.0308 1.3198 0.0611
+#> 306: 92.8294 -5.9540 -0.1524 2.2328 -0.9673 0.4788 3.6681 0.3766 0.3456 0.1502 1.5723 0.0309 1.3214 0.0610
+#> 307: 92.8287 -5.9579 -0.1525 2.2330 -0.9669 0.4779 3.7052 0.3766 0.3452 0.1498 1.5735 0.0309 1.3235 0.0609
+#> 308: 92.8290 -5.9624 -0.1524 2.2332 -0.9669 0.4775 3.7470 0.3766 0.3448 0.1500 1.5737 0.0309 1.3265 0.0607
+#> 309: 92.8293 -5.9653 -0.1524 2.2333 -0.9668 0.4774 3.7756 0.3766 0.3443 0.1499 1.5736 0.0309 1.3290 0.0605
+#> 310: 92.8289 -5.9672 -0.1523 2.2335 -0.9669 0.4762 3.7957 0.3767 0.3438 0.1499 1.5736 0.0309 1.3316 0.0603
+#> 311: 92.8301 -5.9702 -0.1521 2.2337 -0.9670 0.4755 3.8172 0.3767 0.3432 0.1498 1.5737 0.0309 1.3324 0.0603
+#> 312: 92.8322 -5.9715 -0.1520 2.2341 -0.9670 0.4742 3.8229 0.3767 0.3427 0.1496 1.5734 0.0309 1.3309 0.0603
+#> 313: 92.8338 -5.9713 -0.1517 2.2342 -0.9672 0.4737 3.8202 0.3766 0.3422 0.1494 1.5733 0.0309 1.3306 0.0604
+#> 314: 92.8360 -5.9711 -0.1515 2.2343 -0.9675 0.4725 3.8154 0.3767 0.3417 0.1493 1.5733 0.0309 1.3322 0.0603
+#> 315: 92.8378 -5.9694 -0.1514 2.2343 -0.9680 0.4714 3.8051 0.3767 0.3414 0.1494 1.5734 0.0309 1.3352 0.0601
+#> 316: 92.8400 -5.9683 -0.1514 2.2343 -0.9682 0.4705 3.7984 0.3767 0.3410 0.1495 1.5735 0.0309 1.3354 0.0602
+#> 317: 92.8422 -5.9689 -0.1513 2.2344 -0.9686 0.4695 3.7961 0.3768 0.3406 0.1497 1.5735 0.0309 1.3362 0.0602
+#> 318: 92.8440 -5.9696 -0.1510 2.2347 -0.9689 0.4681 3.7934 0.3769 0.3403 0.1499 1.5731 0.0309 1.3381 0.0601
+#> 319: 92.8458 -5.9710 -0.1508 2.2350 -0.9692 0.4668 3.7913 0.3769 0.3401 0.1500 1.5723 0.0309 1.3403 0.0599
+#> 320: 92.8474 -5.9719 -0.1506 2.2353 -0.9695 0.4667 3.7876 0.3769 0.3400 0.1502 1.5714 0.0309 1.3423 0.0598
+#> 321: 92.8494 -5.9710 -0.1503 2.2355 -0.9696 0.4673 3.7790 0.3769 0.3397 0.1503 1.5709 0.0309 1.3439 0.0597
+#> 322: 92.8511 -5.9693 -0.1501 2.2359 -0.9698 0.4690 3.7674 0.3769 0.3395 0.1503 1.5708 0.0309 1.3451 0.0596
+#> 323: 92.8528 -5.9700 -0.1498 2.2364 -0.9699 0.4696 3.7641 0.3768 0.3394 0.1504 1.5701 0.0310 1.3470 0.0594
+#> 324: 92.8547 -5.9695 -0.1495 2.2369 -0.9699 0.4703 3.7567 0.3767 0.3392 0.1505 1.5698 0.0310 1.3485 0.0593
+#> 325: 92.8563 -5.9678 -0.1490 2.2376 -0.9702 0.4701 3.7473 0.3769 0.3395 0.1505 1.5702 0.0311 1.3494 0.0592
+#> 326: 92.8582 -5.9676 -0.1486 2.2382 -0.9703 0.4709 3.7434 0.3771 0.3397 0.1506 1.5700 0.0311 1.3479 0.0593
+#> 327: 92.8603 -5.9665 -0.1481 2.2389 -0.9704 0.4716 3.7361 0.3769 0.3399 0.1507 1.5699 0.0311 1.3471 0.0594
+#> 328: 92.8622 -5.9671 -0.1477 2.2397 -0.9704 0.4726 3.7379 0.3767 0.3398 0.1507 1.5698 0.0311 1.3481 0.0593
+#> 329: 92.8639 -5.9667 -0.1473 2.2405 -0.9707 0.4735 3.7366 0.3766 0.3398 0.1506 1.5696 0.0311 1.3482 0.0593
+#> 330: 92.8663 -5.9673 -0.1469 2.2413 -0.9708 0.4736 3.7382 0.3765 0.3397 0.1506 1.5691 0.0312 1.3492 0.0592
+#> 331: 92.8674 -5.9670 -0.1464 2.2420 -0.9710 0.4740 3.7350 0.3763 0.3397 0.1507 1.5689 0.0312 1.3512 0.0591
+#> 332: 92.8681 -5.9664 -0.1460 2.2428 -0.9710 0.4737 3.7311 0.3762 0.3396 0.1509 1.5687 0.0312 1.3527 0.0590
+#> 333: 92.8683 -5.9649 -0.1456 2.2436 -0.9708 0.4727 3.7232 0.3760 0.3397 0.1509 1.5686 0.0312 1.3505 0.0591
+#> 334: 92.8690 -5.9642 -0.1452 2.2444 -0.9707 0.4723 3.7194 0.3758 0.3399 0.1511 1.5682 0.0312 1.3490 0.0592
+#> 335: 92.8698 -5.9656 -0.1447 2.2454 -0.9707 0.4722 3.7289 0.3756 0.3400 0.1512 1.5674 0.0313 1.3476 0.0592
+#> 336: 92.8691 -5.9664 -0.1443 2.2463 -0.9706 0.4724 3.7333 0.3753 0.3401 0.1511 1.5669 0.0313 1.3455 0.0593
+#> 337: 92.8687 -5.9670 -0.1440 2.2471 -0.9705 0.4742 3.7378 0.3749 0.3402 0.1510 1.5665 0.0314 1.3433 0.0594
+#> 338: 92.8683 -5.9663 -0.1435 2.2480 -0.9703 0.4747 3.7370 0.3746 0.3405 0.1510 1.5663 0.0313 1.3402 0.0595
+#> 339: 92.8682 -5.9650 -0.1431 2.2488 -0.9701 0.4760 3.7332 0.3743 0.3408 0.1509 1.5661 0.0313 1.3374 0.0597
+#> 340: 92.8684 -5.9639 -0.1427 2.2496 -0.9699 0.4774 3.7283 0.3739 0.3411 0.1510 1.5658 0.0313 1.3358 0.0597
+#> 341: 92.8685 -5.9610 -0.1423 2.2504 -0.9696 0.4782 3.7169 0.3735 0.3413 0.1510 1.5661 0.0313 1.3338 0.0598
+#> 342: 92.8681 -5.9581 -0.1419 2.2512 -0.9696 0.4802 3.7060 0.3731 0.3416 0.1511 1.5661 0.0313 1.3316 0.0599
+#> 343: 92.8671 -5.9557 -0.1414 2.2521 -0.9697 0.4821 3.6971 0.3726 0.3419 0.1510 1.5667 0.0313 1.3292 0.0601
+#> 344: 92.8662 -5.9550 -0.1409 2.2531 -0.9696 0.4825 3.6931 0.3722 0.3424 0.1509 1.5660 0.0314 1.3269 0.0602
+#> 345: 92.8651 -5.9542 -0.1405 2.2542 -0.9696 0.4825 3.6886 0.3717 0.3429 0.1511 1.5645 0.0315 1.3252 0.0602
+#> 346: 92.8636 -5.9534 -0.1401 2.2549 -0.9696 0.4822 3.6821 0.3714 0.3432 0.1510 1.5638 0.0315 1.3231 0.0603
+#> 347: 92.8622 -5.9532 -0.1397 2.2557 -0.9696 0.4815 3.6782 0.3712 0.3435 0.1509 1.5636 0.0315 1.3220 0.0604
+#> 348: 92.8593 -5.9538 -0.1394 2.2566 -0.9697 0.4813 3.6787 0.3709 0.3438 0.1508 1.5634 0.0315 1.3202 0.0605
+#> 349: 92.8574 -5.9532 -0.1389 2.2574 -0.9697 0.4808 3.6739 0.3706 0.3440 0.1506 1.5630 0.0316 1.3179 0.0606
+#> 350: 92.8561 -5.9528 -0.1385 2.2583 -0.9697 0.4801 3.6705 0.3703 0.3443 0.1505 1.5625 0.0316 1.3161 0.0607
+#> 351: 92.8541 -5.9518 -0.1381 2.2591 -0.9697 0.4804 3.6650 0.3700 0.3446 0.1505 1.5619 0.0316 1.3141 0.0608
+#> 352: 92.8528 -5.9516 -0.1377 2.2599 -0.9700 0.4818 3.6626 0.3698 0.3449 0.1504 1.5614 0.0316 1.3122 0.0609
+#> 353: 92.8506 -5.9518 -0.1373 2.2607 -0.9700 0.4836 3.6601 0.3697 0.3451 0.1506 1.5604 0.0317 1.3116 0.0610
+#> 354: 92.8482 -5.9507 -0.1369 2.2615 -0.9700 0.4852 3.6520 0.3696 0.3451 0.1506 1.5595 0.0317 1.3099 0.0611
+#> 355: 92.8459 -5.9500 -0.1365 2.2624 -0.9699 0.4873 3.6467 0.3695 0.3454 0.1505 1.5589 0.0318 1.3090 0.0611
+#> 356: 92.8441 -5.9494 -0.1361 2.2632 -0.9700 0.4893 3.6407 0.3696 0.3456 0.1505 1.5581 0.0319 1.3083 0.0612
+#> 357: 92.8425 -5.9492 -0.1356 2.2641 -0.9700 0.4906 3.6359 0.3696 0.3459 0.1506 1.5568 0.0320 1.3082 0.0612
+#> 358: 92.8414 -5.9487 -0.1351 2.2649 -0.9700 0.4914 3.6300 0.3697 0.3460 0.1506 1.5559 0.0321 1.3064 0.0613
+#> 359: 92.8395 -5.9487 -0.1346 2.2657 -0.9700 0.4923 3.6262 0.3699 0.3462 0.1507 1.5558 0.0321 1.3050 0.0614
+#> 360: 92.8373 -5.9478 -0.1341 2.2666 -0.9700 0.4922 3.6206 0.3700 0.3465 0.1509 1.5553 0.0322 1.3061 0.0614
+#> 361: 92.8353 -5.9475 -0.1337 2.2673 -0.9699 0.4912 3.6183 0.3700 0.3469 0.1510 1.5549 0.0322 1.3051 0.0614
+#> 362: 92.8339 -5.9474 -0.1333 2.2681 -0.9699 0.4896 3.6164 0.3700 0.3472 0.1510 1.5549 0.0322 1.3041 0.0616
+#> 363: 92.8318 -5.9470 -0.1328 2.2690 -0.9696 0.4882 3.6136 0.3700 0.3476 0.1510 1.5541 0.0323 1.3035 0.0616
+#> 364: 92.8305 -5.9460 -0.1325 2.2697 -0.9695 0.4863 3.6099 0.3701 0.3477 0.1510 1.5533 0.0324 1.3028 0.0616
+#> 365: 92.8300 -5.9451 -0.1320 2.2705 -0.9693 0.4851 3.6083 0.3703 0.3479 0.1511 1.5535 0.0324 1.3017 0.0617
+#> 366: 92.8290 -5.9444 -0.1317 2.2710 -0.9691 0.4841 3.6062 0.3707 0.3476 0.1512 1.5534 0.0325 1.3013 0.0617
+#> 367: 92.8279 -5.9438 -0.1313 2.2715 -0.9688 0.4829 3.6026 0.3711 0.3473 0.1513 1.5537 0.0325 1.2996 0.0618
+#> 368: 92.8270 -5.9437 -0.1310 2.2721 -0.9687 0.4824 3.6015 0.3715 0.3471 0.1513 1.5535 0.0325 1.2984 0.0619
+#> 369: 92.8268 -5.9444 -0.1306 2.2726 -0.9686 0.4829 3.6042 0.3718 0.3469 0.1514 1.5530 0.0325 1.2983 0.0619
+#> 370: 92.8268 -5.9455 -0.1303 2.2732 -0.9686 0.4833 3.6099 0.3721 0.3466 0.1513 1.5526 0.0326 1.2971 0.0619
+#> 371: 92.8269 -5.9462 -0.1300 2.2737 -0.9686 0.4842 3.6169 0.3723 0.3465 0.1512 1.5516 0.0326 1.2961 0.0619
+#> 372: 92.8272 -5.9465 -0.1297 2.2741 -0.9685 0.4852 3.6242 0.3726 0.3463 0.1512 1.5507 0.0327 1.2950 0.0620
+#> 373: 92.8275 -5.9456 -0.1294 2.2746 -0.9686 0.4861 3.6219 0.3729 0.3461 0.1511 1.5501 0.0328 1.2946 0.0620
+#> 374: 92.8278 -5.9445 -0.1291 2.2750 -0.9687 0.4867 3.6175 0.3730 0.3461 0.1509 1.5496 0.0328 1.2942 0.0620
+#> 375: 92.8285 -5.9438 -0.1289 2.2753 -0.9689 0.4874 3.6118 0.3731 0.3459 0.1509 1.5491 0.0329 1.2938 0.0620
+#> 376: 92.8286 -5.9439 -0.1287 2.2755 -0.9689 0.4876 3.6100 0.3733 0.3458 0.1508 1.5488 0.0329 1.2930 0.0621
+#> 377: 92.8289 -5.9431 -0.1285 2.2758 -0.9690 0.4870 3.6054 0.3735 0.3456 0.1508 1.5487 0.0329 1.2921 0.0621
+#> 378: 92.8293 -5.9428 -0.1284 2.2760 -0.9689 0.4865 3.6019 0.3737 0.3454 0.1508 1.5484 0.0329 1.2910 0.0622
+#> 379: 92.8294 -5.9441 -0.1282 2.2763 -0.9688 0.4857 3.6077 0.3739 0.3451 0.1507 1.5480 0.0329 1.2907 0.0622
+#> 380: 92.8296 -5.9448 -0.1281 2.2766 -0.9688 0.4844 3.6104 0.3741 0.3448 0.1506 1.5475 0.0329 1.2901 0.0622
+#> 381: 92.8301 -5.9461 -0.1280 2.2767 -0.9689 0.4833 3.6194 0.3743 0.3444 0.1505 1.5476 0.0329 1.2893 0.0622
+#> 382: 92.8312 -5.9464 -0.1278 2.2768 -0.9689 0.4823 3.6237 0.3745 0.3441 0.1505 1.5476 0.0329 1.2881 0.0622
+#> 383: 92.8317 -5.9459 -0.1277 2.2770 -0.9687 0.4817 3.6282 0.3747 0.3438 0.1504 1.5479 0.0329 1.2875 0.0622
+#> 384: 92.8325 -5.9458 -0.1276 2.2772 -0.9686 0.4818 3.6293 0.3749 0.3434 0.1503 1.5481 0.0329 1.2863 0.0623
+#> 385: 92.8337 -5.9449 -0.1275 2.2773 -0.9685 0.4832 3.6263 0.3751 0.3431 0.1503 1.5481 0.0330 1.2860 0.0622
+#> 386: 92.8346 -5.9455 -0.1274 2.2773 -0.9682 0.4834 3.6283 0.3754 0.3427 0.1501 1.5483 0.0330 1.2851 0.0623
+#> 387: 92.8353 -5.9460 -0.1273 2.2775 -0.9681 0.4831 3.6303 0.3756 0.3424 0.1499 1.5486 0.0330 1.2836 0.0623
+#> 388: 92.8365 -5.9462 -0.1272 2.2777 -0.9680 0.4831 3.6294 0.3759 0.3420 0.1498 1.5486 0.0330 1.2830 0.0624
+#> 389: 92.8378 -5.9456 -0.1271 2.2779 -0.9678 0.4830 3.6260 0.3762 0.3416 0.1497 1.5486 0.0330 1.2816 0.0624
+#> 390: 92.8397 -5.9454 -0.1270 2.2779 -0.9678 0.4835 3.6245 0.3765 0.3413 0.1496 1.5488 0.0330 1.2805 0.0625
+#> 391: 92.8416 -5.9461 -0.1269 2.2780 -0.9679 0.4841 3.6273 0.3768 0.3409 0.1497 1.5486 0.0330 1.2816 0.0624
+#> 392: 92.8430 -5.9471 -0.1269 2.2779 -0.9679 0.4844 3.6293 0.3771 0.3408 0.1498 1.5483 0.0330 1.2830 0.0623
+#> 393: 92.8444 -5.9478 -0.1269 2.2779 -0.9680 0.4841 3.6310 0.3774 0.3407 0.1500 1.5485 0.0330 1.2842 0.0623
+#> 394: 92.8458 -5.9492 -0.1268 2.2779 -0.9680 0.4839 3.6370 0.3775 0.3407 0.1502 1.5484 0.0330 1.2847 0.0622
+#> 395: 92.8474 -5.9501 -0.1268 2.2780 -0.9681 0.4830 3.6391 0.3777 0.3406 0.1503 1.5485 0.0330 1.2849 0.0622
+#> 396: 92.8484 -5.9500 -0.1267 2.2781 -0.9682 0.4820 3.6369 0.3778 0.3406 0.1504 1.5490 0.0330 1.2850 0.0622
+#> 397: 92.8497 -5.9490 -0.1267 2.2782 -0.9680 0.4813 3.6308 0.3779 0.3407 0.1504 1.5494 0.0330 1.2848 0.0622
+#> 398: 92.8511 -5.9478 -0.1267 2.2782 -0.9679 0.4811 3.6256 0.3780 0.3407 0.1505 1.5498 0.0330 1.2844 0.0622
+#> 399: 92.8531 -5.9467 -0.1266 2.2782 -0.9680 0.4804 3.6208 0.3781 0.3407 0.1505 1.5505 0.0330 1.2842 0.0623
+#> 400: 92.8545 -5.9465 -0.1266 2.2782 -0.9679 0.4793 3.6175 0.3783 0.3406 0.1505 1.5506 0.0329 1.2833 0.0623
+#> 401: 92.8558 -5.9458 -0.1266 2.2781 -0.9679 0.4787 3.6135 0.3784 0.3406 0.1506 1.5506 0.0329 1.2836 0.0623
+#> 402: 92.8571 -5.9454 -0.1266 2.2780 -0.9678 0.4788 3.6122 0.3786 0.3405 0.1506 1.5508 0.0329 1.2841 0.0623
+#> 403: 92.8583 -5.9454 -0.1267 2.2778 -0.9679 0.4794 3.6115 0.3790 0.3402 0.1507 1.5508 0.0330 1.2859 0.0622
+#> 404: 92.8593 -5.9466 -0.1268 2.2776 -0.9681 0.4787 3.6149 0.3793 0.3401 0.1508 1.5507 0.0330 1.2875 0.0621
+#> 405: 92.8598 -5.9475 -0.1269 2.2774 -0.9681 0.4781 3.6208 0.3796 0.3399 0.1509 1.5507 0.0330 1.2888 0.0620
+#> 406: 92.8596 -5.9480 -0.1269 2.2773 -0.9680 0.4776 3.6238 0.3798 0.3397 0.1509 1.5508 0.0330 1.2895 0.0619
+#> 407: 92.8588 -5.9487 -0.1270 2.2773 -0.9679 0.4773 3.6289 0.3801 0.3395 0.1508 1.5510 0.0331 1.2887 0.0619
+#> 408: 92.8587 -5.9489 -0.1271 2.2771 -0.9677 0.4777 3.6323 0.3804 0.3391 0.1508 1.5513 0.0331 1.2878 0.0620
+#> 409: 92.8585 -5.9498 -0.1272 2.2770 -0.9677 0.4791 3.6383 0.3806 0.3389 0.1506 1.5512 0.0331 1.2865 0.0621
+#> 410: 92.8574 -5.9522 -0.1272 2.2769 -0.9676 0.4810 3.6538 0.3809 0.3387 0.1507 1.5509 0.0331 1.2855 0.0621
+#> 411: 92.8568 -5.9532 -0.1272 2.2767 -0.9675 0.4817 3.6651 0.3811 0.3385 0.1507 1.5508 0.0332 1.2842 0.0622
+#> 412: 92.8562 -5.9535 -0.1273 2.2767 -0.9674 0.4819 3.6756 0.3812 0.3383 0.1507 1.5509 0.0332 1.2851 0.0621
+#> 413: 92.8559 -5.9542 -0.1274 2.2766 -0.9672 0.4824 3.6881 0.3814 0.3381 0.1507 1.5514 0.0332 1.2848 0.0621
+#> 414: 92.8556 -5.9550 -0.1274 2.2765 -0.9670 0.4835 3.6990 0.3815 0.3379 0.1507 1.5519 0.0332 1.2838 0.0622
+#> 415: 92.8551 -5.9566 -0.1274 2.2764 -0.9669 0.4838 3.7133 0.3816 0.3377 0.1506 1.5522 0.0332 1.2828 0.0623
+#> 416: 92.8547 -5.9581 -0.1275 2.2764 -0.9668 0.4848 3.7276 0.3818 0.3374 0.1504 1.5526 0.0332 1.2814 0.0623
+#> 417: 92.8538 -5.9581 -0.1274 2.2764 -0.9667 0.4856 3.7321 0.3818 0.3372 0.1503 1.5532 0.0332 1.2800 0.0624
+#> 418: 92.8527 -5.9590 -0.1273 2.2766 -0.9665 0.4869 3.7398 0.3817 0.3372 0.1502 1.5532 0.0332 1.2787 0.0625
+#> 419: 92.8524 -5.9596 -0.1272 2.2768 -0.9663 0.4869 3.7467 0.3817 0.3372 0.1501 1.5531 0.0332 1.2779 0.0625
+#> 420: 92.8520 -5.9598 -0.1271 2.2771 -0.9662 0.4863 3.7494 0.3817 0.3372 0.1501 1.5528 0.0332 1.2774 0.0625
+#> 421: 92.8516 -5.9601 -0.1270 2.2772 -0.9661 0.4855 3.7541 0.3817 0.3372 0.1500 1.5527 0.0333 1.2763 0.0625
+#> 422: 92.8509 -5.9602 -0.1270 2.2775 -0.9659 0.4855 3.7554 0.3818 0.3371 0.1499 1.5525 0.0333 1.2753 0.0626
+#> 423: 92.8497 -5.9608 -0.1269 2.2777 -0.9658 0.4855 3.7590 0.3819 0.3371 0.1499 1.5524 0.0334 1.2746 0.0626
+#> 424: 92.8490 -5.9620 -0.1269 2.2779 -0.9658 0.4852 3.7657 0.3820 0.3370 0.1498 1.5521 0.0334 1.2740 0.0626
+#> 425: 92.8481 -5.9615 -0.1268 2.2780 -0.9657 0.4852 3.7639 0.3819 0.3369 0.1497 1.5520 0.0334 1.2741 0.0625
+#> 426: 92.8471 -5.9611 -0.1267 2.2783 -0.9656 0.4859 3.7632 0.3819 0.3369 0.1495 1.5520 0.0335 1.2744 0.0625
+#> 427: 92.8470 -5.9605 -0.1266 2.2784 -0.9655 0.4856 3.7616 0.3819 0.3368 0.1494 1.5522 0.0335 1.2739 0.0625
+#> 428: 92.8464 -5.9602 -0.1266 2.2786 -0.9653 0.4851 3.7603 0.3820 0.3367 0.1493 1.5522 0.0335 1.2731 0.0625
+#> 429: 92.8450 -5.9593 -0.1265 2.2788 -0.9652 0.4852 3.7573 0.3820 0.3366 0.1493 1.5525 0.0335 1.2720 0.0626
+#> 430: 92.8440 -5.9590 -0.1264 2.2789 -0.9651 0.4862 3.7586 0.3821 0.3365 0.1493 1.5524 0.0335 1.2710 0.0627
+#> 431: 92.8428 -5.9583 -0.1263 2.2791 -0.9649 0.4868 3.7575 0.3821 0.3365 0.1493 1.5522 0.0335 1.2698 0.0627
+#> 432: 92.8417 -5.9583 -0.1262 2.2793 -0.9649 0.4881 3.7580 0.3821 0.3365 0.1493 1.5518 0.0335 1.2683 0.0628
+#> 433: 92.8404 -5.9589 -0.1261 2.2796 -0.9648 0.4888 3.7614 0.3821 0.3364 0.1494 1.5513 0.0335 1.2681 0.0628
+#> 434: 92.8392 -5.9585 -0.1260 2.2798 -0.9646 0.4900 3.7602 0.3821 0.3363 0.1494 1.5509 0.0336 1.2686 0.0627
+#> 435: 92.8376 -5.9587 -0.1260 2.2801 -0.9645 0.4913 3.7622 0.3822 0.3362 0.1494 1.5506 0.0336 1.2677 0.0627
+#> 436: 92.8367 -5.9581 -0.1259 2.2802 -0.9646 0.4912 3.7594 0.3821 0.3361 0.1494 1.5504 0.0336 1.2684 0.0627
+#> 437: 92.8352 -5.9588 -0.1259 2.2803 -0.9647 0.4910 3.7634 0.3821 0.3360 0.1494 1.5501 0.0337 1.2695 0.0626
+#> 438: 92.8332 -5.9592 -0.1259 2.2804 -0.9648 0.4913 3.7649 0.3821 0.3358 0.1494 1.5498 0.0337 1.2705 0.0625
+#> 439: 92.8310 -5.9589 -0.1258 2.2805 -0.9648 0.4916 3.7630 0.3821 0.3357 0.1494 1.5497 0.0337 1.2713 0.0625
+#> 440: 92.8292 -5.9590 -0.1258 2.2806 -0.9649 0.4915 3.7620 0.3821 0.3355 0.1493 1.5494 0.0338 1.2712 0.0625
+#> 441: 92.8276 -5.9590 -0.1258 2.2808 -0.9650 0.4915 3.7619 0.3822 0.3353 0.1493 1.5493 0.0338 1.2712 0.0625
+#> 442: 92.8258 -5.9587 -0.1257 2.2809 -0.9650 0.4927 3.7592 0.3822 0.3351 0.1493 1.5493 0.0338 1.2707 0.0625
+#> 443: 92.8241 -5.9586 -0.1256 2.2811 -0.9651 0.4941 3.7563 0.3822 0.3350 0.1493 1.5491 0.0338 1.2704 0.0625
+#> 444: 92.8228 -5.9591 -0.1256 2.2812 -0.9651 0.4954 3.7566 0.3822 0.3349 0.1493 1.5488 0.0339 1.2703 0.0625
+#> 445: 92.8210 -5.9596 -0.1256 2.2813 -0.9652 0.4972 3.7573 0.3821 0.3348 0.1493 1.5484 0.0339 1.2702 0.0625
+#> 446: 92.8193 -5.9595 -0.1255 2.2815 -0.9652 0.4989 3.7551 0.3821 0.3348 0.1494 1.5482 0.0339 1.2708 0.0624
+#> 447: 92.8183 -5.9598 -0.1255 2.2817 -0.9652 0.5002 3.7548 0.3820 0.3347 0.1494 1.5478 0.0339 1.2710 0.0624
+#> 448: 92.8177 -5.9607 -0.1255 2.2818 -0.9653 0.5019 3.7585 0.3819 0.3347 0.1495 1.5475 0.0340 1.2711 0.0624
+#> 449: 92.8171 -5.9613 -0.1254 2.2819 -0.9654 0.5040 3.7592 0.3819 0.3347 0.1495 1.5474 0.0340 1.2711 0.0624
+#> 450: 92.8164 -5.9621 -0.1253 2.2821 -0.9655 0.5060 3.7632 0.3818 0.3346 0.1495 1.5470 0.0340 1.2704 0.0624
+#> 451: 92.8157 -5.9628 -0.1253 2.2822 -0.9655 0.5082 3.7655 0.3816 0.3346 0.1495 1.5469 0.0340 1.2699 0.0625
+#> 452: 92.8157 -5.9633 -0.1252 2.2824 -0.9656 0.5092 3.7657 0.3815 0.3346 0.1495 1.5468 0.0340 1.2691 0.0625
+#> 453: 92.8155 -5.9631 -0.1252 2.2823 -0.9657 0.5099 3.7646 0.3815 0.3347 0.1494 1.5470 0.0340 1.2684 0.0625
+#> 454: 92.8149 -5.9627 -0.1252 2.2823 -0.9656 0.5110 3.7623 0.3815 0.3347 0.1495 1.5470 0.0340 1.2678 0.0626
+#> 455: 92.8147 -5.9626 -0.1253 2.2822 -0.9656 0.5118 3.7610 0.3816 0.3347 0.1495 1.5471 0.0340 1.2675 0.0626
+#> 456: 92.8146 -5.9631 -0.1253 2.2821 -0.9657 0.5124 3.7612 0.3817 0.3348 0.1495 1.5473 0.0340 1.2684 0.0625
+#> 457: 92.8146 -5.9639 -0.1253 2.2820 -0.9658 0.5131 3.7636 0.3817 0.3347 0.1494 1.5471 0.0340 1.2683 0.0625
+#> 458: 92.8142 -5.9641 -0.1254 2.2818 -0.9658 0.5143 3.7637 0.3817 0.3347 0.1493 1.5472 0.0340 1.2679 0.0626
+#> 459: 92.8129 -5.9636 -0.1254 2.2818 -0.9660 0.5155 3.7609 0.3817 0.3347 0.1493 1.5474 0.0340 1.2692 0.0625
+#> 460: 92.8118 -5.9630 -0.1254 2.2817 -0.9660 0.5155 3.7563 0.3818 0.3347 0.1493 1.5476 0.0340 1.2703 0.0624
+#> 461: 92.8102 -5.9625 -0.1255 2.2816 -0.9661 0.5159 3.7525 0.3818 0.3347 0.1493 1.5478 0.0340 1.2711 0.0624
+#> 462: 92.8090 -5.9628 -0.1255 2.2814 -0.9661 0.5163 3.7520 0.3819 0.3347 0.1492 1.5481 0.0340 1.2708 0.0624
+#> 463: 92.8075 -5.9633 -0.1256 2.2813 -0.9660 0.5180 3.7534 0.3819 0.3347 0.1491 1.5484 0.0340 1.2705 0.0624
+#> 464: 92.8066 -5.9628 -0.1256 2.2812 -0.9659 0.5194 3.7507 0.3820 0.3347 0.1490 1.5485 0.0340 1.2702 0.0624
+#> 465: 92.8058 -5.9627 -0.1257 2.2811 -0.9658 0.5212 3.7506 0.3820 0.3347 0.1490 1.5484 0.0340 1.2696 0.0625
+#> 466: 92.8055 -5.9624 -0.1258 2.2808 -0.9656 0.5227 3.7510 0.3821 0.3347 0.1489 1.5487 0.0340 1.2704 0.0624
+#> 467: 92.8052 -5.9624 -0.1260 2.2805 -0.9656 0.5242 3.7518 0.3822 0.3346 0.1488 1.5488 0.0340 1.2715 0.0623
+#> 468: 92.8054 -5.9623 -0.1261 2.2803 -0.9654 0.5260 3.7545 0.3823 0.3346 0.1487 1.5493 0.0340 1.2730 0.0623
+#> 469: 92.8052 -5.9629 -0.1262 2.2803 -0.9654 0.5278 3.7617 0.3824 0.3346 0.1486 1.5495 0.0340 1.2737 0.0622
+#> 470: 92.8055 -5.9638 -0.1263 2.2802 -0.9653 0.5290 3.7667 0.3825 0.3347 0.1486 1.5494 0.0341 1.2729 0.0623
+#> 471: 92.8061 -5.9645 -0.1263 2.2801 -0.9653 0.5293 3.7702 0.3825 0.3347 0.1485 1.5494 0.0341 1.2724 0.0623
+#> 472: 92.8057 -5.9645 -0.1264 2.2800 -0.9653 0.5288 3.7699 0.3826 0.3347 0.1484 1.5495 0.0341 1.2728 0.0623
+#> 473: 92.8053 -5.9643 -0.1265 2.2799 -0.9652 0.5282 3.7701 0.3827 0.3347 0.1483 1.5494 0.0341 1.2721 0.0623
+#> 474: 92.8049 -5.9638 -0.1266 2.2798 -0.9653 0.5273 3.7676 0.3828 0.3347 0.1483 1.5495 0.0341 1.2722 0.0623
+#> 475: 92.8041 -5.9639 -0.1267 2.2796 -0.9654 0.5269 3.7668 0.3829 0.3347 0.1482 1.5495 0.0341 1.2721 0.0623
+#> 476: 92.8032 -5.9641 -0.1269 2.2794 -0.9653 0.5260 3.7681 0.3830 0.3347 0.1481 1.5496 0.0341 1.2716 0.0623
+#> 477: 92.8026 -5.9634 -0.1270 2.2792 -0.9653 0.5249 3.7647 0.3831 0.3347 0.1480 1.5500 0.0341 1.2716 0.0623
+#> 478: 92.8021 -5.9627 -0.1271 2.2789 -0.9653 0.5241 3.7606 0.3832 0.3346 0.1480 1.5500 0.0341 1.2718 0.0623
+#> 479: 92.8019 -5.9623 -0.1272 2.2787 -0.9654 0.5241 3.7581 0.3833 0.3345 0.1480 1.5502 0.0342 1.2714 0.0624
+#> 480: 92.8017 -5.9631 -0.1274 2.2784 -0.9654 0.5241 3.7606 0.3835 0.3344 0.1479 1.5503 0.0342 1.2711 0.0624
+#> 481: 92.8020 -5.9638 -0.1275 2.2781 -0.9654 0.5237 3.7659 0.3837 0.3343 0.1478 1.5508 0.0342 1.2720 0.0624
+#> 482: 92.8024 -5.9640 -0.1278 2.2777 -0.9654 0.5228 3.7668 0.3838 0.3342 0.1478 1.5512 0.0342 1.2729 0.0623
+#> 483: 92.8017 -5.9645 -0.1280 2.2773 -0.9654 0.5224 3.7676 0.3840 0.3341 0.1478 1.5515 0.0342 1.2741 0.0622
+#> 484: 92.8012 -5.9642 -0.1281 2.2771 -0.9653 0.5221 3.7649 0.3841 0.3340 0.1478 1.5521 0.0341 1.2747 0.0622
+#> 485: 92.8009 -5.9642 -0.1283 2.2769 -0.9653 0.5214 3.7635 0.3842 0.3339 0.1479 1.5523 0.0341 1.2752 0.0622
+#> 486: 92.8002 -5.9639 -0.1284 2.2767 -0.9652 0.5213 3.7609 0.3842 0.3339 0.1480 1.5523 0.0341 1.2760 0.0621
+#> 487: 92.7998 -5.9636 -0.1285 2.2767 -0.9652 0.5212 3.7603 0.3842 0.3339 0.1480 1.5525 0.0341 1.2762 0.0621
+#> 488: 92.7995 -5.9634 -0.1285 2.2766 -0.9652 0.5218 3.7592 0.3841 0.3339 0.1480 1.5530 0.0341 1.2773 0.0621
+#> 489: 92.7996 -5.9630 -0.1286 2.2765 -0.9653 0.5220 3.7578 0.3841 0.3339 0.1480 1.5532 0.0341 1.2778 0.0621
+#> 490: 92.8001 -5.9629 -0.1287 2.2764 -0.9652 0.5226 3.7573 0.3841 0.3339 0.1479 1.5533 0.0341 1.2788 0.0620
+#> 491: 92.8001 -5.9629 -0.1287 2.2762 -0.9651 0.5225 3.7568 0.3841 0.3338 0.1479 1.5533 0.0341 1.2790 0.0620
+#> 492: 92.8005 -5.9625 -0.1288 2.2761 -0.9651 0.5228 3.7544 0.3840 0.3339 0.1479 1.5536 0.0341 1.2797 0.0619
+#> 493: 92.8010 -5.9626 -0.1289 2.2759 -0.9651 0.5228 3.7544 0.3840 0.3339 0.1479 1.5537 0.0340 1.2795 0.0620
+#> 494: 92.8014 -5.9623 -0.1290 2.2757 -0.9651 0.5239 3.7523 0.3839 0.3340 0.1479 1.5540 0.0340 1.2790 0.0620
+#> 495: 92.8017 -5.9617 -0.1291 2.2755 -0.9652 0.5244 3.7491 0.3838 0.3341 0.1480 1.5540 0.0340 1.2787 0.0621
+#> 496: 92.8019 -5.9613 -0.1291 2.2754 -0.9652 0.5246 3.7459 0.3837 0.3341 0.1481 1.5539 0.0340 1.2802 0.0620
+#> 497: 92.8023 -5.9611 -0.1292 2.2753 -0.9653 0.5252 3.7447 0.3836 0.3340 0.1482 1.5539 0.0340 1.2814 0.0620
+#> 498: 92.8025 -5.9615 -0.1292 2.2752 -0.9653 0.5254 3.7446 0.3836 0.3339 0.1483 1.5539 0.0340 1.2825 0.0619
+#> 499: 92.8033 -5.9616 -0.1292 2.2751 -0.9654 0.5254 3.7447 0.3836 0.3338 0.1483 1.5538 0.0340 1.2834 0.0619
+#> 500: 92.8041 -5.9630 -0.1292 2.2752 -0.9655 0.5248 3.7529 0.3836 0.3337 0.1484 1.5538 0.0340 1.2841 0.0619
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[5]+THETA[5];
-#> rx_expr_12~exp(-(rx_expr_8));
-#> rx_expr_14~t*rx_expr_12;
-#> rx_expr_15~1+rx_expr_14;
-#> rx_expr_17~rx_expr_7-(rx_expr_8);
-#> rx_expr_19~exp(rx_expr_17);
-#> d/dt(parent)=-rx_expr_19*parent/(rx_expr_15);
-#> rx_expr_9~ETA[2]+THETA[2];
-#> rx_expr_11~exp(rx_expr_9);
-#> d/dt(A1)=-rx_expr_11*A1+rx_expr_19*parent*f_parent_to_A1/(rx_expr_15);
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_13~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_13+rx_expr_3;
-#> rx_hi_~rx_expr_13+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_10~parent*(rx_expr_2);
-#> rx_expr_16~rx_expr_10*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1);
-#> rx_r_=(Rx_pow_di(((rx_expr_4+rx_expr_16)*(rx_expr_0)+(rx_expr_4+rx_expr_16)*(rx_expr_2)*(rx_expr_1)),2)*Rx_pow_di(THETA[9],2)+Rx_pow_di(THETA[8],2))*(rx_expr_0)+(Rx_pow_di(THETA[7],2)*Rx_pow_di(((rx_expr_4+rx_expr_16)*(rx_expr_1)),2)+Rx_pow_di(THETA[6],2))*(rx_expr_2)*(rx_expr_1);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_alpha=THETA[4];
-#> log_beta=THETA[5];
-#> sigma_low_parent=THETA[6];
-#> rsd_high_parent=THETA[7];
-#> sigma_low_A1=THETA[8];
-#> rsd_high_A1=THETA[9];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_alpha=ETA[4];
-#> eta.log_beta=ETA[5];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_11;
-#> alpha=exp(rx_expr_7);
-#> beta=exp(rx_expr_8);
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.386 8.556
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_alpha |
+#> |.....................| log_beta |sigma_low_parent |rsd_high_parent |sigma_low_A1 |
+#> |.....................|rsd_high_A1 | o1 | o2 | o3 |
+#> |.....................| o4 | o5 |...........|...........|
+#> | 1| 504.82714 | 1.000 | -1.000 | -0.9114 | -0.8944 |
+#> |.....................| -0.8457 | -0.8687 | -0.8916 | -0.8687 |
+#> |.....................| -0.8916 | -0.8768 | -0.8745 | -0.8676 |
+#> |.....................| -0.8705 | -0.8704 |...........|...........|
+#> | U| 504.82714 | 93.12 | -5.303 | -0.9442 | -0.1065 |
+#> |.....................| 2.291 | 1.160 | 0.03005 | 1.160 |
+#> |.....................| 0.03005 | 0.7578 | 0.8738 | 1.213 |
+#> |.....................| 1.069 | 1.072 |...........|...........|
+#> | X| 504.82714 | 93.12 | 0.004975 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.160 | 0.03005 | 1.160 |
+#> |.....................| 0.03005 | 0.7578 | 0.8738 | 1.213 |
+#> |.....................| 1.069 | 1.072 |...........|...........|
+#> | G| Gill Diff. | 73.79 | 2.406 | 0.05615 | 0.2285 |
+#> |.....................| 0.009051 | -73.50 | -23.10 | 0.2441 |
+#> |.....................| -2.663 | 1.201 | 11.89 | -10.88 |
+#> |.....................| -9.982 | -10.81 |...........|...........|
+#> | 2| 4109.9562 | 0.3228 | -1.022 | -0.9119 | -0.8965 |
+#> |.....................| -0.8458 | -0.1941 | -0.6796 | -0.8709 |
+#> |.....................| -0.8672 | -0.8879 | -0.9836 | -0.7677 |
+#> |.....................| -0.7789 | -0.7712 |...........|...........|
+#> | U| 4109.9562 | 30.05 | -5.326 | -0.9447 | -0.1086 |
+#> |.....................| 2.291 | 1.551 | 0.03324 | 1.158 |
+#> |.....................| 0.03042 | 0.7495 | 0.7784 | 1.335 |
+#> |.....................| 1.167 | 1.178 |...........|...........|
+#> | X| 4109.9562 | 30.05 | 0.004866 | 0.2800 | 0.8971 |
+#> |.....................| 9.883 | 1.551 | 0.03324 | 1.158 |
+#> |.....................| 0.03042 | 0.7495 | 0.7784 | 1.335 |
+#> |.....................| 1.167 | 1.178 |...........|...........|
+#> | 3| 527.72868 | 0.9323 | -1.002 | -0.9115 | -0.8946 |
+#> |.....................| -0.8457 | -0.8012 | -0.8704 | -0.8689 |
+#> |.....................| -0.8892 | -0.8779 | -0.8854 | -0.8576 |
+#> |.....................| -0.8613 | -0.8605 |...........|...........|
+#> | U| 527.72868 | 86.81 | -5.306 | -0.9442 | -0.1067 |
+#> |.....................| 2.291 | 1.199 | 0.03037 | 1.159 |
+#> |.....................| 0.03009 | 0.7570 | 0.8642 | 1.226 |
+#> |.....................| 1.079 | 1.083 |...........|...........|
+#> | X| 527.72868 | 86.81 | 0.004964 | 0.2800 | 0.8988 |
+#> |.....................| 9.884 | 1.199 | 0.03037 | 1.159 |
+#> |.....................| 0.03009 | 0.7570 | 0.8642 | 1.226 |
+#> |.....................| 1.079 | 1.083 |...........|...........|
+#> | 4| 503.94655 | 0.9891 | -1.000 | -0.9114 | -0.8944 |
+#> |.....................| -0.8457 | -0.8578 | -0.8882 | -0.8687 |
+#> |.....................| -0.8912 | -0.8770 | -0.8762 | -0.8660 |
+#> |.....................| -0.8690 | -0.8688 |...........|...........|
+#> | U| 503.94655 | 92.10 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.166 | 0.03011 | 1.160 |
+#> |.....................| 0.03006 | 0.7577 | 0.8722 | 1.215 |
+#> |.....................| 1.070 | 1.074 |...........|...........|
+#> | X| 503.94655 | 92.10 | 0.004973 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.166 | 0.03011 | 1.160 |
+#> |.....................| 0.03006 | 0.7577 | 0.8722 | 1.215 |
+#> |.....................| 1.070 | 1.074 |...........|...........|
+#> | F| Forward Diff. | -83.20 | 2.270 | -0.2572 | 0.1460 |
+#> |.....................| -0.3233 | -71.29 | -24.25 | 0.7297 |
+#> |.....................| -2.130 | 1.329 | 9.332 | -11.82 |
+#> |.....................| -9.604 | -10.42 |...........|...........|
+#> | 5| 503.03407 | 1.000 | -1.001 | -0.9114 | -0.8944 |
+#> |.....................| -0.8456 | -0.8473 | -0.8847 | -0.8688 |
+#> |.....................| -0.8909 | -0.8772 | -0.8776 | -0.8642 |
+#> |.....................| -0.8676 | -0.8673 |...........|...........|
+#> | U| 503.03407 | 93.15 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.172 | 0.03016 | 1.159 |
+#> |.....................| 0.03007 | 0.7575 | 0.8710 | 1.217 |
+#> |.....................| 1.072 | 1.075 |...........|...........|
+#> | X| 503.03407 | 93.15 | 0.004971 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.172 | 0.03016 | 1.159 |
+#> |.....................| 0.03007 | 0.7575 | 0.8710 | 1.217 |
+#> |.....................| 1.072 | 1.075 |...........|...........|
+#> | F| Forward Diff. | 79.23 | 2.386 | 0.06830 | 0.2424 |
+#> |.....................| 0.02121 | -70.84 | -22.28 | -0.5289 |
+#> |.....................| -2.713 | 1.149 | 11.82 | -11.86 |
+#> |.....................| -9.567 | -10.47 |...........|...........|
+#> | 6| 502.12413 | 0.9895 | -1.001 | -0.9114 | -0.8945 |
+#> |.....................| -0.8456 | -0.8365 | -0.8812 | -0.8687 |
+#> |.....................| -0.8905 | -0.8774 | -0.8794 | -0.8624 |
+#> |.....................| -0.8662 | -0.8657 |...........|...........|
+#> | U| 502.12413 | 92.14 | -5.304 | -0.9442 | -0.1066 |
+#> |.....................| 2.291 | 1.178 | 0.03021 | 1.160 |
+#> |.....................| 0.03007 | 0.7574 | 0.8695 | 1.220 |
+#> |.....................| 1.073 | 1.077 |...........|...........|
+#> | X| 502.12413 | 92.14 | 0.004969 | 0.2801 | 0.8989 |
+#> |.....................| 9.884 | 1.178 | 0.03021 | 1.160 |
+#> |.....................| 0.03007 | 0.7574 | 0.8695 | 1.220 |
+#> |.....................| 1.073 | 1.077 |...........|...........|
+#> | F| Forward Diff. | -77.28 | 2.252 | -0.2503 | 0.1427 |
+#> |.....................| -0.3238 | -69.21 | -23.25 | 0.3943 |
+#> |.....................| -2.493 | 1.092 | 10.79 | -11.67 |
+#> |.....................| -9.485 | -10.25 |...........|...........|
+#> | 7| 501.24651 | 1.000 | -1.001 | -0.9114 | -0.8945 |
+#> |.....................| -0.8456 | -0.8257 | -0.8776 | -0.8688 |
+#> |.....................| -0.8901 | -0.8775 | -0.8811 | -0.8606 |
+#> |.....................| -0.8647 | -0.8641 |...........|...........|
+#> | U| 501.24651 | 93.15 | -5.305 | -0.9441 | -0.1067 |
+#> |.....................| 2.291 | 1.184 | 0.03026 | 1.160 |
+#> |.....................| 0.03008 | 0.7573 | 0.8680 | 1.222 |
+#> |.....................| 1.075 | 1.079 |...........|...........|
+#> | X| 501.24651 | 93.15 | 0.004968 | 0.2801 | 0.8988 |
+#> |.....................| 9.885 | 1.184 | 0.03026 | 1.160 |
+#> |.....................| 0.03008 | 0.7573 | 0.8680 | 1.222 |
+#> |.....................| 1.075 | 1.079 |...........|...........|
+#> | F| Forward Diff. | 78.96 | 2.363 | 0.07229 | 0.2390 |
+#> |.....................| 0.02239 | -67.81 | -20.97 | 0.1381 |
+#> |.....................| -2.125 | 1.379 | 9.797 | -11.70 |
+#> |.....................| -9.438 | -10.29 |...........|...........|
+#> | 8| 500.35160 | 0.9896 | -1.002 | -0.9114 | -0.8945 |
+#> |.....................| -0.8456 | -0.8148 | -0.8742 | -0.8688 |
+#> |.....................| -0.8898 | -0.8778 | -0.8827 | -0.8587 |
+#> |.....................| -0.8632 | -0.8625 |...........|...........|
+#> | U| 500.3516 | 92.15 | -5.305 | -0.9441 | -0.1067 |
+#> |.....................| 2.291 | 1.191 | 0.03032 | 1.159 |
+#> |.....................| 0.03008 | 0.7571 | 0.8666 | 1.224 |
+#> |.....................| 1.077 | 1.081 |...........|...........|
+#> | X| 500.3516 | 92.15 | 0.004966 | 0.2801 | 0.8988 |
+#> |.....................| 9.885 | 1.191 | 0.03032 | 1.159 |
+#> |.....................| 0.03008 | 0.7571 | 0.8666 | 1.224 |
+#> |.....................| 1.077 | 1.081 |...........|...........|
+#> | F| Forward Diff. | -75.23 | 2.232 | -0.2459 | 0.1501 |
+#> |.....................| -0.3253 | -66.87 | -22.19 | 0.4436 |
+#> |.....................| -2.150 | 0.9434 | 9.182 | -11.49 |
+#> |.....................| -9.350 | -10.07 |...........|...........|
+#> | 9| 499.45361 | 1.000 | -1.002 | -0.9113 | -0.8946 |
+#> |.....................| -0.8455 | -0.8036 | -0.8705 | -0.8689 |
+#> |.....................| -0.8894 | -0.8779 | -0.8842 | -0.8568 |
+#> |.....................| -0.8616 | -0.8608 |...........|...........|
+#> | U| 499.45361 | 93.12 | -5.306 | -0.9441 | -0.1067 |
+#> |.....................| 2.291 | 1.197 | 0.03037 | 1.159 |
+#> |.....................| 0.03009 | 0.7570 | 0.8653 | 1.226 |
+#> |.....................| 1.078 | 1.082 |...........|...........|
+#> | X| 499.45361 | 93.12 | 0.004964 | 0.2801 | 0.8988 |
+#> |.....................| 9.885 | 1.197 | 0.03037 | 1.159 |
+#> |.....................| 0.03009 | 0.7570 | 0.8653 | 1.226 |
+#> |.....................| 1.078 | 1.082 |...........|...........|
+#> | F| Forward Diff. | 73.21 | 2.337 | 0.06584 | 0.2472 |
+#> |.....................| 0.008903 | -65.96 | -20.21 | -0.3457 |
+#> |.....................| -2.677 | 1.048 | 11.29 | -11.53 |
+#> |.....................| -9.311 | -10.11 |...........|...........|
+#> | 10| 498.59105 | 0.9896 | -1.003 | -0.9113 | -0.8946 |
+#> |.....................| -0.8455 | -0.7924 | -0.8671 | -0.8688 |
+#> |.....................| -0.8890 | -0.8781 | -0.8861 | -0.8548 |
+#> |.....................| -0.8600 | -0.8591 |...........|...........|
+#> | U| 498.59105 | 92.15 | -5.306 | -0.9441 | -0.1068 |
+#> |.....................| 2.291 | 1.204 | 0.03042 | 1.159 |
+#> |.....................| 0.03009 | 0.7568 | 0.8636 | 1.229 |
+#> |.....................| 1.080 | 1.084 |...........|...........|
+#> | X| 498.59105 | 92.15 | 0.004962 | 0.2801 | 0.8987 |
+#> |.....................| 9.885 | 1.204 | 0.03042 | 1.159 |
+#> |.....................| 0.03009 | 0.7568 | 0.8636 | 1.229 |
+#> |.....................| 1.080 | 1.084 |...........|...........|
+#> | F| Forward Diff. | -74.43 | 2.211 | -0.2431 | 0.1502 |
+#> |.....................| -0.3305 | -64.40 | -21.08 | 0.5329 |
+#> |.....................| -2.487 | 0.9319 | 8.926 | -11.33 |
+#> |.....................| -9.217 | -9.888 |...........|...........|
+#> | 11| 497.71590 | 1.000 | -1.003 | -0.9113 | -0.8946 |
+#> |.....................| -0.8455 | -0.7811 | -0.8634 | -0.8689 |
+#> |.....................| -0.8885 | -0.8783 | -0.8877 | -0.8529 |
+#> |.....................| -0.8584 | -0.8573 |...........|...........|
+#> | U| 497.7159 | 93.11 | -5.306 | -0.9441 | -0.1068 |
+#> |.....................| 2.291 | 1.210 | 0.03048 | 1.159 |
+#> |.....................| 0.03010 | 0.7567 | 0.8622 | 1.231 |
+#> |.....................| 1.082 | 1.086 |...........|...........|
+#> | X| 497.7159 | 93.11 | 0.004960 | 0.2801 | 0.8987 |
+#> |.....................| 9.886 | 1.210 | 0.03048 | 1.159 |
+#> |.....................| 0.03010 | 0.7567 | 0.8622 | 1.231 |
+#> |.....................| 1.082 | 1.086 |...........|...........|
+#> | F| Forward Diff. | 71.79 | 2.312 | 0.07434 | 0.2557 |
+#> |.....................| 0.006614 | -63.04 | -18.95 | 0.3164 |
+#> |.....................| -2.117 | 1.342 | 9.274 | -11.35 |
+#> |.....................| -9.172 | -9.924 |...........|...........|
+#> | 12| 496.86264 | 0.9898 | -1.003 | -0.9113 | -0.8947 |
+#> |.....................| -0.8455 | -0.7696 | -0.8599 | -0.8690 |
+#> |.....................| -0.8881 | -0.8785 | -0.8894 | -0.8508 |
+#> |.....................| -0.8567 | -0.8555 |...........|...........|
+#> | U| 496.86264 | 92.17 | -5.307 | -0.9441 | -0.1068 |
+#> |.....................| 2.291 | 1.217 | 0.03053 | 1.159 |
+#> |.....................| 0.03011 | 0.7565 | 0.8607 | 1.234 |
+#> |.....................| 1.084 | 1.088 |...........|...........|
+#> | X| 496.86264 | 92.17 | 0.004958 | 0.2801 | 0.8987 |
+#> |.....................| 9.886 | 1.217 | 0.03053 | 1.159 |
+#> |.....................| 0.03011 | 0.7565 | 0.8607 | 1.234 |
+#> |.....................| 1.084 | 1.088 |...........|...........|
+#> | F| Forward Diff. | -71.54 | 2.190 | -0.2371 | 0.1482 |
+#> |.....................| -0.3369 | -61.67 | -19.90 | 0.9419 |
+#> |.....................| -2.139 | 1.041 | 7.036 | -11.13 |
+#> |.....................| -9.064 | -9.692 |...........|...........|
+#> | 13| 495.99097 | 0.9997 | -1.004 | -0.9113 | -0.8947 |
+#> |.....................| -0.8454 | -0.7580 | -0.8562 | -0.8692 |
+#> |.....................| -0.8877 | -0.8787 | -0.8907 | -0.8487 |
+#> |.....................| -0.8550 | -0.8537 |...........|...........|
+#> | U| 495.99097 | 93.09 | -5.307 | -0.9441 | -0.1069 |
+#> |.....................| 2.291 | 1.224 | 0.03059 | 1.159 |
+#> |.....................| 0.03011 | 0.7564 | 0.8596 | 1.236 |
+#> |.....................| 1.085 | 1.090 |...........|...........|
+#> | X| 495.99097 | 93.09 | 0.004956 | 0.2801 | 0.8987 |
+#> |.....................| 9.886 | 1.224 | 0.03059 | 1.159 |
+#> |.....................| 0.03011 | 0.7564 | 0.8596 | 1.236 |
+#> |.....................| 1.085 | 1.090 |...........|...........|
+#> | F| Forward Diff. | 67.48 | 2.282 | 0.05510 | 0.2442 |
+#> |.....................| -0.01700 | -60.62 | -17.93 | 0.4372 |
+#> |.....................| -2.100 | 1.212 | 9.042 | -11.17 |
+#> |.....................| -9.025 | -9.723 |...........|...........|
+#> | 14| 495.15472 | 0.9899 | -1.004 | -0.9113 | -0.8948 |
+#> |.....................| -0.8454 | -0.7463 | -0.8527 | -0.8693 |
+#> |.....................| -0.8873 | -0.8789 | -0.8924 | -0.8465 |
+#> |.....................| -0.8533 | -0.8518 |...........|...........|
+#> | U| 495.15472 | 92.18 | -5.308 | -0.9441 | -0.1069 |
+#> |.....................| 2.291 | 1.231 | 0.03064 | 1.159 |
+#> |.....................| 0.03012 | 0.7562 | 0.8581 | 1.239 |
+#> |.....................| 1.087 | 1.092 |...........|...........|
+#> | X| 495.15472 | 92.18 | 0.004954 | 0.2801 | 0.8986 |
+#> |.....................| 9.886 | 1.231 | 0.03064 | 1.159 |
+#> |.....................| 0.03012 | 0.7562 | 0.8581 | 1.239 |
+#> |.....................| 1.087 | 1.092 |...........|...........|
+#> | F| Forward Diff. | -68.93 | 2.171 | -0.2257 | 0.1488 |
+#> |.....................| -0.3348 | -59.34 | -18.81 | 1.070 |
+#> |.....................| -2.082 | 1.016 | 8.208 | -10.96 |
+#> |.....................| -8.930 | -9.498 |...........|...........|
+#> | 15| 494.30065 | 0.9995 | -1.005 | -0.9112 | -0.8948 |
+#> |.....................| -0.8453 | -0.7344 | -0.8490 | -0.8695 |
+#> |.....................| -0.8869 | -0.8792 | -0.8941 | -0.8443 |
+#> |.....................| -0.8515 | -0.8499 |...........|...........|
+#> | U| 494.30065 | 93.07 | -5.308 | -0.9440 | -0.1069 |
+#> |.....................| 2.291 | 1.237 | 0.03069 | 1.159 |
+#> |.....................| 0.03013 | 0.7561 | 0.8567 | 1.242 |
+#> |.....................| 1.089 | 1.094 |...........|...........|
+#> | X| 494.30065 | 93.07 | 0.004951 | 0.2801 | 0.8986 |
+#> |.....................| 9.887 | 1.237 | 0.03069 | 1.159 |
+#> |.....................| 0.03013 | 0.7561 | 0.8567 | 1.242 |
+#> |.....................| 1.089 | 1.094 |...........|...........|
+#> | F| Forward Diff. | 65.20 | 2.260 | 0.06851 | 0.2416 |
+#> |.....................| -0.02143 | -58.42 | -17.03 | 0.3665 |
+#> |.....................| -2.202 | 1.112 | 7.377 | -10.96 |
+#> |.....................| -8.866 | -9.510 |...........|...........|
+#> | 16| 493.48608 | 0.9901 | -1.005 | -0.9112 | -0.8948 |
+#> |.....................| -0.8453 | -0.7225 | -0.8455 | -0.8696 |
+#> |.....................| -0.8865 | -0.8794 | -0.8956 | -0.8421 |
+#> |.....................| -0.8496 | -0.8479 |...........|...........|
+#> | U| 493.48608 | 92.19 | -5.309 | -0.9440 | -0.1070 |
+#> |.....................| 2.291 | 1.244 | 0.03075 | 1.159 |
+#> |.....................| 0.03013 | 0.7559 | 0.8553 | 1.244 |
+#> |.....................| 1.091 | 1.096 |...........|...........|
+#> | X| 493.48608 | 92.19 | 0.004949 | 0.2801 | 0.8985 |
+#> |.....................| 9.887 | 1.244 | 0.03075 | 1.159 |
+#> |.....................| 0.03013 | 0.7559 | 0.8553 | 1.244 |
+#> |.....................| 1.091 | 1.096 |...........|...........|
+#> | F| Forward Diff. | -66.94 | 2.152 | -0.2367 | 0.1452 |
+#> |.....................| -0.3412 | -57.13 | -17.84 | 1.057 |
+#> |.....................| -2.129 | 0.9540 | 6.557 | -10.77 |
+#> |.....................| -8.770 | -9.285 |...........|...........|
+#> | 17| 492.64670 | 0.9993 | -1.006 | -0.9112 | -0.8949 |
+#> |.....................| -0.8453 | -0.7105 | -0.8419 | -0.8698 |
+#> |.....................| -0.8860 | -0.8796 | -0.8969 | -0.8398 |
+#> |.....................| -0.8478 | -0.8460 |...........|...........|
+#> | U| 492.6467 | 93.06 | -5.309 | -0.9440 | -0.1070 |
+#> |.....................| 2.291 | 1.251 | 0.03080 | 1.159 |
+#> |.....................| 0.03014 | 0.7557 | 0.8542 | 1.247 |
+#> |.....................| 1.093 | 1.098 |...........|...........|
+#> | X| 492.6467 | 93.06 | 0.004947 | 0.2801 | 0.8985 |
+#> |.....................| 9.888 | 1.251 | 0.03080 | 1.159 |
+#> |.....................| 0.03014 | 0.7557 | 0.8542 | 1.247 |
+#> |.....................| 1.093 | 1.098 |...........|...........|
+#> | F| Forward Diff. | 62.51 | 2.244 | 0.07930 | 0.2506 |
+#> |.....................| -0.02305 | -56.21 | -16.10 | 0.4420 |
+#> |.....................| -2.202 | 1.071 | 7.160 | -10.75 |
+#> |.....................| -8.705 | -9.292 |...........|...........|
+#> | 18| 491.85024 | 0.9902 | -1.006 | -0.9112 | -0.8949 |
+#> |.....................| -0.8453 | -0.6983 | -0.8384 | -0.8699 |
+#> |.....................| -0.8855 | -0.8798 | -0.8984 | -0.8374 |
+#> |.....................| -0.8459 | -0.8439 |...........|...........|
+#> | U| 491.85024 | 92.21 | -5.310 | -0.9440 | -0.1071 |
+#> |.....................| 2.291 | 1.258 | 0.03085 | 1.159 |
+#> |.....................| 0.03015 | 0.7556 | 0.8529 | 1.250 |
+#> |.....................| 1.095 | 1.100 |...........|...........|
+#> | X| 491.85024 | 92.21 | 0.004944 | 0.2801 | 0.8985 |
+#> |.....................| 9.888 | 1.258 | 0.03085 | 1.159 |
+#> |.....................| 0.03015 | 0.7556 | 0.8529 | 1.250 |
+#> |.....................| 1.095 | 1.100 |...........|...........|
+#> | F| Forward Diff. | -64.39 | 2.132 | -0.2231 | 0.1507 |
+#> |.....................| -0.3455 | -54.91 | -16.84 | 1.107 |
+#> |.....................| -2.130 | 0.9153 | 6.361 | -10.56 |
+#> |.....................| -8.604 | -9.065 |...........|...........|
+#> | 19| 491.03181 | 0.9992 | -1.007 | -0.9112 | -0.8950 |
+#> |.....................| -0.8452 | -0.6860 | -0.8347 | -0.8702 |
+#> |.....................| -0.8850 | -0.8800 | -0.8997 | -0.8350 |
+#> |.....................| -0.8439 | -0.8419 |...........|...........|
+#> | U| 491.03181 | 93.04 | -5.310 | -0.9440 | -0.1071 |
+#> |.....................| 2.291 | 1.265 | 0.03091 | 1.159 |
+#> |.....................| 0.03015 | 0.7554 | 0.8517 | 1.253 |
+#> |.....................| 1.097 | 1.103 |...........|...........|
+#> | X| 491.03181 | 93.04 | 0.004942 | 0.2801 | 0.8984 |
+#> |.....................| 9.888 | 1.265 | 0.03091 | 1.159 |
+#> |.....................| 0.03015 | 0.7554 | 0.8517 | 1.253 |
+#> |.....................| 1.097 | 1.103 |...........|...........|
+#> | F| Forward Diff. | 59.97 | 2.217 | 0.06954 | 0.2512 |
+#> |.....................| -0.03854 | -54.10 | -15.21 | 0.3955 |
+#> |.....................| -2.336 | 1.047 | 8.162 | -10.81 |
+#> |.....................| -8.706 | -9.233 |...........|...........|
+#> | 20| 490.24998 | 0.9904 | -1.007 | -0.9112 | -0.8950 |
+#> |.....................| -0.8452 | -0.6737 | -0.8313 | -0.8703 |
+#> |.....................| -0.8845 | -0.8803 | -0.9015 | -0.8325 |
+#> |.....................| -0.8419 | -0.8397 |...........|...........|
+#> | U| 490.24998 | 92.22 | -5.311 | -0.9440 | -0.1072 |
+#> |.....................| 2.291 | 1.273 | 0.03096 | 1.159 |
+#> |.....................| 0.03016 | 0.7552 | 0.8502 | 1.256 |
+#> |.....................| 1.099 | 1.105 |...........|...........|
+#> | X| 490.24998 | 92.22 | 0.004939 | 0.2801 | 0.8984 |
+#> |.....................| 9.889 | 1.273 | 0.03096 | 1.159 |
+#> |.....................| 0.03016 | 0.7552 | 0.8502 | 1.256 |
+#> |.....................| 1.099 | 1.105 |...........|...........|
+#> | F| Forward Diff. | -61.40 | 2.114 | -0.2172 | 0.1580 |
+#> |.....................| -0.3477 | -53.15 | -16.02 | 0.7982 |
+#> |.....................| -2.483 | 0.7215 | 9.240 | -10.34 |
+#> |.....................| -8.435 | -8.843 |...........|...........|
+#> | 21| 489.45580 | 0.9991 | -1.008 | -0.9111 | -0.8951 |
+#> |.....................| -0.8451 | -0.6614 | -0.8278 | -0.8705 |
+#> |.....................| -0.8839 | -0.8804 | -0.9038 | -0.8300 |
+#> |.....................| -0.8398 | -0.8376 |...........|...........|
+#> | U| 489.4558 | 93.03 | -5.311 | -0.9439 | -0.1072 |
+#> |.....................| 2.291 | 1.280 | 0.03101 | 1.159 |
+#> |.....................| 0.03017 | 0.7551 | 0.8482 | 1.259 |
+#> |.....................| 1.102 | 1.107 |...........|...........|
+#> | X| 489.4558 | 93.03 | 0.004937 | 0.2801 | 0.8983 |
+#> |.....................| 9.889 | 1.280 | 0.03101 | 1.159 |
+#> |.....................| 0.03017 | 0.7551 | 0.8482 | 1.259 |
+#> |.....................| 1.102 | 1.107 |...........|...........|
+#> | F| Forward Diff. | 58.20 | 2.191 | 0.07193 | 0.2543 |
+#> |.....................| -0.04201 | -51.69 | -14.22 | 0.6968 |
+#> |.....................| -2.088 | 1.024 | 8.024 | -10.34 |
+#> |.....................| -8.364 | -8.845 |...........|...........|
+#> | 22| 488.71859 | 0.9903 | -1.008 | -0.9111 | -0.8951 |
+#> |.....................| -0.8451 | -0.6491 | -0.8245 | -0.8707 |
+#> |.....................| -0.8833 | -0.8807 | -0.9059 | -0.8275 |
+#> |.....................| -0.8378 | -0.8354 |...........|...........|
+#> | U| 488.71859 | 92.21 | -5.312 | -0.9439 | -0.1073 |
+#> |.....................| 2.291 | 1.287 | 0.03106 | 1.158 |
+#> |.....................| 0.03018 | 0.7549 | 0.8463 | 1.262 |
+#> |.....................| 1.104 | 1.110 |...........|...........|
+#> | X| 488.71859 | 92.21 | 0.004934 | 0.2801 | 0.8983 |
+#> |.....................| 9.890 | 1.287 | 0.03106 | 1.158 |
+#> |.....................| 0.03018 | 0.7549 | 0.8463 | 1.262 |
+#> |.....................| 1.104 | 1.110 |...........|...........|
+#> | F| Forward Diff. | -62.72 | 2.087 | -0.2158 | 0.1536 |
+#> |.....................| -0.3560 | -50.59 | -14.96 | 1.289 |
+#> |.....................| -2.066 | 0.8753 | 7.259 | -10.12 |
+#> |.....................| -8.247 | -8.604 |...........|...........|
+#> | 23| 487.91801 | 0.9987 | -1.009 | -0.9111 | -0.8952 |
+#> |.....................| -0.8450 | -0.6366 | -0.8210 | -0.8711 |
+#> |.....................| -0.8828 | -0.8809 | -0.9078 | -0.8248 |
+#> |.....................| -0.8356 | -0.8332 |...........|...........|
+#> | U| 487.91801 | 93.00 | -5.312 | -0.9439 | -0.1073 |
+#> |.....................| 2.292 | 1.294 | 0.03112 | 1.158 |
+#> |.....................| 0.03019 | 0.7547 | 0.8446 | 1.265 |
+#> |.....................| 1.106 | 1.112 |...........|...........|
+#> | X| 487.91801 | 93.00 | 0.004931 | 0.2801 | 0.8982 |
+#> |.....................| 9.890 | 1.294 | 0.03112 | 1.158 |
+#> |.....................| 0.03019 | 0.7547 | 0.8446 | 1.265 |
+#> |.....................| 1.106 | 1.112 |...........|...........|
+#> | F| Forward Diff. | 52.73 | 2.162 | 0.07610 | 0.2481 |
+#> |.....................| -0.05835 | -50.28 | -13.63 | 0.1991 |
+#> |.....................| -2.681 | 0.6961 | 9.479 | -10.12 |
+#> |.....................| -8.180 | -8.607 |...........|...........|
+#> | 24| 487.19380 | 0.9906 | -1.009 | -0.9111 | -0.8952 |
+#> |.....................| -0.8450 | -0.6240 | -0.8177 | -0.8712 |
+#> |.....................| -0.8820 | -0.8811 | -0.9103 | -0.8222 |
+#> |.....................| -0.8335 | -0.8310 |...........|...........|
+#> | U| 487.1938 | 92.24 | -5.313 | -0.9439 | -0.1074 |
+#> |.....................| 2.292 | 1.301 | 0.03116 | 1.158 |
+#> |.....................| 0.03020 | 0.7546 | 0.8424 | 1.269 |
+#> |.....................| 1.108 | 1.114 |...........|...........|
+#> | X| 487.1938 | 92.24 | 0.004929 | 0.2801 | 0.8982 |
+#> |.....................| 9.891 | 1.301 | 0.03116 | 1.158 |
+#> |.....................| 0.03020 | 0.7546 | 0.8424 | 1.269 |
+#> |.....................| 1.108 | 1.114 |...........|...........|
+#> | F| Forward Diff. | -58.70 | 2.065 | -0.2024 | 0.1592 |
+#> |.....................| -0.3563 | -48.58 | -14.05 | 1.280 |
+#> |.....................| -2.114 | 0.8980 | 5.535 | -9.882 |
+#> |.....................| -8.046 | -8.364 |...........|...........|
+#> | 25| 486.45861 | 0.9990 | -1.010 | -0.9111 | -0.8953 |
+#> |.....................| -0.8449 | -0.6115 | -0.8144 | -0.8715 |
+#> |.....................| -0.8813 | -0.8813 | -0.9121 | -0.8195 |
+#> |.....................| -0.8313 | -0.8287 |...........|...........|
+#> | U| 486.45861 | 93.03 | -5.313 | -0.9439 | -0.1074 |
+#> |.....................| 2.292 | 1.309 | 0.03121 | 1.158 |
+#> |.....................| 0.03021 | 0.7545 | 0.8409 | 1.272 |
+#> |.....................| 1.111 | 1.117 |...........|...........|
+#> | X| 486.45861 | 93.03 | 0.004926 | 0.2801 | 0.8981 |
+#> |.....................| 9.892 | 1.309 | 0.03121 | 1.158 |
+#> |.....................| 0.03021 | 0.7545 | 0.8409 | 1.272 |
+#> |.....................| 1.111 | 1.117 |...........|...........|
+#> | F| Forward Diff. | 56.64 | 2.141 | 0.09518 | 0.2574 |
+#> |.....................| -0.04938 | -48.45 | -12.81 | 0.1110 |
+#> |.....................| -2.819 | 0.7463 | 7.804 | -9.858 |
+#> |.....................| -7.976 | -8.366 |...........|...........|
+#> | 26| 485.70463 | 0.9912 | -1.011 | -0.9111 | -0.8954 |
+#> |.....................| -0.8448 | -0.5987 | -0.8113 | -0.8717 |
+#> |.....................| -0.8805 | -0.8815 | -0.9139 | -0.8166 |
+#> |.....................| -0.8290 | -0.8264 |...........|...........|
+#> | U| 485.70463 | 92.30 | -5.314 | -0.9439 | -0.1075 |
+#> |.....................| 2.292 | 1.316 | 0.03126 | 1.158 |
+#> |.....................| 0.03022 | 0.7543 | 0.8393 | 1.275 |
+#> |.....................| 1.113 | 1.119 |...........|...........|
+#> | X| 485.70463 | 92.30 | 0.004923 | 0.2801 | 0.8981 |
+#> |.....................| 9.892 | 1.316 | 0.03126 | 1.158 |
+#> |.....................| 0.03022 | 0.7543 | 0.8393 | 1.275 |
+#> |.....................| 1.113 | 1.119 |...........|...........|
+#> | F| Forward Diff. | -49.75 | 2.049 | -0.1896 | 0.1657 |
+#> |.....................| -0.3394 | -47.06 | -13.27 | 0.8968 |
+#> |.....................| -2.558 | 0.5259 | 7.006 | -9.655 |
+#> |.....................| -7.860 | -8.128 |...........|...........|
+#> | 27| 485.03383 | 0.9993 | -1.011 | -0.9111 | -0.8954 |
+#> |.....................| -0.8447 | -0.5860 | -0.8081 | -0.8719 |
+#> |.....................| -0.8796 | -0.8816 | -0.9160 | -0.8138 |
+#> |.....................| -0.8267 | -0.8240 |...........|...........|
+#> | U| 485.03383 | 93.05 | -5.315 | -0.9439 | -0.1076 |
+#> |.....................| 2.292 | 1.323 | 0.03131 | 1.158 |
+#> |.....................| 0.03024 | 0.7542 | 0.8375 | 1.279 |
+#> |.....................| 1.116 | 1.122 |...........|...........|
+#> | X| 485.03383 | 93.05 | 0.004920 | 0.2801 | 0.8980 |
+#> |.....................| 9.893 | 1.323 | 0.03131 | 1.158 |
+#> |.....................| 0.03024 | 0.7542 | 0.8375 | 1.279 |
+#> |.....................| 1.116 | 1.122 |...........|...........|
+#> | F| Forward Diff. | 59.36 | 2.117 | 0.1128 | 0.2587 |
+#> |.....................| -0.03694 | -45.49 | -11.65 | 0.8714 |
+#> |.....................| -2.196 | 0.9711 | 7.208 | -9.629 |
+#> |.....................| -7.785 | -8.123 |...........|...........|
+#> | 28| 484.30050 | 0.9913 | -1.012 | -0.9111 | -0.8955 |
+#> |.....................| -0.8447 | -0.5733 | -0.8052 | -0.8723 |
+#> |.....................| -0.8788 | -0.8818 | -0.9181 | -0.8109 |
+#> |.....................| -0.8243 | -0.8216 |...........|...........|
+#> | U| 484.3005 | 92.30 | -5.315 | -0.9439 | -0.1077 |
+#> |.....................| 2.292 | 1.331 | 0.03135 | 1.157 |
+#> |.....................| 0.03025 | 0.7541 | 0.8357 | 1.282 |
+#> |.....................| 1.118 | 1.124 |...........|...........|
+#> | X| 484.3005 | 92.30 | 0.004916 | 0.2801 | 0.8979 |
+#> |.....................| 9.894 | 1.331 | 0.03135 | 1.157 |
+#> |.....................| 0.03025 | 0.7541 | 0.8357 | 1.282 |
+#> |.....................| 1.118 | 1.124 |...........|...........|
+#> | F| Forward Diff. | -49.13 | 2.024 | -0.1788 | 0.1668 |
+#> |.....................| -0.3408 | -44.74 | -12.30 | 1.348 |
+#> |.....................| -2.137 | 0.7757 | 5.010 | -9.393 |
+#> |.....................| -7.651 | -7.866 |...........|...........|
+#> | 29| 483.61888 | 0.9988 | -1.013 | -0.9110 | -0.8956 |
+#> |.....................| -0.8446 | -0.5603 | -0.8022 | -0.8729 |
+#> |.....................| -0.8781 | -0.8821 | -0.9194 | -0.8078 |
+#> |.....................| -0.8218 | -0.8191 |...........|...........|
+#> | U| 483.61888 | 93.00 | -5.316 | -0.9438 | -0.1077 |
+#> |.....................| 2.292 | 1.338 | 0.03140 | 1.157 |
+#> |.....................| 0.03026 | 0.7539 | 0.8345 | 1.286 |
+#> |.....................| 1.121 | 1.127 |...........|...........|
+#> | X| 483.61888 | 93.00 | 0.004913 | 0.2801 | 0.8979 |
+#> |.....................| 9.895 | 1.338 | 0.03140 | 1.157 |
+#> |.....................| 0.03026 | 0.7539 | 0.8345 | 1.286 |
+#> |.....................| 1.121 | 1.127 |...........|...........|
+#> | F| Forward Diff. | 51.77 | 2.082 | 0.08733 | 0.2462 |
+#> |.....................| -0.07383 | -44.60 | -11.22 | 0.3023 |
+#> |.....................| -2.722 | 0.5489 | 8.672 | -9.371 |
+#> |.....................| -7.562 | -7.848 |...........|...........|
+#> | 30| 482.91165 | 0.9915 | -1.013 | -0.9110 | -0.8957 |
+#> |.....................| -0.8445 | -0.5473 | -0.7995 | -0.8732 |
+#> |.....................| -0.8770 | -0.8822 | -0.9219 | -0.8047 |
+#> |.....................| -0.8192 | -0.8165 |...........|...........|
+#> | U| 482.91165 | 92.33 | -5.317 | -0.9438 | -0.1078 |
+#> |.....................| 2.292 | 1.346 | 0.03144 | 1.157 |
+#> |.....................| 0.03027 | 0.7538 | 0.8323 | 1.290 |
+#> |.....................| 1.124 | 1.130 |...........|...........|
+#> | X| 482.91165 | 92.33 | 0.004909 | 0.2801 | 0.8978 |
+#> |.....................| 9.895 | 1.346 | 0.03144 | 1.157 |
+#> |.....................| 0.03027 | 0.7538 | 0.8323 | 1.290 |
+#> |.....................| 1.124 | 1.130 |...........|...........|
+#> | F| Forward Diff. | -45.50 | 2.003 | -0.1660 | 0.1702 |
+#> |.....................| -0.3374 | -43.33 | -11.63 | 0.9930 |
+#> |.....................| -2.511 | 0.4656 | 7.949 | -9.128 |
+#> |.....................| -7.427 | -7.608 |...........|...........|
+#> | 31| 482.28997 | 0.9991 | -1.014 | -0.9110 | -0.8957 |
+#> |.....................| -0.8444 | -0.5346 | -0.7968 | -0.8735 |
+#> |.....................| -0.8759 | -0.8822 | -0.9253 | -0.8017 |
+#> |.....................| -0.8168 | -0.8141 |...........|...........|
+#> | U| 482.28997 | 93.03 | -5.317 | -0.9438 | -0.1079 |
+#> |.....................| 2.292 | 1.353 | 0.03148 | 1.157 |
+#> |.....................| 0.03029 | 0.7538 | 0.8294 | 1.293 |
+#> |.....................| 1.126 | 1.132 |...........|...........|
+#> | X| 482.28997 | 93.03 | 0.004906 | 0.2801 | 0.8977 |
+#> |.....................| 9.896 | 1.353 | 0.03148 | 1.157 |
+#> |.....................| 0.03029 | 0.7538 | 0.8294 | 1.293 |
+#> |.....................| 1.126 | 1.132 |...........|...........|
+#> | F| Forward Diff. | 55.95 | 2.054 | 0.1106 | 0.2465 |
+#> |.....................| -0.05340 | -42.18 | -10.21 | 0.8261 |
+#> |.....................| -2.234 | 0.9104 | 5.096 | -9.114 |
+#> |.....................| -7.334 | -7.590 |...........|...........|
+#> | 32| 481.60550 | 0.9915 | -1.015 | -0.9110 | -0.8958 |
+#> |.....................| -0.8443 | -0.5217 | -0.7945 | -0.8740 |
+#> |.....................| -0.8749 | -0.8824 | -0.9274 | -0.7984 |
+#> |.....................| -0.8142 | -0.8115 |...........|...........|
+#> | U| 481.6055 | 92.33 | -5.318 | -0.9438 | -0.1080 |
+#> |.....................| 2.292 | 1.361 | 0.03151 | 1.156 |
+#> |.....................| 0.03031 | 0.7536 | 0.8276 | 1.297 |
+#> |.....................| 1.129 | 1.135 |...........|...........|
+#> | X| 481.6055 | 92.33 | 0.004902 | 0.2801 | 0.8977 |
+#> |.....................| 9.897 | 1.361 | 0.03151 | 1.156 |
+#> |.....................| 0.03031 | 0.7536 | 0.8276 | 1.297 |
+#> |.....................| 1.129 | 1.135 |...........|...........|
+#> | F| Forward Diff. | -45.82 | 1.973 | -0.1624 | 0.1674 |
+#> |.....................| -0.3387 | -41.15 | -10.74 | 1.410 |
+#> |.....................| -2.130 | 0.6088 | 4.422 | -8.852 |
+#> |.....................| -7.186 | -7.335 |...........|...........|
+#> | 33| 480.97343 | 0.9986 | -1.016 | -0.9110 | -0.8959 |
+#> |.....................| -0.8442 | -0.5084 | -0.7922 | -0.8748 |
+#> |.....................| -0.8740 | -0.8826 | -0.9278 | -0.7950 |
+#> |.....................| -0.8114 | -0.8088 |...........|...........|
+#> | U| 480.97343 | 92.98 | -5.319 | -0.9438 | -0.1081 |
+#> |.....................| 2.292 | 1.368 | 0.03155 | 1.156 |
+#> |.....................| 0.03032 | 0.7534 | 0.8272 | 1.301 |
+#> |.....................| 1.132 | 1.138 |...........|...........|
+#> | X| 480.97343 | 92.98 | 0.004897 | 0.2801 | 0.8976 |
+#> |.....................| 9.898 | 1.368 | 0.03155 | 1.156 |
+#> |.....................| 0.03032 | 0.7534 | 0.8272 | 1.301 |
+#> |.....................| 1.132 | 1.138 |...........|...........|
+#> | F| Forward Diff. | 47.76 | 2.024 | 0.09167 | 0.2404 |
+#> |.....................| -0.07393 | -40.22 | -9.470 | 1.031 |
+#> |.....................| -2.098 | 0.8752 | 6.346 | -8.797 |
+#> |.....................| -7.089 | -7.296 |...........|...........|
+#> | 34| 480.33235 | 0.9916 | -1.017 | -0.9110 | -0.8960 |
+#> |.....................| -0.8441 | -0.4952 | -0.7903 | -0.8757 |
+#> |.....................| -0.8731 | -0.8830 | -0.9294 | -0.7914 |
+#> |.....................| -0.8086 | -0.8060 |...........|...........|
+#> | U| 480.33235 | 92.33 | -5.320 | -0.9438 | -0.1082 |
+#> |.....................| 2.292 | 1.376 | 0.03158 | 1.155 |
+#> |.....................| 0.03033 | 0.7532 | 0.8258 | 1.306 |
+#> |.....................| 1.135 | 1.141 |...........|...........|
+#> | X| 480.33235 | 92.33 | 0.004893 | 0.2801 | 0.8975 |
+#> |.....................| 9.899 | 1.376 | 0.03158 | 1.155 |
+#> |.....................| 0.03033 | 0.7532 | 0.8258 | 1.306 |
+#> |.....................| 1.135 | 1.141 |...........|...........|
+#> | F| Forward Diff. | -44.82 | 1.956 | -0.1640 | 0.1653 |
+#> |.....................| -0.3374 | -39.36 | -9.982 | 1.432 |
+#> |.....................| -2.136 | 0.6770 | 5.747 | -8.552 |
+#> |.....................| -6.943 | -7.038 |...........|...........|
+#> | 35| 479.71253 | 0.9984 | -1.018 | -0.9110 | -0.8961 |
+#> |.....................| -0.8439 | -0.4821 | -0.7885 | -0.8768 |
+#> |.....................| -0.8721 | -0.8833 | -0.9319 | -0.7879 |
+#> |.....................| -0.8057 | -0.8033 |...........|...........|
+#> | U| 479.71253 | 92.97 | -5.321 | -0.9438 | -0.1083 |
+#> |.....................| 2.293 | 1.384 | 0.03160 | 1.155 |
+#> |.....................| 0.03035 | 0.7529 | 0.8236 | 1.310 |
+#> |.....................| 1.138 | 1.144 |...........|...........|
+#> | X| 479.71253 | 92.97 | 0.004888 | 0.2801 | 0.8974 |
+#> |.....................| 9.901 | 1.384 | 0.03160 | 1.155 |
+#> |.....................| 0.03035 | 0.7529 | 0.8236 | 1.310 |
+#> |.....................| 1.138 | 1.144 |...........|...........|
+#> | F| Forward Diff. | 45.27 | 2.001 | 0.09802 | 0.2411 |
+#> |.....................| -0.07361 | -39.48 | -9.147 | 0.2467 |
+#> |.....................| -2.886 | 0.4583 | 7.836 | -8.475 |
+#> |.....................| -6.831 | -7.001 |...........|...........|
+#> | 36| 479.08241 | 0.9920 | -1.019 | -0.9110 | -0.8962 |
+#> |.....................| -0.8438 | -0.4691 | -0.7871 | -0.8771 |
+#> |.....................| -0.8704 | -0.8833 | -0.9359 | -0.7844 |
+#> |.....................| -0.8029 | -0.8006 |...........|...........|
+#> | U| 479.08241 | 92.37 | -5.322 | -0.9438 | -0.1084 |
+#> |.....................| 2.293 | 1.391 | 0.03163 | 1.155 |
+#> |.....................| 0.03037 | 0.7529 | 0.8201 | 1.314 |
+#> |.....................| 1.141 | 1.147 |...........|...........|
+#> | X| 479.08241 | 92.37 | 0.004883 | 0.2801 | 0.8973 |
+#> |.....................| 9.902 | 1.391 | 0.03163 | 1.155 |
+#> |.....................| 0.03037 | 0.7529 | 0.8201 | 1.314 |
+#> |.....................| 1.141 | 1.147 |...........|...........|
+#> | F| Forward Diff. | -39.48 | 1.926 | -0.1378 | 0.1752 |
+#> |.....................| -0.3206 | -38.45 | -9.498 | 0.8453 |
+#> |.....................| -2.699 | 0.3871 | 5.589 | -8.242 |
+#> |.....................| -6.674 | -6.762 |...........|...........|
+#> | 37| 478.53604 | 0.9990 | -1.019 | -0.9110 | -0.8964 |
+#> |.....................| -0.8437 | -0.4561 | -0.7854 | -0.8772 |
+#> |.....................| -0.8684 | -0.8832 | -0.9392 | -0.7811 |
+#> |.....................| -0.8002 | -0.7981 |...........|...........|
+#> | U| 478.53604 | 93.02 | -5.323 | -0.9438 | -0.1085 |
+#> |.....................| 2.293 | 1.399 | 0.03165 | 1.155 |
+#> |.....................| 0.03040 | 0.7530 | 0.8172 | 1.318 |
+#> |.....................| 1.144 | 1.150 |...........|...........|
+#> | X| 478.53604 | 93.02 | 0.004879 | 0.2801 | 0.8972 |
+#> |.....................| 9.903 | 1.399 | 0.03165 | 1.155 |
+#> |.....................| 0.03040 | 0.7530 | 0.8172 | 1.318 |
+#> |.....................| 1.144 | 1.150 |...........|...........|
+#> | F| Forward Diff. | 52.06 | 1.969 | 0.1359 | 0.2508 |
+#> |.....................| -0.04337 | -37.95 | -8.435 | 0.2680 |
+#> |.....................| -2.930 | 0.5186 | 5.955 | -8.188 |
+#> |.....................| -6.576 | -6.741 |...........|...........|
+#> | 38| 477.90297 | 0.9924 | -1.021 | -0.9111 | -0.8965 |
+#> |.....................| -0.8436 | -0.4428 | -0.7846 | -0.8771 |
+#> |.....................| -0.8659 | -0.8830 | -0.9416 | -0.7776 |
+#> |.....................| -0.7975 | -0.7955 |...........|...........|
+#> | U| 477.90297 | 92.41 | -5.324 | -0.9439 | -0.1086 |
+#> |.....................| 2.293 | 1.406 | 0.03166 | 1.155 |
+#> |.....................| 0.03044 | 0.7531 | 0.8151 | 1.323 |
+#> |.....................| 1.147 | 1.152 |...........|...........|
+#> | X| 477.90297 | 92.41 | 0.004873 | 0.2801 | 0.8971 |
+#> |.....................| 9.904 | 1.406 | 0.03166 | 1.155 |
+#> |.....................| 0.03044 | 0.7531 | 0.8151 | 1.323 |
+#> |.....................| 1.147 | 1.152 |...........|...........|
+#> | F| Forward Diff. | -35.48 | 1.900 | -0.1171 | 0.1805 |
+#> |.....................| -0.3013 | -36.12 | -8.554 | 1.521 |
+#> |.....................| -2.082 | 0.5139 | 5.057 | -7.934 |
+#> |.....................| -6.421 | -6.501 |...........|...........|
+#> | 39| 477.39487 | 0.9991 | -1.022 | -0.9111 | -0.8966 |
+#> |.....................| -0.8434 | -0.4296 | -0.7836 | -0.8780 |
+#> |.....................| -0.8642 | -0.8831 | -0.9436 | -0.7740 |
+#> |.....................| -0.7946 | -0.7928 |...........|...........|
+#> | U| 477.39487 | 93.04 | -5.325 | -0.9439 | -0.1088 |
+#> |.....................| 2.293 | 1.414 | 0.03168 | 1.154 |
+#> |.....................| 0.03047 | 0.7531 | 0.8134 | 1.327 |
+#> |.....................| 1.150 | 1.155 |...........|...........|
+#> | X| 477.39487 | 93.04 | 0.004868 | 0.2801 | 0.8969 |
+#> |.....................| 9.906 | 1.414 | 0.03168 | 1.154 |
+#> |.....................| 0.03047 | 0.7531 | 0.8134 | 1.327 |
+#> |.....................| 1.150 | 1.155 |...........|...........|
+#> | F| Forward Diff. | 53.22 | 1.947 | 0.1564 | 0.2562 |
+#> |.....................| -0.02756 | -35.38 | -7.440 | 1.129 |
+#> |.....................| -2.109 | 0.8531 | 5.389 | -7.888 |
+#> |.....................| -6.311 | -6.462 |...........|...........|
+#> | 40| 476.77835 | 0.9927 | -1.023 | -0.9112 | -0.8968 |
+#> |.....................| -0.8433 | -0.4165 | -0.7840 | -0.8801 |
+#> |.....................| -0.8630 | -0.8835 | -0.9455 | -0.7699 |
+#> |.....................| -0.7913 | -0.7897 |...........|...........|
+#> | U| 476.77835 | 92.44 | -5.326 | -0.9439 | -0.1090 |
+#> |.....................| 2.293 | 1.422 | 0.03167 | 1.153 |
+#> |.....................| 0.03048 | 0.7527 | 0.8117 | 1.332 |
+#> |.....................| 1.153 | 1.159 |...........|...........|
+#> | X| 476.77835 | 92.44 | 0.004861 | 0.2801 | 0.8968 |
+#> |.....................| 9.907 | 1.422 | 0.03167 | 1.153 |
+#> |.....................| 0.03048 | 0.7527 | 0.8117 | 1.332 |
+#> |.....................| 1.153 | 1.159 |...........|...........|
+#> | F| Forward Diff. | -31.48 | 1.878 | -0.09989 | 0.1868 |
+#> |.....................| -0.2862 | -34.69 | -7.934 | 1.303 |
+#> |.....................| -2.230 | 0.5238 | 3.299 | -7.623 |
+#> |.....................| -6.137 | -6.207 |...........|...........|
+#> | 41| 476.29140 | 0.9988 | -1.024 | -0.9112 | -0.8970 |
+#> |.....................| -0.8432 | -0.4030 | -0.7837 | -0.8817 |
+#> |.....................| -0.8615 | -0.8839 | -0.9453 | -0.7660 |
+#> |.....................| -0.7883 | -0.7869 |...........|...........|
+#> | U| 476.2914 | 93.01 | -5.328 | -0.9440 | -0.1091 |
+#> |.....................| 2.293 | 1.430 | 0.03168 | 1.152 |
+#> |.....................| 0.03051 | 0.7524 | 0.8119 | 1.337 |
+#> |.....................| 1.157 | 1.162 |...........|...........|
+#> | X| 476.2914 | 93.01 | 0.004855 | 0.2801 | 0.8966 |
+#> |.....................| 9.909 | 1.430 | 0.03168 | 1.152 |
+#> |.....................| 0.03051 | 0.7524 | 0.8119 | 1.337 |
+#> |.....................| 1.157 | 1.162 |...........|...........|
+#> | F| Forward Diff. | 48.73 | 1.930 | 0.1514 | 0.2545 |
+#> |.....................| -0.03521 | -34.01 | -6.934 | 1.004 |
+#> |.....................| -2.133 | 0.7968 | 5.252 | -7.528 |
+#> |.....................| -6.021 | -6.137 |...........|...........|
+#> | 42| 475.72593 | 0.9927 | -1.026 | -0.9113 | -0.8972 |
+#> |.....................| -0.8430 | -0.3897 | -0.7848 | -0.8834 |
+#> |.....................| -0.8598 | -0.8844 | -0.9451 | -0.7619 |
+#> |.....................| -0.7851 | -0.7840 |...........|...........|
+#> | U| 475.72593 | 92.44 | -5.329 | -0.9441 | -0.1094 |
+#> |.....................| 2.294 | 1.437 | 0.03166 | 1.151 |
+#> |.....................| 0.03053 | 0.7521 | 0.8121 | 1.342 |
+#> |.....................| 1.160 | 1.165 |...........|...........|
+#> | X| 475.72593 | 92.44 | 0.004847 | 0.2801 | 0.8964 |
+#> |.....................| 9.910 | 1.437 | 0.03166 | 1.151 |
+#> |.....................| 0.03053 | 0.7521 | 0.8121 | 1.342 |
+#> |.....................| 1.160 | 1.165 |...........|...........|
+#> | F| Forward Diff. | -31.62 | 1.868 | -0.1026 | 0.1833 |
+#> |.....................| -0.2884 | -33.06 | -7.282 | 1.547 |
+#> |.....................| -2.194 | 0.5347 | 3.320 | -7.249 |
+#> |.....................| -5.852 | -5.889 |...........|...........|
+#> | 43| 475.25217 | 0.9986 | -1.027 | -0.9113 | -0.8974 |
+#> |.....................| -0.8428 | -0.3762 | -0.7856 | -0.8854 |
+#> |.....................| -0.8580 | -0.8849 | -0.9453 | -0.7580 |
+#> |.....................| -0.7821 | -0.7812 |...........|...........|
+#> | U| 475.25217 | 92.99 | -5.331 | -0.9441 | -0.1096 |
+#> |.....................| 2.294 | 1.445 | 0.03165 | 1.150 |
+#> |.....................| 0.03056 | 0.7517 | 0.8119 | 1.346 |
+#> |.....................| 1.163 | 1.168 |...........|...........|
+#> | X| 475.25217 | 92.99 | 0.004840 | 0.2801 | 0.8962 |
+#> |.....................| 9.912 | 1.445 | 0.03165 | 1.150 |
+#> |.....................| 0.03056 | 0.7517 | 0.8119 | 1.346 |
+#> |.....................| 1.163 | 1.168 |...........|...........|
+#> | F| Forward Diff. | 45.01 | 1.918 | 0.1424 | 0.2472 |
+#> |.....................| -0.04139 | -32.61 | -6.424 | 0.9161 |
+#> |.....................| -2.151 | 0.6354 | 5.209 | -7.174 |
+#> |.....................| -5.746 | -5.822 |...........|...........|
+#> | 44| 474.72079 | 0.9929 | -1.029 | -0.9114 | -0.8977 |
+#> |.....................| -0.8427 | -0.3629 | -0.7879 | -0.8876 |
+#> |.....................| -0.8559 | -0.8852 | -0.9458 | -0.7541 |
+#> |.....................| -0.7790 | -0.7785 |...........|...........|
+#> | U| 474.72079 | 92.46 | -5.333 | -0.9442 | -0.1098 |
+#> |.....................| 2.294 | 1.453 | 0.03161 | 1.149 |
+#> |.....................| 0.03059 | 0.7515 | 0.8114 | 1.351 |
+#> |.....................| 1.167 | 1.171 |...........|...........|
+#> | X| 474.72079 | 92.46 | 0.004831 | 0.2800 | 0.8960 |
+#> |.....................| 9.913 | 1.453 | 0.03161 | 1.149 |
+#> |.....................| 0.03059 | 0.7515 | 0.8114 | 1.351 |
+#> |.....................| 1.167 | 1.171 |...........|...........|
+#> | F| Forward Diff. | -29.98 | 1.856 | -0.09377 | 0.1852 |
+#> |.....................| -0.2753 | -32.15 | -6.889 | 1.072 |
+#> |.....................| -2.266 | 0.4091 | 3.274 | -6.876 |
+#> |.....................| -5.564 | -5.585 |...........|...........|
+#> | 45| 474.26379 | 0.9985 | -1.031 | -0.9115 | -0.8979 |
+#> |.....................| -0.8425 | -0.3491 | -0.7895 | -0.8887 |
+#> |.....................| -0.8536 | -0.8852 | -0.9464 | -0.7506 |
+#> |.....................| -0.7762 | -0.7761 |...........|...........|
+#> | U| 474.26379 | 92.98 | -5.335 | -0.9443 | -0.1101 |
+#> |.....................| 2.294 | 1.461 | 0.03159 | 1.148 |
+#> |.....................| 0.03063 | 0.7515 | 0.8109 | 1.355 |
+#> |.....................| 1.170 | 1.173 |...........|...........|
+#> | X| 474.26379 | 92.98 | 0.004822 | 0.2800 | 0.8958 |
+#> |.....................| 9.915 | 1.461 | 0.03159 | 1.148 |
+#> |.....................| 0.03063 | 0.7515 | 0.8109 | 1.355 |
+#> |.....................| 1.170 | 1.173 |...........|...........|
+#> | F| Forward Diff. | 42.78 | 1.902 | 0.1464 | 0.2388 |
+#> |.....................| -0.03417 | -31.28 | -5.931 | 0.8375 |
+#> |.....................| -2.202 | 0.7305 | 5.128 | -6.841 |
+#> |.....................| -5.479 | -5.554 |...........|...........|
+#> | 46| 473.76810 | 0.9929 | -1.033 | -0.9117 | -0.8982 |
+#> |.....................| -0.8424 | -0.3358 | -0.7928 | -0.8897 |
+#> |.....................| -0.8508 | -0.8855 | -0.9473 | -0.7471 |
+#> |.....................| -0.7734 | -0.7737 |...........|...........|
+#> | U| 473.7681 | 92.46 | -5.337 | -0.9444 | -0.1104 |
+#> |.....................| 2.294 | 1.469 | 0.03154 | 1.147 |
+#> |.....................| 0.03067 | 0.7512 | 0.8101 | 1.360 |
+#> |.....................| 1.173 | 1.176 |...........|...........|
+#> | X| 473.7681 | 92.46 | 0.004812 | 0.2800 | 0.8955 |
+#> |.....................| 9.917 | 1.469 | 0.03154 | 1.147 |
+#> |.....................| 0.03067 | 0.7512 | 0.8101 | 1.360 |
+#> |.....................| 1.173 | 1.176 |...........|...........|
+#> | F| Forward Diff. | -30.83 | 1.832 | -0.1003 | 0.1743 |
+#> |.....................| -0.2686 | -30.77 | -6.362 | 1.107 |
+#> |.....................| -2.234 | 0.4249 | 4.678 | -6.593 |
+#> |.....................| -5.329 | -5.340 |...........|...........|
+#> | 47| 473.32508 | 0.9983 | -1.035 | -0.9117 | -0.8984 |
+#> |.....................| -0.8422 | -0.3229 | -0.7959 | -0.8909 |
+#> |.....................| -0.8482 | -0.8859 | -0.9520 | -0.7438 |
+#> |.....................| -0.7708 | -0.7715 |...........|...........|
+#> | U| 473.32508 | 92.96 | -5.339 | -0.9445 | -0.1106 |
+#> |.....................| 2.294 | 1.476 | 0.03149 | 1.147 |
+#> |.....................| 0.03071 | 0.7509 | 0.8061 | 1.364 |
+#> |.....................| 1.175 | 1.178 |...........|...........|
+#> | X| 473.32508 | 92.96 | 0.004802 | 0.2800 | 0.8953 |
+#> |.....................| 9.918 | 1.476 | 0.03149 | 1.147 |
+#> |.....................| 0.03071 | 0.7509 | 0.8061 | 1.364 |
+#> |.....................| 1.175 | 1.178 |...........|...........|
+#> | F| Forward Diff. | 38.19 | 1.865 | 0.1554 | 0.2504 |
+#> |.....................| -0.02116 | -30.15 | -5.522 | 0.8218 |
+#> |.....................| -2.215 | 0.6878 | 4.772 | -6.537 |
+#> |.....................| -5.232 | -5.315 |...........|...........|
+#> | 48| 472.87290 | 0.9930 | -1.038 | -0.9119 | -0.8988 |
+#> |.....................| -0.8421 | -0.3103 | -0.8002 | -0.8921 |
+#> |.....................| -0.8451 | -0.8864 | -0.9564 | -0.7407 |
+#> |.....................| -0.7684 | -0.7695 |...........|...........|
+#> | U| 472.8729 | 92.47 | -5.341 | -0.9447 | -0.1109 |
+#> |.....................| 2.294 | 1.483 | 0.03143 | 1.146 |
+#> |.....................| 0.03075 | 0.7506 | 0.8022 | 1.367 |
+#> |.....................| 1.178 | 1.180 |...........|...........|
+#> | X| 472.8729 | 92.47 | 0.004791 | 0.2800 | 0.8950 |
+#> |.....................| 9.919 | 1.483 | 0.03143 | 1.146 |
+#> |.....................| 0.03075 | 0.7506 | 0.8022 | 1.367 |
+#> |.....................| 1.178 | 1.180 |...........|...........|
+#> | F| Forward Diff. | -31.43 | 1.786 | -0.07853 | 0.1828 |
+#> |.....................| -0.2451 | -29.69 | -5.937 | 1.129 |
+#> |.....................| -2.237 | 0.5225 | 4.143 | -6.356 |
+#> |.....................| -5.097 | -5.139 |...........|...........|
+#> | 49| 472.45068 | 0.9981 | -1.040 | -0.9121 | -0.8991 |
+#> |.....................| -0.8421 | -0.2974 | -0.8046 | -0.8935 |
+#> |.....................| -0.8420 | -0.8871 | -0.9597 | -0.7375 |
+#> |.....................| -0.7660 | -0.7674 |...........|...........|
+#> | U| 472.45068 | 92.94 | -5.343 | -0.9449 | -0.1112 |
+#> |.....................| 2.294 | 1.491 | 0.03136 | 1.145 |
+#> |.....................| 0.03080 | 0.7500 | 0.7993 | 1.371 |
+#> |.....................| 1.180 | 1.183 |...........|...........|
+#> | X| 472.45068 | 92.94 | 0.004780 | 0.2799 | 0.8947 |
+#> |.....................| 9.919 | 1.491 | 0.03136 | 1.145 |
+#> |.....................| 0.03080 | 0.7500 | 0.7993 | 1.371 |
+#> |.....................| 1.180 | 1.183 |...........|...........|
+#> | F| Forward Diff. | 34.69 | 1.825 | 0.1712 | 0.2558 |
+#> |.....................| 0.0008262 | -30.15 | -5.461 | 0.02383 |
+#> |.....................| -3.011 | 0.3236 | 4.609 | -6.242 |
+#> |.....................| -4.997 | -5.107 |...........|...........|
+#> | 50| 472.02915 | 0.9936 | -1.042 | -0.9125 | -0.8995 |
+#> |.....................| -0.8422 | -0.2847 | -0.8092 | -0.8923 |
+#> |.....................| -0.8364 | -0.8868 | -0.9626 | -0.7353 |
+#> |.....................| -0.7644 | -0.7660 |...........|...........|
+#> | U| 472.02915 | 92.52 | -5.345 | -0.9452 | -0.1116 |
+#> |.....................| 2.294 | 1.498 | 0.03129 | 1.146 |
+#> |.....................| 0.03088 | 0.7503 | 0.7968 | 1.374 |
+#> |.....................| 1.182 | 1.184 |...........|...........|
+#> | X| 472.02915 | 92.52 | 0.004770 | 0.2799 | 0.8944 |
+#> |.....................| 9.918 | 1.498 | 0.03129 | 1.146 |
+#> |.....................| 0.03088 | 0.7503 | 0.7968 | 1.374 |
+#> |.....................| 1.182 | 1.184 |...........|...........|
+#> | F| Forward Diff. | -26.29 | 1.758 | -0.04843 | 0.1910 |
+#> |.....................| -0.1997 | -28.69 | -5.506 | 1.097 |
+#> |.....................| -2.285 | 0.4947 | 2.297 | -6.079 |
+#> |.....................| -4.892 | -4.970 |...........|...........|
+#> | 51| 471.69520 | 0.9992 | -1.044 | -0.9127 | -0.8998 |
+#> |.....................| -0.8423 | -0.2715 | -0.8127 | -0.8918 |
+#> |.....................| -0.8317 | -0.8866 | -0.9606 | -0.7330 |
+#> |.....................| -0.7627 | -0.7642 |...........|...........|
+#> | U| 471.6952 | 93.04 | -5.347 | -0.9454 | -0.1120 |
+#> |.....................| 2.294 | 1.506 | 0.03124 | 1.146 |
+#> |.....................| 0.03096 | 0.7504 | 0.7985 | 1.377 |
+#> |.....................| 1.184 | 1.186 |...........|...........|
+#> | X| 471.6952 | 93.04 | 0.004761 | 0.2798 | 0.8941 |
+#> |.....................| 9.917 | 1.506 | 0.03124 | 1.146 |
+#> |.....................| 0.03096 | 0.7504 | 0.7985 | 1.377 |
+#> |.....................| 1.184 | 1.186 |...........|...........|
+#> | F| Forward Diff. | 46.70 | 1.815 | 0.2108 | 0.2607 |
+#> |.....................| 0.05766 | -27.95 | -4.639 | 0.9041 |
+#> |.....................| -2.201 | 0.7590 | 4.326 | -6.078 |
+#> |.....................| -4.851 | -4.972 |...........|...........|
+#> | 52| 471.30240 | 0.9939 | -1.046 | -0.9131 | -0.9002 |
+#> |.....................| -0.8425 | -0.2596 | -0.8187 | -0.8939 |
+#> |.....................| -0.8280 | -0.8876 | -0.9571 | -0.7302 |
+#> |.....................| -0.7606 | -0.7622 |...........|...........|
+#> | U| 471.3024 | 92.55 | -5.350 | -0.9458 | -0.1124 |
+#> |.....................| 2.294 | 1.513 | 0.03115 | 1.145 |
+#> |.....................| 0.03101 | 0.7497 | 0.8016 | 1.380 |
+#> |.....................| 1.186 | 1.188 |...........|...........|
+#> | X| 471.3024 | 92.55 | 0.004750 | 0.2797 | 0.8937 |
+#> |.....................| 9.915 | 1.513 | 0.03115 | 1.145 |
+#> |.....................| 0.03101 | 0.7497 | 0.8016 | 1.380 |
+#> |.....................| 1.186 | 1.188 |...........|...........|
+#> | F| Forward Diff. | -23.61 | 1.763 | -0.06060 | 0.1836 |
+#> |.....................| -0.1912 | -28.31 | -5.279 | 0.6597 |
+#> |.....................| -2.739 | 0.2048 | 5.941 | -5.864 |
+#> |.....................| -4.747 | -4.787 |...........|...........|
+#> | 53| 470.94339 | 0.9985 | -1.048 | -0.9133 | -0.9006 |
+#> |.....................| -0.8426 | -0.2476 | -0.8235 | -0.8946 |
+#> |.....................| -0.8237 | -0.8877 | -0.9629 | -0.7278 |
+#> |.....................| -0.7587 | -0.7604 |...........|...........|
+#> | U| 470.94339 | 92.98 | -5.352 | -0.9460 | -0.1127 |
+#> |.....................| 2.294 | 1.520 | 0.03108 | 1.145 |
+#> |.....................| 0.03108 | 0.7496 | 0.7965 | 1.383 |
+#> |.....................| 1.188 | 1.190 |...........|...........|
+#> | X| 470.94339 | 92.98 | 0.004740 | 0.2797 | 0.8934 |
+#> |.....................| 9.914 | 1.520 | 0.03108 | 1.145 |
+#> |.....................| 0.03108 | 0.7496 | 0.7965 | 1.383 |
+#> |.....................| 1.188 | 1.190 |...........|...........|
+#> | F| Forward Diff. | 36.04 | 1.791 | 0.1836 | 0.2544 |
+#> |.....................| 0.04274 | -27.03 | -4.370 | 0.9159 |
+#> |.....................| -2.217 | 0.6791 | 4.141 | -5.840 |
+#> |.....................| -4.667 | -4.764 |...........|...........|
+#> | 54| 470.60274 | 0.9931 | -1.051 | -0.9136 | -0.9010 |
+#> |.....................| -0.8428 | -0.2366 | -0.8300 | -0.8957 |
+#> |.....................| -0.8190 | -0.8879 | -0.9681 | -0.7257 |
+#> |.....................| -0.7570 | -0.7588 |...........|...........|
+#> | U| 470.60274 | 92.48 | -5.354 | -0.9463 | -0.1131 |
+#> |.....................| 2.294 | 1.526 | 0.03098 | 1.144 |
+#> |.....................| 0.03115 | 0.7494 | 0.7919 | 1.386 |
+#> |.....................| 1.190 | 1.192 |...........|...........|
+#> | X| 470.60274 | 92.48 | 0.004728 | 0.2796 | 0.8930 |
+#> |.....................| 9.912 | 1.526 | 0.03098 | 1.144 |
+#> |.....................| 0.03115 | 0.7494 | 0.7919 | 1.386 |
+#> |.....................| 1.190 | 1.192 |...........|...........|
+#> | F| Forward Diff. | -35.91 | 1.718 | -0.07847 | 0.1786 |
+#> |.....................| -0.1996 | -26.69 | -4.843 | 1.231 |
+#> |.....................| -2.229 | 0.5625 | 3.489 | -5.662 |
+#> |.....................| -4.557 | -4.604 |...........|...........|
+#> | 55| 470.25392 | 0.9977 | -1.054 | -0.9140 | -0.9015 |
+#> |.....................| -0.8431 | -0.2250 | -0.8375 | -0.8987 |
+#> |.....................| -0.8153 | -0.8894 | -0.9673 | -0.7229 |
+#> |.....................| -0.7550 | -0.7569 |...........|...........|
+#> | U| 470.25392 | 92.90 | -5.357 | -0.9467 | -0.1136 |
+#> |.....................| 2.293 | 1.533 | 0.03087 | 1.142 |
+#> |.....................| 0.03120 | 0.7483 | 0.7927 | 1.389 |
+#> |.....................| 1.192 | 1.194 |...........|...........|
+#> | X| 470.25392 | 92.90 | 0.004715 | 0.2796 | 0.8926 |
+#> |.....................| 9.909 | 1.533 | 0.03087 | 1.142 |
+#> |.....................| 0.03120 | 0.7483 | 0.7927 | 1.389 |
+#> |.....................| 1.192 | 1.194 |...........|...........|
+#> | F| Forward Diff. | 23.42 | 1.753 | 0.1414 | 0.2393 |
+#> |.....................| 0.01691 | -26.51 | -4.262 | 0.6993 |
+#> |.....................| -2.408 | 0.5525 | 2.318 | -5.573 |
+#> |.....................| -4.475 | -4.572 |...........|...........|
+#> | 56| 469.96066 | 0.9934 | -1.056 | -0.9144 | -0.9019 |
+#> |.....................| -0.8434 | -0.2128 | -0.8432 | -0.9002 |
+#> |.....................| -0.8113 | -0.8903 | -0.9627 | -0.7205 |
+#> |.....................| -0.7531 | -0.7551 |...........|...........|
+#> | U| 469.96066 | 92.50 | -5.359 | -0.9470 | -0.1140 |
+#> |.....................| 2.293 | 1.540 | 0.03078 | 1.141 |
+#> |.....................| 0.03126 | 0.7476 | 0.7967 | 1.392 |
+#> |.....................| 1.194 | 1.196 |...........|...........|
+#> | X| 469.96066 | 92.50 | 0.004704 | 0.2795 | 0.8922 |
+#> |.....................| 9.906 | 1.540 | 0.03078 | 1.141 |
+#> |.....................| 0.03126 | 0.7476 | 0.7967 | 1.392 |
+#> |.....................| 1.194 | 1.196 |...........|...........|
+#> | F| Forward Diff. | -33.10 | 1.713 | -0.09549 | 0.1710 |
+#> |.....................| -0.1943 | -25.89 | -4.557 | 1.045 |
+#> |.....................| -2.243 | 0.5648 | 3.834 | -5.392 |
+#> |.....................| -4.399 | -4.402 |...........|...........|
+#> | 57| 469.66426 | 0.9983 | -1.059 | -0.9147 | -0.9023 |
+#> |.....................| -0.8437 | -0.2012 | -0.8503 | -0.9014 |
+#> |.....................| -0.8068 | -0.8914 | -0.9589 | -0.7186 |
+#> |.....................| -0.7515 | -0.7537 |...........|...........|
+#> | U| 469.66426 | 92.95 | -5.362 | -0.9473 | -0.1144 |
+#> |.....................| 2.293 | 1.547 | 0.03068 | 1.141 |
+#> |.....................| 0.03133 | 0.7468 | 0.8000 | 1.394 |
+#> |.....................| 1.196 | 1.197 |...........|...........|
+#> | X| 469.66426 | 92.95 | 0.004691 | 0.2794 | 0.8919 |
+#> |.....................| 9.903 | 1.547 | 0.03068 | 1.141 |
+#> |.....................| 0.03133 | 0.7468 | 0.8000 | 1.394 |
+#> |.....................| 1.196 | 1.197 |...........|...........|
+#> | F| Forward Diff. | 29.48 | 1.769 | 0.1441 | 0.2362 |
+#> |.....................| 0.03493 | -25.40 | -3.876 | 0.7581 |
+#> |.....................| -2.246 | 0.6653 | 4.370 | -5.362 |
+#> |.....................| -4.340 | -4.389 |...........|...........|
+#> | 58| 469.35361 | 0.9940 | -1.062 | -0.9149 | -0.9027 |
+#> |.....................| -0.8440 | -0.1900 | -0.8585 | -0.9032 |
+#> |.....................| -0.8026 | -0.8931 | -0.9615 | -0.7168 |
+#> |.....................| -0.7497 | -0.7523 |...........|...........|
+#> | U| 469.35361 | 92.56 | -5.365 | -0.9475 | -0.1149 |
+#> |.....................| 2.293 | 1.553 | 0.03055 | 1.140 |
+#> |.....................| 0.03139 | 0.7454 | 0.7977 | 1.396 |
+#> |.....................| 1.198 | 1.199 |...........|...........|
+#> | X| 469.35361 | 92.56 | 0.004677 | 0.2794 | 0.8915 |
+#> |.....................| 9.900 | 1.553 | 0.03055 | 1.140 |
+#> |.....................| 0.03139 | 0.7454 | 0.7977 | 1.396 |
+#> |.....................| 1.198 | 1.199 |...........|...........|
+#> | F| Forward Diff. | -26.71 | 1.702 | -0.07338 | 0.1729 |
+#> |.....................| -0.1601 | -26.00 | -4.465 | 0.4354 |
+#> |.....................| -2.821 | 0.3110 | 5.728 | -5.228 |
+#> |.....................| -4.240 | -4.266 |...........|...........|
+#> | 59| 469.04262 | 0.9978 | -1.064 | -0.9151 | -0.9031 |
+#> |.....................| -0.8443 | -0.1798 | -0.8657 | -0.9030 |
+#> |.....................| -0.7971 | -0.8938 | -0.9685 | -0.7157 |
+#> |.....................| -0.7487 | -0.7515 |...........|...........|
+#> | U| 469.04262 | 92.91 | -5.368 | -0.9477 | -0.1152 |
+#> |.....................| 2.292 | 1.559 | 0.03044 | 1.140 |
+#> |.....................| 0.03147 | 0.7450 | 0.7916 | 1.398 |
+#> |.....................| 1.199 | 1.200 |...........|...........|
+#> | X| 469.04262 | 92.91 | 0.004665 | 0.2794 | 0.8912 |
+#> |.....................| 9.897 | 1.559 | 0.03044 | 1.140 |
+#> |.....................| 0.03147 | 0.7450 | 0.7916 | 1.398 |
+#> |.....................| 1.199 | 1.200 |...........|...........|
+#> | 60| 468.78438 | 0.9975 | -1.068 | -0.9154 | -0.9036 |
+#> |.....................| -0.8447 | -0.1709 | -0.8764 | -0.9025 |
+#> |.....................| -0.7900 | -0.8946 | -0.9771 | -0.7153 |
+#> |.....................| -0.7482 | -0.7514 |...........|...........|
+#> | U| 468.78438 | 92.88 | -5.371 | -0.9479 | -0.1157 |
+#> |.....................| 2.292 | 1.564 | 0.03028 | 1.140 |
+#> |.....................| 0.03158 | 0.7443 | 0.7841 | 1.398 |
+#> |.....................| 1.200 | 1.200 |...........|...........|
+#> | X| 468.78438 | 92.88 | 0.004649 | 0.2793 | 0.8907 |
+#> |.....................| 9.893 | 1.564 | 0.03028 | 1.140 |
+#> |.....................| 0.03158 | 0.7443 | 0.7841 | 1.398 |
+#> |.....................| 1.200 | 1.200 |...........|...........|
+#> | 61| 467.65199 | 0.9960 | -1.083 | -0.9167 | -0.9058 |
+#> |.....................| -0.8469 | -0.1283 | -0.9284 | -0.9002 |
+#> |.....................| -0.7560 | -0.8987 | -1.018 | -0.7133 |
+#> |.....................| -0.7456 | -0.7506 |...........|...........|
+#> | U| 467.65199 | 92.74 | -5.387 | -0.9492 | -0.1179 |
+#> |.....................| 2.290 | 1.589 | 0.02950 | 1.141 |
+#> |.....................| 0.03209 | 0.7413 | 0.7481 | 1.401 |
+#> |.....................| 1.202 | 1.201 |...........|...........|
+#> | X| 467.65199 | 92.74 | 0.004577 | 0.2791 | 0.8887 |
+#> |.....................| 9.872 | 1.589 | 0.02950 | 1.141 |
+#> |.....................| 0.03209 | 0.7413 | 0.7481 | 1.401 |
+#> |.....................| 1.202 | 1.201 |...........|...........|
+#> | 62| 464.96560 | 0.9898 | -1.148 | -0.9222 | -0.9151 |
+#> |.....................| -0.8556 | 0.04847 | -1.144 | -0.8910 |
+#> |.....................| -0.6148 | -0.9154 | -1.189 | -0.7051 |
+#> |.....................| -0.7350 | -0.7474 |...........|...........|
+#> | U| 464.9656 | 92.17 | -5.451 | -0.9543 | -0.1273 |
+#> |.....................| 2.281 | 1.691 | 0.02626 | 1.147 |
+#> |.....................| 0.03421 | 0.7285 | 0.5986 | 1.411 |
+#> |.....................| 1.214 | 1.204 |...........|...........|
+#> | X| 464.9656 | 92.17 | 0.004291 | 0.2780 | 0.8805 |
+#> |.....................| 9.786 | 1.691 | 0.02626 | 1.147 |
+#> |.....................| 0.03421 | 0.7285 | 0.5986 | 1.411 |
+#> |.....................| 1.214 | 1.204 |...........|...........|
+#> | F| Forward Diff. | -134.9 | 0.8693 | 0.2607 | 0.2086 |
+#> |.....................| 0.2111 | -19.53 | -3.427 | 3.399 |
+#> |.....................| -2.172 | 1.526 | -11.79 | -4.993 |
+#> |.....................| -3.321 | -4.659 |...........|...........|
+#> | 63| 458.88877 | 1.003 | -1.235 | -0.9465 | -0.9328 |
+#> |.....................| -0.8841 | 0.3192 | -1.460 | -0.9475 |
+#> |.....................| -0.4237 | -0.9768 | -1.134 | -0.6574 |
+#> |.....................| -0.7075 | -0.6995 |...........|...........|
+#> | U| 458.88877 | 93.40 | -5.538 | -0.9774 | -0.1450 |
+#> |.....................| 2.252 | 1.848 | 0.02152 | 1.114 |
+#> |.....................| 0.03709 | 0.6820 | 0.6469 | 1.468 |
+#> |.....................| 1.243 | 1.255 |...........|...........|
+#> | X| 458.88877 | 93.40 | 0.003933 | 0.2734 | 0.8651 |
+#> |.....................| 9.511 | 1.848 | 0.02152 | 1.114 |
+#> |.....................| 0.03709 | 0.6820 | 0.6469 | 1.468 |
+#> |.....................| 1.243 | 1.255 |...........|...........|
+#> | 64| 455.19412 | 1.006 | -1.330 | -0.9732 | -0.9522 |
+#> |.....................| -0.9154 | 0.6143 | -1.806 | -1.009 |
+#> |.....................| -0.2144 | -1.044 | -1.075 | -0.6056 |
+#> |.....................| -0.6776 | -0.6473 |...........|...........|
+#> | U| 455.19412 | 93.67 | -5.634 | -1.003 | -0.1644 |
+#> |.....................| 2.221 | 2.019 | 0.01631 | 1.078 |
+#> |.....................| 0.04023 | 0.6311 | 0.6989 | 1.531 |
+#> |.....................| 1.275 | 1.311 |...........|...........|
+#> | X| 455.19412 | 93.67 | 0.003576 | 0.2684 | 0.8484 |
+#> |.....................| 9.218 | 2.019 | 0.01631 | 1.078 |
+#> |.....................| 0.04023 | 0.6311 | 0.6989 | 1.531 |
+#> |.....................| 1.275 | 1.311 |...........|...........|
+#> | F| Forward Diff. | 18.82 | 0.9889 | -1.032 | -0.1489 |
+#> |.....................| 0.2009 | -8.117 | -0.5123 | 0.1656 |
+#> |.....................| -2.314 | -3.473 | -0.8284 | 0.3432 |
+#> |.....................| -0.8357 | 0.04588 |...........|...........|
+#> | 65| 458.62552 | 1.004 | -1.494 | -0.8145 | -0.9319 |
+#> |.....................| -0.9630 | 1.033 | -2.192 | -1.036 |
+#> |.....................| 0.2529 | -0.5036 | -0.8838 | -0.8679 |
+#> |.....................| -0.7178 | -0.8209 |...........|...........|
+#> | U| 458.62552 | 93.52 | -5.797 | -0.8527 | -0.1440 |
+#> |.....................| 2.174 | 2.262 | 0.01051 | 1.062 |
+#> |.....................| 0.04725 | 1.041 | 0.8656 | 1.213 |
+#> |.....................| 1.232 | 1.125 |...........|...........|
+#> | X| 458.62552 | 93.52 | 0.003036 | 0.2989 | 0.8659 |
+#> |.....................| 8.789 | 2.262 | 0.01051 | 1.062 |
+#> |.....................| 0.04725 | 1.041 | 0.8656 | 1.213 |
+#> |.....................| 1.232 | 1.125 |...........|...........|
+#> | 66| 454.48694 | 1.003 | -1.384 | -0.9206 | -0.9455 |
+#> |.....................| -0.9312 | 0.7538 | -1.934 | -1.018 |
+#> |.....................| -0.05956 | -0.8649 | -1.011 | -0.6924 |
+#> |.....................| -0.6908 | -0.7048 |...........|...........|
+#> | U| 454.48694 | 93.41 | -5.688 | -0.9529 | -0.1576 |
+#> |.....................| 2.205 | 2.100 | 0.01439 | 1.073 |
+#> |.....................| 0.04256 | 0.7669 | 0.7542 | 1.426 |
+#> |.....................| 1.261 | 1.250 |...........|...........|
+#> | X| 454.48694 | 93.41 | 0.003387 | 0.2783 | 0.8542 |
+#> |.....................| 9.074 | 2.100 | 0.01439 | 1.073 |
+#> |.....................| 0.04256 | 0.7669 | 0.7542 | 1.426 |
+#> |.....................| 1.261 | 1.250 |...........|...........|
+#> | F| Forward Diff. | -11.88 | 0.8805 | 1.030 | 0.0001663 |
+#> |.....................| -0.3119 | -6.748 | -1.151 | 0.2517 |
+#> |.....................| -3.379 | 3.981 | 5.317 | -4.395 |
+#> |.....................| -1.890 | -2.785 |...........|...........|
+#> | 67| 453.47854 | 1.004 | -1.455 | -0.9097 | -0.9308 |
+#> |.....................| -0.9364 | 0.8078 | -2.047 | -1.046 |
+#> |.....................| 0.2383 | -0.8443 | -0.9977 | -0.6524 |
+#> |.....................| -0.6789 | -0.6970 |...........|...........|
+#> | U| 453.47854 | 93.48 | -5.759 | -0.9426 | -0.1429 |
+#> |.....................| 2.200 | 2.132 | 0.01270 | 1.056 |
+#> |.....................| 0.04703 | 0.7825 | 0.7661 | 1.474 |
+#> |.....................| 1.274 | 1.258 |...........|...........|
+#> | X| 453.47854 | 93.48 | 0.003156 | 0.2804 | 0.8668 |
+#> |.....................| 9.026 | 2.132 | 0.01270 | 1.056 |
+#> |.....................| 0.04703 | 0.7825 | 0.7661 | 1.474 |
+#> |.....................| 1.274 | 1.258 |...........|...........|
+#> | F| Forward Diff. | -7.580 | 0.7096 | 1.748 | 0.4450 |
+#> |.....................| -0.3063 | -5.686 | -1.090 | 2.089 |
+#> |.....................| -1.806 | 4.661 | 3.477 | -2.550 |
+#> |.....................| -1.063 | -2.646 |...........|...........|
+#> | 68| 452.65869 | 1.010 | -1.604 | -0.9910 | -0.9601 |
+#> |.....................| -0.9321 | 0.9548 | -2.236 | -1.333 |
+#> |.....................| 0.7427 | -0.9083 | -1.017 | -0.7899 |
+#> |.....................| -0.7453 | -0.6781 |...........|...........|
+#> | U| 452.65869 | 94.06 | -5.907 | -1.019 | -0.1723 |
+#> |.....................| 2.204 | 2.217 | 0.009851 | 0.8906 |
+#> |.....................| 0.05461 | 0.7340 | 0.7490 | 1.308 |
+#> |.....................| 1.203 | 1.278 |...........|...........|
+#> | X| 452.65869 | 94.06 | 0.002719 | 0.2652 | 0.8418 |
+#> |.....................| 9.065 | 2.217 | 0.009851 | 0.8906 |
+#> |.....................| 0.05461 | 0.7340 | 0.7490 | 1.308 |
+#> |.....................| 1.203 | 1.278 |...........|...........|
+#> | F| Forward Diff. | 87.74 | 0.4343 | -0.7887 | -0.2527 |
+#> |.....................| -0.1232 | -3.287 | -0.3715 | -5.728 |
+#> |.....................| -3.469 | 4.620 | 5.104 | -8.863 |
+#> |.....................| -5.024 | -1.180 |...........|...........|
+#> | 69| 455.46876 | 1.000 | -1.721 | -0.9929 | -1.109 |
+#> |.....................| -0.8905 | 1.109 | -2.343 | -1.386 |
+#> |.....................| 1.193 | -1.162 | -0.9750 | -0.9277 |
+#> |.....................| -0.5804 | -0.9245 |...........|...........|
+#> | U| 455.46876 | 93.13 | -6.025 | -1.021 | -0.3216 |
+#> |.....................| 2.246 | 2.306 | 0.008241 | 0.8595 |
+#> |.....................| 0.06138 | 0.5417 | 0.7859 | 1.140 |
+#> |.....................| 1.379 | 1.014 |...........|...........|
+#> | X| 455.46876 | 93.13 | 0.002419 | 0.2648 | 0.7250 |
+#> |.....................| 9.450 | 2.306 | 0.008241 | 0.8595 |
+#> |.....................| 0.06138 | 0.5417 | 0.7859 | 1.140 |
+#> |.....................| 1.379 | 1.014 |...........|...........|
+#> | 70| 453.13548 | 0.9926 | -1.633 | -0.9913 | -0.9976 |
+#> |.....................| -0.9216 | 0.9941 | -2.263 | -1.345 |
+#> |.....................| 0.8563 | -0.9728 | -1.008 | -0.8230 |
+#> |.....................| -0.7030 | -0.7398 |...........|...........|
+#> | U| 453.13548 | 92.43 | -5.937 | -1.020 | -0.2097 |
+#> |.....................| 2.215 | 2.240 | 0.009448 | 0.8833 |
+#> |.....................| 0.05632 | 0.6851 | 0.7575 | 1.268 |
+#> |.....................| 1.248 | 1.212 |...........|...........|
+#> | X| 453.13548 | 92.43 | 0.002640 | 0.2651 | 0.8108 |
+#> |.....................| 9.161 | 2.240 | 0.009448 | 0.8833 |
+#> |.....................| 0.05632 | 0.6851 | 0.7575 | 1.268 |
+#> |.....................| 1.248 | 1.212 |...........|...........|
+#> | 71| 453.54485 | 0.9910 | -1.615 | -0.9910 | -0.9747 |
+#> |.....................| -0.9280 | 0.9706 | -2.247 | -1.337 |
+#> |.....................| 0.7875 | -0.9341 | -1.014 | -0.8015 |
+#> |.....................| -0.7281 | -0.7020 |...........|...........|
+#> | U| 453.54485 | 92.28 | -5.919 | -1.019 | -0.1868 |
+#> |.....................| 2.209 | 2.226 | 0.009694 | 0.8882 |
+#> |.....................| 0.05529 | 0.7144 | 0.7517 | 1.294 |
+#> |.....................| 1.221 | 1.253 |...........|...........|
+#> | X| 453.54485 | 92.28 | 0.002688 | 0.2651 | 0.8296 |
+#> |.....................| 9.103 | 2.226 | 0.009694 | 0.8882 |
+#> |.....................| 0.05529 | 0.7144 | 0.7517 | 1.294 |
+#> |.....................| 1.221 | 1.253 |...........|...........|
+#> | 72| 453.87696 | 0.9902 | -1.606 | -0.9909 | -0.9627 |
+#> |.....................| -0.9313 | 0.9582 | -2.238 | -1.332 |
+#> |.....................| 0.7513 | -0.9138 | -1.018 | -0.7903 |
+#> |.....................| -0.7413 | -0.6822 |...........|...........|
+#> | U| 453.87696 | 92.21 | -5.909 | -1.019 | -0.1748 |
+#> |.....................| 2.205 | 2.219 | 0.009824 | 0.8908 |
+#> |.....................| 0.05474 | 0.7298 | 0.7487 | 1.307 |
+#> |.....................| 1.207 | 1.274 |...........|...........|
+#> | X| 453.87696 | 92.21 | 0.002714 | 0.2652 | 0.8396 |
+#> |.....................| 9.072 | 2.219 | 0.009824 | 0.8908 |
+#> |.....................| 0.05474 | 0.7298 | 0.7487 | 1.307 |
+#> |.....................| 1.207 | 1.274 |...........|...........|
+#> | 73| 452.40810 | 1.003 | -1.604 | -0.9910 | -0.9601 |
+#> |.....................| -0.9321 | 0.9550 | -2.236 | -1.332 |
+#> |.....................| 0.7430 | -0.9087 | -1.018 | -0.7892 |
+#> |.....................| -0.7449 | -0.6781 |...........|...........|
+#> | U| 452.4081 | 93.41 | -5.907 | -1.019 | -0.1722 |
+#> |.....................| 2.204 | 2.217 | 0.009851 | 0.8908 |
+#> |.....................| 0.05462 | 0.7337 | 0.7487 | 1.309 |
+#> |.....................| 1.203 | 1.278 |...........|...........|
+#> | X| 452.4081 | 93.41 | 0.002719 | 0.2652 | 0.8418 |
+#> |.....................| 9.065 | 2.217 | 0.009851 | 0.8908 |
+#> |.....................| 0.05462 | 0.7337 | 0.7487 | 1.309 |
+#> |.....................| 1.203 | 1.278 |...........|...........|
+#> | F| Forward Diff. | -20.28 | 0.3985 | -0.9900 | -0.3302 |
+#> |.....................| -0.4580 | -3.509 | -0.7634 | -5.125 |
+#> |.....................| -3.224 | 3.921 | 4.784 | -8.607 |
+#> |.....................| -4.910 | -1.049 |...........|...........|
+#> | 74| 452.35774 | 1.005 | -1.605 | -0.9906 | -0.9617 |
+#> |.....................| -0.9314 | 0.9567 | -2.238 | -1.332 |
+#> |.....................| 0.7462 | -0.9112 | -1.018 | -0.7890 |
+#> |.....................| -0.7417 | -0.6810 |...........|...........|
+#> | U| 452.35774 | 93.58 | -5.909 | -1.019 | -0.1738 |
+#> |.....................| 2.205 | 2.218 | 0.009828 | 0.8908 |
+#> |.....................| 0.05467 | 0.7317 | 0.7485 | 1.309 |
+#> |.....................| 1.207 | 1.275 |...........|...........|
+#> | X| 452.35774 | 93.58 | 0.002715 | 0.2652 | 0.8405 |
+#> |.....................| 9.072 | 2.218 | 0.009828 | 0.8908 |
+#> |.....................| 0.05467 | 0.7317 | 0.7485 | 1.309 |
+#> |.....................| 1.207 | 1.275 |...........|...........|
+#> | F| Forward Diff. | 9.319 | 0.4042 | -0.9262 | -0.3428 |
+#> |.....................| -0.3413 | -3.482 | -0.6441 | -5.151 |
+#> |.....................| -3.223 | 3.864 | 4.863 | -8.623 |
+#> |.....................| -4.770 | -1.217 |...........|...........|
+#> | 75| 452.31017 | 1.003 | -1.607 | -0.9902 | -0.9631 |
+#> |.....................| -0.9307 | 0.9586 | -2.239 | -1.332 |
+#> |.....................| 0.7493 | -0.9137 | -1.019 | -0.7876 |
+#> |.....................| -0.7383 | -0.6834 |...........|...........|
+#> | U| 452.31017 | 93.41 | -5.910 | -1.019 | -0.1752 |
+#> |.....................| 2.206 | 2.219 | 0.009807 | 0.8910 |
+#> |.....................| 0.05471 | 0.7298 | 0.7478 | 1.310 |
+#> |.....................| 1.210 | 1.273 |...........|...........|
+#> | X| 452.31017 | 93.41 | 0.002711 | 0.2653 | 0.8393 |
+#> |.....................| 9.078 | 2.219 | 0.009807 | 0.8910 |
+#> |.....................| 0.05471 | 0.7298 | 0.7478 | 1.310 |
+#> |.....................| 1.210 | 1.273 |...........|...........|
+#> | F| Forward Diff. | -20.20 | 0.3903 | -0.9767 | -0.3983 |
+#> |.....................| -0.4106 | -3.495 | -0.7375 | -5.052 |
+#> |.....................| -3.297 | 3.718 | 4.704 | -8.538 |
+#> |.....................| -4.606 | -1.295 |...........|...........|
+#> | 76| 452.25868 | 1.005 | -1.609 | -0.9898 | -0.9648 |
+#> |.....................| -0.9300 | 0.9604 | -2.241 | -1.332 |
+#> |.....................| 0.7529 | -0.9160 | -1.019 | -0.7870 |
+#> |.....................| -0.7354 | -0.6858 |...........|...........|
+#> | U| 452.25868 | 93.58 | -5.912 | -1.018 | -0.1770 |
+#> |.....................| 2.207 | 2.220 | 0.009778 | 0.8908 |
+#> |.....................| 0.05477 | 0.7281 | 0.7476 | 1.311 |
+#> |.....................| 1.213 | 1.270 |...........|...........|
+#> | X| 452.25868 | 93.58 | 0.002707 | 0.2654 | 0.8378 |
+#> |.....................| 9.084 | 2.220 | 0.009778 | 0.8908 |
+#> |.....................| 0.05477 | 0.7281 | 0.7476 | 1.311 |
+#> |.....................| 1.213 | 1.270 |...........|...........|
+#> | F| Forward Diff. | 8.768 | 0.3959 | -0.9108 | -0.4152 |
+#> |.....................| -0.2985 | -3.789 | -0.7277 | -5.480 |
+#> |.....................| -3.800 | 3.463 | 7.165 | -8.525 |
+#> |.....................| -4.480 | -1.429 |...........|...........|
+#> | 77| 452.20380 | 1.003 | -1.610 | -0.9896 | -0.9665 |
+#> |.....................| -0.9299 | 0.9625 | -2.243 | -1.331 |
+#> |.....................| 0.7574 | -0.9182 | -1.020 | -0.7855 |
+#> |.....................| -0.7330 | -0.6868 |...........|...........|
+#> | U| 452.2038 | 93.42 | -5.913 | -1.018 | -0.1787 |
+#> |.....................| 2.207 | 2.221 | 0.009753 | 0.8912 |
+#> |.....................| 0.05483 | 0.7265 | 0.7464 | 1.313 |
+#> |.....................| 1.216 | 1.269 |...........|...........|
+#> | X| 452.2038 | 93.42 | 0.002704 | 0.2654 | 0.8364 |
+#> |.....................| 9.085 | 2.221 | 0.009753 | 0.8912 |
+#> |.....................| 0.05483 | 0.7265 | 0.7464 | 1.313 |
+#> |.....................| 1.216 | 1.269 |...........|...........|
+#> | F| Forward Diff. | -17.51 | 0.3875 | -0.9566 | -0.4713 |
+#> |.....................| -0.3666 | -3.384 | -0.7134 | -4.862 |
+#> |.....................| -3.257 | 3.566 | 3.539 | -8.382 |
+#> |.....................| -4.308 | -1.428 |...........|...........|
+#> | 78| 452.15674 | 1.006 | -1.611 | -0.9895 | -0.9681 |
+#> |.....................| -0.9296 | 0.9646 | -2.244 | -1.331 |
+#> |.....................| 0.7624 | -0.9204 | -1.020 | -0.7847 |
+#> |.....................| -0.7317 | -0.6876 |...........|...........|
+#> | U| 452.15674 | 93.63 | -5.915 | -1.018 | -0.1803 |
+#> |.....................| 2.207 | 2.222 | 0.009729 | 0.8915 |
+#> |.....................| 0.05491 | 0.7248 | 0.7463 | 1.314 |
+#> |.....................| 1.217 | 1.268 |...........|...........|
+#> | X| 452.15674 | 93.63 | 0.002700 | 0.2654 | 0.8350 |
+#> |.....................| 9.088 | 2.222 | 0.009729 | 0.8915 |
+#> |.....................| 0.05491 | 0.7248 | 0.7463 | 1.314 |
+#> |.....................| 1.217 | 1.268 |...........|...........|
+#> | F| Forward Diff. | 16.34 | 0.3942 | -0.8917 | -0.4820 |
+#> |.....................| -0.2498 | -3.403 | -0.6022 | -5.023 |
+#> |.....................| -3.383 | 3.482 | 3.627 | -8.397 |
+#> |.....................| -4.266 | -1.517 |...........|...........|
+#> | 79| 452.11013 | 1.004 | -1.613 | -0.9892 | -0.9692 |
+#> |.....................| -0.9285 | 0.9667 | -2.245 | -1.330 |
+#> |.....................| 0.7674 | -0.9230 | -1.020 | -0.7840 |
+#> |.....................| -0.7312 | -0.6887 |...........|...........|
+#> | U| 452.11013 | 93.48 | -5.917 | -1.018 | -0.1814 |
+#> |.....................| 2.208 | 2.224 | 0.009710 | 0.8921 |
+#> |.....................| 0.05499 | 0.7229 | 0.7466 | 1.315 |
+#> |.....................| 1.218 | 1.267 |...........|...........|
+#> | X| 452.11013 | 93.48 | 0.002694 | 0.2655 | 0.8341 |
+#> |.....................| 9.098 | 2.224 | 0.009710 | 0.8921 |
+#> |.....................| 0.05499 | 0.7229 | 0.7466 | 1.315 |
+#> |.....................| 1.218 | 1.267 |...........|...........|
+#> | F| Forward Diff. | -8.858 | 0.3784 | -0.9339 | -0.5242 |
+#> |.....................| -0.2958 | -3.274 | -0.6451 | -4.716 |
+#> |.....................| -3.235 | 3.524 | 3.578 | -8.323 |
+#> |.....................| -4.226 | -1.527 |...........|...........|
+#> | 80| 452.06081 | 1.006 | -1.615 | -0.9885 | -0.9698 |
+#> |.....................| -0.9277 | 0.9688 | -2.247 | -1.329 |
+#> |.....................| 0.7723 | -0.9255 | -1.020 | -0.7822 |
+#> |.....................| -0.7302 | -0.6891 |...........|...........|
+#> | U| 452.06081 | 93.65 | -5.919 | -1.017 | -0.1820 |
+#> |.....................| 2.209 | 2.225 | 0.009693 | 0.8927 |
+#> |.....................| 0.05506 | 0.7209 | 0.7465 | 1.317 |
+#> |.....................| 1.219 | 1.266 |...........|...........|
+#> | X| 452.06081 | 93.65 | 0.002689 | 0.2656 | 0.8336 |
+#> |.....................| 9.105 | 2.225 | 0.009693 | 0.8927 |
+#> |.....................| 0.05506 | 0.7209 | 0.7465 | 1.317 |
+#> |.....................| 1.219 | 1.266 |...........|...........|
+#> | F| Forward Diff. | 18.08 | 0.3814 | -0.8701 | -0.5179 |
+#> |.....................| -0.1901 | -3.027 | -0.4828 | -4.583 |
+#> |.....................| -3.046 | 3.385 | 4.724 | -8.292 |
+#> |.....................| -4.215 | -1.583 |...........|...........|
+#> | 81| 452.00089 | 1.004 | -1.618 | -0.9864 | -0.9698 |
+#> |.....................| -0.9276 | 0.9701 | -2.249 | -1.331 |
+#> |.....................| 0.7751 | -0.9261 | -1.021 | -0.7787 |
+#> |.....................| -0.7281 | -0.6889 |...........|...........|
+#> | U| 452.00089 | 93.48 | -5.921 | -1.015 | -0.1820 |
+#> |.....................| 2.209 | 2.226 | 0.009656 | 0.8916 |
+#> |.....................| 0.05510 | 0.7205 | 0.7459 | 1.321 |
+#> |.....................| 1.221 | 1.267 |...........|...........|
+#> | X| 452.00089 | 93.48 | 0.002683 | 0.2660 | 0.8336 |
+#> |.....................| 9.107 | 2.226 | 0.009656 | 0.8916 |
+#> |.....................| 0.05510 | 0.7205 | 0.7459 | 1.321 |
+#> |.....................| 1.221 | 1.267 |...........|...........|
+#> | F| Forward Diff. | -8.141 | 0.3688 | -0.8752 | -0.5418 |
+#> |.....................| -0.2687 | -3.191 | -0.6153 | -4.612 |
+#> |.....................| -3.168 | 3.248 | 4.602 | -8.159 |
+#> |.....................| -4.118 | -1.545 |...........|...........|
+#> | 82| 451.94404 | 1.006 | -1.619 | -0.9850 | -0.9696 |
+#> |.....................| -0.9279 | 0.9711 | -2.251 | -1.332 |
+#> |.....................| 0.7767 | -0.9258 | -1.022 | -0.7739 |
+#> |.....................| -0.7256 | -0.6877 |...........|...........|
+#> | U| 451.94404 | 93.65 | -5.922 | -1.014 | -0.1817 |
+#> |.....................| 2.209 | 2.226 | 0.009627 | 0.8908 |
+#> |.....................| 0.05512 | 0.7207 | 0.7445 | 1.327 |
+#> |.....................| 1.224 | 1.268 |...........|...........|
+#> | X| 451.94404 | 93.65 | 0.002679 | 0.2663 | 0.8338 |
+#> |.....................| 9.104 | 2.226 | 0.009627 | 0.8908 |
+#> |.....................| 0.05512 | 0.7207 | 0.7445 | 1.327 |
+#> |.....................| 1.224 | 1.268 |...........|...........|
+#> | 83| 451.90577 | 1.006 | -1.621 | -0.9832 | -0.9693 |
+#> |.....................| -0.9284 | 0.9716 | -2.254 | -1.336 |
+#> |.....................| 0.7778 | -0.9242 | -1.023 | -0.7696 |
+#> |.....................| -0.7233 | -0.6864 |...........|...........|
+#> | U| 451.90577 | 93.65 | -5.925 | -1.012 | -0.1815 |
+#> |.....................| 2.208 | 2.227 | 0.009581 | 0.8887 |
+#> |.....................| 0.05514 | 0.7219 | 0.7437 | 1.332 |
+#> |.....................| 1.226 | 1.269 |...........|...........|
+#> | X| 451.90577 | 93.65 | 0.002673 | 0.2666 | 0.8340 |
+#> |.....................| 9.099 | 2.227 | 0.009581 | 0.8887 |
+#> |.....................| 0.05514 | 0.7219 | 0.7437 | 1.332 |
+#> |.....................| 1.226 | 1.269 |...........|...........|
+#> | 84| 451.74017 | 1.006 | -1.632 | -0.9740 | -0.9682 |
+#> |.....................| -0.9311 | 0.9738 | -2.270 | -1.354 |
+#> |.....................| 0.7839 | -0.9163 | -1.028 | -0.7474 |
+#> |.....................| -0.7117 | -0.6796 |...........|...........|
+#> | U| 451.74017 | 93.64 | -5.935 | -1.003 | -0.1804 |
+#> |.....................| 2.205 | 2.228 | 0.009348 | 0.8780 |
+#> |.....................| 0.05523 | 0.7279 | 0.7400 | 1.359 |
+#> |.....................| 1.239 | 1.277 |...........|...........|
+#> | X| 451.74017 | 93.64 | 0.002645 | 0.2683 | 0.8350 |
+#> |.....................| 9.074 | 2.228 | 0.009348 | 0.8780 |
+#> |.....................| 0.05523 | 0.7279 | 0.7400 | 1.359 |
+#> |.....................| 1.239 | 1.277 |...........|...........|
+#> | 85| 451.58673 | 1.005 | -1.675 | -0.9364 | -0.9637 |
+#> |.....................| -0.9422 | 0.9828 | -2.333 | -1.429 |
+#> |.....................| 0.8084 | -0.8841 | -1.045 | -0.6570 |
+#> |.....................| -0.6645 | -0.6522 |...........|...........|
+#> | U| 451.58673 | 93.57 | -5.978 | -0.9678 | -0.1758 |
+#> |.....................| 2.194 | 2.233 | 0.008399 | 0.8346 |
+#> |.....................| 0.05560 | 0.7523 | 0.7245 | 1.469 |
+#> |.....................| 1.289 | 1.306 |...........|...........|
+#> | X| 451.58673 | 93.57 | 0.002533 | 0.2753 | 0.8388 |
+#> |.....................| 8.974 | 2.233 | 0.008399 | 0.8346 |
+#> |.....................| 0.05560 | 0.7523 | 0.7245 | 1.469 |
+#> |.....................| 1.289 | 1.306 |...........|...........|
+#> | F| Forward Diff. | 7.829 | 0.3494 | 0.8366 | -0.4922 |
+#> |.....................| -0.7083 | -3.782 | -0.9020 | -9.523 |
+#> |.....................| -4.571 | 4.733 | 3.935 | -3.194 |
+#> |.....................| -1.280 | 0.5510 |...........|...........|
+#> | 86| 450.56328 | 1.003 | -1.760 | -0.9418 | -0.9563 |
+#> |.....................| -0.9480 | 1.050 | -2.445 | -1.421 |
+#> |.....................| 0.9402 | -0.9310 | -1.041 | -0.6107 |
+#> |.....................| -0.6547 | -0.6413 |...........|...........|
+#> | U| 450.56328 | 93.41 | -6.064 | -0.9728 | -0.1684 |
+#> |.....................| 2.189 | 2.272 | 0.006706 | 0.8396 |
+#> |.....................| 0.05758 | 0.7168 | 0.7280 | 1.525 |
+#> |.....................| 1.300 | 1.318 |...........|...........|
+#> | X| 450.56328 | 93.41 | 0.002326 | 0.2743 | 0.8450 |
+#> |.....................| 8.923 | 2.272 | 0.006706 | 0.8396 |
+#> |.....................| 0.05758 | 0.7168 | 0.7280 | 1.525 |
+#> |.....................| 1.300 | 1.318 |...........|...........|
+#> | 87| 449.70344 | 1.004 | -1.916 | -0.9511 | -0.9429 |
+#> |.....................| -0.9589 | 1.170 | -2.653 | -1.409 |
+#> |.....................| 1.180 | -1.015 | -1.032 | -0.5274 |
+#> |.....................| -0.6372 | -0.6210 |...........|...........|
+#> | U| 449.70344 | 93.47 | -6.220 | -0.9817 | -0.1550 |
+#> |.....................| 2.178 | 2.342 | 0.003591 | 0.8462 |
+#> |.....................| 0.06119 | 0.6534 | 0.7360 | 1.626 |
+#> |.....................| 1.318 | 1.340 |...........|...........|
+#> | X| 449.70344 | 93.47 | 0.001990 | 0.2726 | 0.8564 |
+#> |.....................| 8.826 | 2.342 | 0.003591 | 0.8462 |
+#> |.....................| 0.06119 | 0.6534 | 0.7360 | 1.626 |
+#> |.....................| 1.318 | 1.340 |...........|...........|
+#> | F| Forward Diff. | -19.90 | -0.3168 | 0.4549 | 0.1875 |
+#> |.....................| -1.116 | -0.4934 | -0.07687 | -3.113 |
+#> |.....................| -2.715 | -1.586 | 5.430 | 3.365 |
+#> |.....................| 0.3009 | 1.974 |...........|...........|
+#> | 88| 451.98935 | 1.002 | -1.890 | -1.062 | -1.052 |
+#> |.....................| -0.7983 | 1.243 | -2.828 | -1.513 |
+#> |.....................| 1.600 | -1.043 | -1.029 | -0.6268 |
+#> |.....................| -0.3463 | -0.6648 |...........|...........|
+#> | U| 451.98935 | 93.35 | -6.193 | -1.087 | -0.2643 |
+#> |.....................| 2.338 | 2.384 | 0.0009551 | 0.7857 |
+#> |.....................| 0.06749 | 0.6319 | 0.7389 | 1.506 |
+#> |.....................| 1.629 | 1.293 |...........|...........|
+#> | X| 451.98935 | 93.35 | 0.002043 | 0.2523 | 0.7677 |
+#> |.....................| 10.36 | 2.384 | 0.0009551 | 0.7857 |
+#> |.....................| 0.06749 | 0.6319 | 0.7389 | 1.506 |
+#> |.....................| 1.629 | 1.293 |...........|...........|
+#> | 89| 449.56377 | 1.005 | -1.911 | -0.9716 | -0.9631 |
+#> |.....................| -0.9292 | 1.184 | -2.685 | -1.428 |
+#> |.....................| 1.258 | -1.020 | -1.032 | -0.5459 |
+#> |.....................| -0.5835 | -0.6292 |...........|...........|
+#> | U| 449.56377 | 93.56 | -6.215 | -1.001 | -0.1752 |
+#> |.....................| 2.207 | 2.350 | 0.003105 | 0.8351 |
+#> |.....................| 0.06235 | 0.6495 | 0.7362 | 1.604 |
+#> |.....................| 1.376 | 1.331 |...........|...........|
+#> | X| 449.56377 | 93.56 | 0.002000 | 0.2687 | 0.8393 |
+#> |.....................| 9.092 | 2.350 | 0.003105 | 0.8351 |
+#> |.....................| 0.06235 | 0.6495 | 0.7362 | 1.604 |
+#> |.....................| 1.376 | 1.331 |...........|...........|
+#> | F| Forward Diff. | -8.503 | -0.3085 | -0.7128 | -0.4858 |
+#> |.....................| -0.1462 | -0.3349 | -0.04630 | -2.615 |
+#> |.....................| -2.539 | -1.761 | 5.421 | 2.664 |
+#> |.....................| 3.069 | 1.771 |...........|...........|
+#> | 90| 449.37295 | 1.008 | -1.883 | -0.9569 | -0.9753 |
+#> |.....................| -0.9112 | 1.201 | -2.710 | -1.458 |
+#> |.....................| 1.352 | -1.030 | -1.036 | -0.5467 |
+#> |.....................| -0.5933 | -0.6460 |...........|...........|
+#> | U| 449.37295 | 93.89 | -6.186 | -0.9871 | -0.1875 |
+#> |.....................| 2.225 | 2.360 | 0.002726 | 0.8181 |
+#> |.....................| 0.06377 | 0.6417 | 0.7326 | 1.603 |
+#> |.....................| 1.365 | 1.313 |...........|...........|
+#> | X| 449.37295 | 93.89 | 0.002058 | 0.2715 | 0.8291 |
+#> |.....................| 9.256 | 2.360 | 0.002726 | 0.8181 |
+#> |.....................| 0.06377 | 0.6417 | 0.7326 | 1.603 |
+#> |.....................| 1.365 | 1.313 |...........|...........|
+#> | F| Forward Diff. | 31.95 | -0.2055 | 0.2861 | -0.8772 |
+#> |.....................| 0.4589 | 0.008909 | 0.01409 | -2.994 |
+#> |.....................| -2.511 | -2.129 | 5.021 | 2.567 |
+#> |.....................| 2.446 | 1.004 |...........|...........|
+#> | 91| 449.07232 | 1.007 | -1.848 | -0.9883 | -0.9607 |
+#> |.....................| -0.9269 | 1.208 | -2.721 | -1.473 |
+#> |.....................| 1.446 | -1.013 | -1.041 | -0.5472 |
+#> |.....................| -0.6000 | -0.6251 |...........|...........|
+#> | U| 449.07232 | 93.73 | -6.151 | -1.017 | -0.1729 |
+#> |.....................| 2.210 | 2.364 | 0.002568 | 0.8093 |
+#> |.....................| 0.06518 | 0.6543 | 0.7283 | 1.602 |
+#> |.....................| 1.358 | 1.335 |...........|...........|
+#> | X| 449.07232 | 93.73 | 0.002130 | 0.2656 | 0.8412 |
+#> |.....................| 9.113 | 2.364 | 0.002568 | 0.8093 |
+#> |.....................| 0.06518 | 0.6543 | 0.7283 | 1.602 |
+#> |.....................| 1.358 | 1.335 |...........|...........|
+#> | 92| 449.34581 | 1.013 | -1.744 | -1.083 | -0.9172 |
+#> |.....................| -0.9739 | 1.229 | -2.752 | -1.520 |
+#> |.....................| 1.728 | -0.9642 | -1.054 | -0.5478 |
+#> |.....................| -0.6192 | -0.5619 |...........|...........|
+#> | U| 449.34581 | 94.33 | -6.047 | -1.106 | -0.1294 |
+#> |.....................| 2.163 | 2.376 | 0.002092 | 0.7821 |
+#> |.....................| 0.06942 | 0.6916 | 0.7169 | 1.601 |
+#> |.....................| 1.337 | 1.403 |...........|...........|
+#> | X| 449.34581 | 94.33 | 0.002364 | 0.2486 | 0.8787 |
+#> |.....................| 8.694 | 2.376 | 0.002092 | 0.7821 |
+#> |.....................| 0.06942 | 0.6916 | 0.7169 | 1.601 |
+#> |.....................| 1.337 | 1.403 |...........|...........|
+#> | F| Forward Diff. | 11.36 | -0.08356 | -1.544 | -0.3785 |
+#> |.....................| -0.02879 | 0.1985 | 0.04898 | -2.532 |
+#> |.....................| -2.210 | -1.428 | 5.624 | 2.440 |
+#> |.....................| 2.104 | 1.894 |...........|...........|
+#> | 93| 449.83746 | 0.9966 | -1.806 | -0.8436 | -0.9213 |
+#> |.....................| -1.016 | 1.236 | -2.752 | -1.567 |
+#> |.....................| 1.816 | -1.085 | -1.056 | -0.6567 |
+#> |.....................| -0.5363 | -0.5852 |...........|...........|
+#> | U| 449.83746 | 92.80 | -6.109 | -0.8802 | -0.1335 |
+#> |.....................| 2.121 | 2.380 | 0.002093 | 0.7548 |
+#> |.....................| 0.07074 | 0.5997 | 0.7149 | 1.469 |
+#> |.....................| 1.426 | 1.378 |...........|...........|
+#> | X| 449.83746 | 92.80 | 0.002222 | 0.2931 | 0.8750 |
+#> |.....................| 8.340 | 2.380 | 0.002093 | 0.7548 |
+#> |.....................| 0.07074 | 0.5997 | 0.7149 | 1.469 |
+#> |.....................| 1.426 | 1.378 |...........|...........|
+#> | 94| 449.05525 | 1.000 | -1.836 | -0.9477 | -0.9497 |
+#> |.....................| -0.9515 | 1.216 | -2.730 | -1.498 |
+#> |.....................| 1.549 | -1.033 | -1.047 | -0.5784 |
+#> |.....................| -0.5830 | -0.6146 |...........|...........|
+#> | U| 449.05525 | 93.13 | -6.140 | -0.9784 | -0.1618 |
+#> |.....................| 2.185 | 2.368 | 0.002436 | 0.7946 |
+#> |.....................| 0.06673 | 0.6395 | 0.7230 | 1.564 |
+#> |.....................| 1.376 | 1.346 |...........|...........|
+#> | X| 449.05525 | 93.13 | 0.002156 | 0.2732 | 0.8506 |
+#> |.....................| 8.891 | 2.368 | 0.002436 | 0.7946 |
+#> |.....................| 0.06673 | 0.6395 | 0.7230 | 1.564 |
+#> |.....................| 1.376 | 1.346 |...........|...........|
+#> | F| Forward Diff. | -56.82 | -0.05113 | 0.4930 | -0.04031 |
+#> |.....................| -1.049 | 0.03445 | -0.05944 | -2.319 |
+#> |.....................| -2.208 | -2.328 | 3.545 | 0.3775 |
+#> |.....................| 2.643 | 2.387 |...........|...........|
+#> | 95| 448.75128 | 1.006 | -1.837 | -0.9543 | -0.9497 |
+#> |.....................| -0.9537 | 1.219 | -2.732 | -1.514 |
+#> |.....................| 1.608 | -1.030 | -1.050 | -0.5750 |
+#> |.....................| -0.5860 | -0.6263 |...........|...........|
+#> | U| 448.75128 | 93.69 | -6.140 | -0.9847 | -0.1618 |
+#> |.....................| 2.183 | 2.370 | 0.002396 | 0.7854 |
+#> |.....................| 0.06761 | 0.6415 | 0.7208 | 1.568 |
+#> |.....................| 1.373 | 1.334 |...........|...........|
+#> | X| 448.75128 | 93.69 | 0.002154 | 0.2720 | 0.8506 |
+#> |.....................| 8.872 | 2.370 | 0.002396 | 0.7854 |
+#> |.....................| 0.06761 | 0.6415 | 0.7208 | 1.568 |
+#> |.....................| 1.373 | 1.334 |...........|...........|
+#> | F| Forward Diff. | 6.795 | -0.02569 | 0.3964 | 0.03329 |
+#> |.....................| -0.8574 | 0.1774 | 0.01390 | -2.462 |
+#> |.....................| -2.149 | -2.476 | 3.910 | 1.045 |
+#> |.....................| 2.743 | 2.014 |...........|...........|
+#> | 96| 448.60805 | 1.005 | -1.844 | -0.9658 | -0.9658 |
+#> |.....................| -0.9330 | 1.222 | -2.731 | -1.528 |
+#> |.....................| 1.652 | -1.023 | -1.051 | -0.5597 |
+#> |.....................| -0.5993 | -0.6478 |...........|...........|
+#> | U| 448.60805 | 93.55 | -6.147 | -0.9955 | -0.1780 |
+#> |.....................| 2.204 | 2.372 | 0.002406 | 0.7773 |
+#> |.....................| 0.06828 | 0.6470 | 0.7198 | 1.587 |
+#> |.....................| 1.359 | 1.311 |...........|...........|
+#> | X| 448.60805 | 93.55 | 0.002140 | 0.2698 | 0.8370 |
+#> |.....................| 9.057 | 2.372 | 0.002406 | 0.7773 |
+#> |.....................| 0.06828 | 0.6470 | 0.7198 | 1.587 |
+#> |.....................| 1.359 | 1.311 |...........|...........|
+#> | 97| 448.54893 | 1.004 | -1.854 | -0.9831 | -0.9905 |
+#> |.....................| -0.9018 | 1.226 | -2.730 | -1.550 |
+#> |.....................| 1.719 | -1.013 | -1.051 | -0.5361 |
+#> |.....................| -0.6188 | -0.6800 |...........|...........|
+#> | U| 448.54893 | 93.53 | -6.157 | -1.012 | -0.2026 |
+#> |.....................| 2.235 | 2.374 | 0.002422 | 0.7645 |
+#> |.....................| 0.06928 | 0.6548 | 0.7192 | 1.616 |
+#> |.....................| 1.338 | 1.276 |...........|...........|
+#> | X| 448.54893 | 93.53 | 0.002118 | 0.2666 | 0.8166 |
+#> |.....................| 9.344 | 2.374 | 0.002422 | 0.7645 |
+#> |.....................| 0.06928 | 0.6548 | 0.7192 | 1.616 |
+#> |.....................| 1.338 | 1.276 |...........|...........|
+#> | F| Forward Diff. | -11.31 | -0.05480 | -1.344 | -1.332 |
+#> |.....................| 0.5363 | 0.1616 | -0.02955 | -2.282 |
+#> |.....................| -1.949 | -1.541 | 5.051 | 2.875 |
+#> |.....................| 1.005 | -0.6800 |...........|...........|
+#> | 98| 448.23423 | 1.005 | -1.862 | -0.9802 | -0.9885 |
+#> |.....................| -0.8649 | 1.225 | -2.731 | -1.570 |
+#> |.....................| 1.863 | -0.9934 | -1.058 | -0.5422 |
+#> |.....................| -0.6330 | -0.6404 |...........|...........|
+#> | U| 448.23423 | 93.60 | -6.165 | -1.009 | -0.2007 |
+#> |.....................| 2.272 | 2.374 | 0.002415 | 0.7529 |
+#> |.....................| 0.07145 | 0.6695 | 0.7131 | 1.608 |
+#> |.....................| 1.323 | 1.319 |...........|...........|
+#> | X| 448.23423 | 93.60 | 0.002101 | 0.2671 | 0.8182 |
+#> |.....................| 9.695 | 2.374 | 0.002415 | 0.7529 |
+#> |.....................| 0.07145 | 0.6695 | 0.7131 | 1.608 |
+#> |.....................| 1.323 | 1.319 |...........|...........|
+#> | 99| 448.52797 | 1.003 | -1.887 | -0.9721 | -0.9832 |
+#> |.....................| -0.7539 | 1.222 | -2.732 | -1.631 |
+#> |.....................| 2.296 | -0.9358 | -1.078 | -0.5592 |
+#> |.....................| -0.6753 | -0.5215 |...........|...........|
+#> | U| 448.52797 | 93.41 | -6.190 | -1.001 | -0.1954 |
+#> |.....................| 2.383 | 2.371 | 0.002396 | 0.7173 |
+#> |.....................| 0.07796 | 0.7131 | 0.6963 | 1.588 |
+#> |.....................| 1.277 | 1.446 |...........|...........|
+#> | X| 448.52797 | 93.41 | 0.002050 | 0.2687 | 0.8225 |
+#> |.....................| 10.83 | 2.371 | 0.002396 | 0.7173 |
+#> |.....................| 0.07796 | 0.7131 | 0.6963 | 1.588 |
+#> |.....................| 1.277 | 1.446 |...........|...........|
+#> | F| Forward Diff. | -1.417 | -0.03842 | -1.058 | -1.257 |
+#> |.....................| 1.697 | 0.2446 | 0.02601 | -1.725 |
+#> |.....................| -1.728 | -0.7541 | 3.822 | 2.423 |
+#> |.....................| 0.4552 | 1.132 |...........|...........|
+#> | 100| 447.48636 | 1.010 | -1.889 | -1.018 | -0.9136 |
+#> |.....................| -0.9465 | 1.241 | -2.741 | -1.706 |
+#> |.....................| 2.465 | -0.9635 | -1.095 | -0.5705 |
+#> |.....................| -0.6276 | -0.6598 |...........|...........|
+#> | U| 447.48636 | 94.00 | -6.193 | -1.045 | -0.1257 |
+#> |.....................| 2.190 | 2.383 | 0.002265 | 0.6743 |
+#> |.....................| 0.08050 | 0.6921 | 0.6807 | 1.574 |
+#> |.....................| 1.328 | 1.298 |...........|...........|
+#> | X| 447.48636 | 94.00 | 0.002044 | 0.2602 | 0.8818 |
+#> |.....................| 8.935 | 2.383 | 0.002265 | 0.6743 |
+#> |.....................| 0.08050 | 0.6921 | 0.6807 | 1.574 |
+#> |.....................| 1.328 | 1.298 |...........|...........|
+#> | F| Forward Diff. | 49.18 | 0.06228 | -2.520 | 1.219 |
+#> |.....................| -0.3402 | 0.5332 | 0.01803 | -1.013 |
+#> |.....................| -0.7363 | 0.9697 | 2.720 | 0.6118 |
+#> |.....................| 0.4882 | -0.1519 |...........|...........|
+#> | 101| 448.59314 | 1.009 | -1.906 | -0.9798 | -1.202 |
+#> |.....................| -1.107 | 1.243 | -2.730 | -1.791 |
+#> |.....................| 2.989 | -0.9474 | -1.110 | -0.5914 |
+#> |.....................| -0.6423 | -0.5882 |...........|...........|
+#> | U| 448.59314 | 93.96 | -6.209 | -1.009 | -0.4139 |
+#> |.....................| 2.029 | 2.384 | 0.002422 | 0.6247 |
+#> |.....................| 0.08837 | 0.7043 | 0.6679 | 1.549 |
+#> |.....................| 1.313 | 1.375 |...........|...........|
+#> | X| 448.59314 | 93.96 | 0.002010 | 0.2672 | 0.6611 |
+#> |.....................| 7.610 | 2.384 | 0.002422 | 0.6247 |
+#> |.....................| 0.08837 | 0.7043 | 0.6679 | 1.549 |
+#> |.....................| 1.313 | 1.375 |...........|...........|
+#> | 102| 447.34338 | 1.004 | -1.893 | -1.010 | -0.9727 |
+#> |.....................| -0.9794 | 1.241 | -2.739 | -1.723 |
+#> |.....................| 2.572 | -0.9603 | -1.099 | -0.5748 |
+#> |.....................| -0.6307 | -0.6452 |...........|...........|
+#> | U| 447.34338 | 93.48 | -6.196 | -1.037 | -0.1848 |
+#> |.....................| 2.157 | 2.383 | 0.002297 | 0.6642 |
+#> |.....................| 0.08211 | 0.6946 | 0.6778 | 1.569 |
+#> |.....................| 1.325 | 1.314 |...........|...........|
+#> | X| 447.34338 | 93.48 | 0.002037 | 0.2617 | 0.8313 |
+#> |.....................| 8.647 | 2.383 | 0.002297 | 0.6642 |
+#> |.....................| 0.08211 | 0.6946 | 0.6778 | 1.569 |
+#> |.....................| 1.325 | 1.314 |...........|...........|
+#> | F| Forward Diff. | -27.99 | 0.05620 | -2.283 | -0.5861 |
+#> |.....................| -1.399 | 0.3409 | -0.05316 | -0.7185 |
+#> |.....................| -0.6589 | 0.7167 | 1.472 | 0.2167 |
+#> |.....................| 0.2339 | 0.7351 |...........|...........|
+#> | 103| 447.24116 | 1.004 | -1.898 | -0.9880 | -0.9438 |
+#> |.....................| -0.9421 | 1.243 | -2.723 | -1.759 |
+#> |.....................| 2.683 | -0.9737 | -1.096 | -0.5790 |
+#> |.....................| -0.6284 | -0.6557 |...........|...........|
+#> | U| 447.24116 | 93.50 | -6.201 | -1.017 | -0.1559 |
+#> |.....................| 2.195 | 2.384 | 0.002530 | 0.6435 |
+#> |.....................| 0.08377 | 0.6844 | 0.6802 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | X| 447.24116 | 93.50 | 0.002027 | 0.2657 | 0.8556 |
+#> |.....................| 8.976 | 2.384 | 0.002530 | 0.6435 |
+#> |.....................| 0.08377 | 0.6844 | 0.6802 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | F| Forward Diff. | -22.25 | 0.02611 | -1.124 | 0.2366 |
+#> |.....................| -0.4078 | 0.2597 | -0.06938 | -0.8187 |
+#> |.....................| -0.5375 | 0.002218 | 1.533 | -0.1306 |
+#> |.....................| 0.2372 | 0.1318 |...........|...........|
+#> | 104| 447.36545 | 1.010 | -1.910 | -0.9563 | -1.018 |
+#> |.....................| -0.9640 | 1.238 | -2.696 | -1.806 |
+#> |.....................| 2.921 | -0.9760 | -1.100 | -0.5866 |
+#> |.....................| -0.6320 | -0.6434 |...........|...........|
+#> | U| 447.36545 | 94.05 | -6.214 | -0.9866 | -0.2304 |
+#> |.....................| 2.173 | 2.381 | 0.002941 | 0.6159 |
+#> |.....................| 0.08734 | 0.6827 | 0.6770 | 1.554 |
+#> |.....................| 1.324 | 1.315 |...........|...........|
+#> | X| 447.36545 | 94.05 | 0.002002 | 0.2716 | 0.7942 |
+#> |.....................| 8.780 | 2.381 | 0.002941 | 0.6159 |
+#> |.....................| 0.08734 | 0.6827 | 0.6770 | 1.554 |
+#> |.....................| 1.324 | 1.315 |...........|...........|
+#> | 105| 447.25244 | 1.009 | -1.902 | -0.9770 | -0.9694 |
+#> |.....................| -0.9495 | 1.241 | -2.714 | -1.775 |
+#> |.....................| 2.765 | -0.9745 | -1.097 | -0.5816 |
+#> |.....................| -0.6297 | -0.6515 |...........|...........|
+#> | U| 447.25244 | 93.94 | -6.205 | -1.006 | -0.1815 |
+#> |.....................| 2.187 | 2.383 | 0.002671 | 0.6341 |
+#> |.....................| 0.08500 | 0.6838 | 0.6790 | 1.560 |
+#> |.....................| 1.326 | 1.307 |...........|...........|
+#> | X| 447.25244 | 93.94 | 0.002018 | 0.2677 | 0.8340 |
+#> |.....................| 8.909 | 2.383 | 0.002671 | 0.6341 |
+#> |.....................| 0.08500 | 0.6838 | 0.6790 | 1.560 |
+#> |.....................| 1.326 | 1.307 |...........|...........|
+#> | 106| 447.24908 | 1.008 | -1.900 | -0.9828 | -0.9557 |
+#> |.....................| -0.9455 | 1.242 | -2.719 | -1.766 |
+#> |.....................| 2.721 | -0.9741 | -1.097 | -0.5802 |
+#> |.....................| -0.6290 | -0.6537 |...........|...........|
+#> | U| 447.24908 | 93.91 | -6.203 | -1.012 | -0.1678 |
+#> |.....................| 2.191 | 2.383 | 0.002596 | 0.6392 |
+#> |.....................| 0.08434 | 0.6841 | 0.6795 | 1.562 |
+#> |.....................| 1.327 | 1.304 |...........|...........|
+#> | X| 447.24908 | 93.91 | 0.002023 | 0.2667 | 0.8455 |
+#> |.....................| 8.945 | 2.383 | 0.002596 | 0.6392 |
+#> |.....................| 0.08434 | 0.6841 | 0.6795 | 1.562 |
+#> |.....................| 1.327 | 1.304 |...........|...........|
+#> | 107| 447.25180 | 1.008 | -1.899 | -0.9855 | -0.9493 |
+#> |.....................| -0.9436 | 1.242 | -2.721 | -1.762 |
+#> |.....................| 2.700 | -0.9739 | -1.097 | -0.5796 |
+#> |.....................| -0.6287 | -0.6548 |...........|...........|
+#> | U| 447.2518 | 93.89 | -6.202 | -1.014 | -0.1614 |
+#> |.....................| 2.193 | 2.383 | 0.002560 | 0.6416 |
+#> |.....................| 0.08403 | 0.6843 | 0.6798 | 1.563 |
+#> |.....................| 1.327 | 1.303 |...........|...........|
+#> | X| 447.2518 | 93.89 | 0.002025 | 0.2662 | 0.8509 |
+#> |.....................| 8.962 | 2.383 | 0.002560 | 0.6416 |
+#> |.....................| 0.08403 | 0.6843 | 0.6798 | 1.563 |
+#> |.....................| 1.327 | 1.303 |...........|...........|
+#> | 108| 447.25421 | 1.008 | -1.898 | -0.9869 | -0.9460 |
+#> |.....................| -0.9426 | 1.242 | -2.722 | -1.760 |
+#> |.....................| 2.690 | -0.9738 | -1.096 | -0.5792 |
+#> |.....................| -0.6286 | -0.6553 |...........|...........|
+#> | U| 447.25421 | 93.88 | -6.202 | -1.015 | -0.1582 |
+#> |.....................| 2.194 | 2.384 | 0.002542 | 0.6428 |
+#> |.....................| 0.08388 | 0.6843 | 0.6799 | 1.563 |
+#> |.....................| 1.327 | 1.303 |...........|...........|
+#> | X| 447.25421 | 93.88 | 0.002026 | 0.2659 | 0.8537 |
+#> |.....................| 8.970 | 2.384 | 0.002542 | 0.6428 |
+#> |.....................| 0.08388 | 0.6843 | 0.6799 | 1.563 |
+#> |.....................| 1.327 | 1.303 |...........|...........|
+#> | 109| 447.24978 | 1.008 | -1.898 | -0.9878 | -0.9438 |
+#> |.....................| -0.9420 | 1.242 | -2.723 | -1.759 |
+#> |.....................| 2.683 | -0.9737 | -1.096 | -0.5790 |
+#> |.....................| -0.6285 | -0.6557 |...........|...........|
+#> | U| 447.24978 | 93.86 | -6.201 | -1.016 | -0.1560 |
+#> |.....................| 2.195 | 2.384 | 0.002530 | 0.6436 |
+#> |.....................| 0.08377 | 0.6844 | 0.6800 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | X| 447.24978 | 93.86 | 0.002027 | 0.2657 | 0.8556 |
+#> |.....................| 8.976 | 2.384 | 0.002530 | 0.6436 |
+#> |.....................| 0.08377 | 0.6844 | 0.6800 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | 110| 447.22094 | 1.006 | -1.898 | -0.9879 | -0.9438 |
+#> |.....................| -0.9420 | 1.243 | -2.723 | -1.759 |
+#> |.....................| 2.683 | -0.9737 | -1.096 | -0.5790 |
+#> |.....................| -0.6284 | -0.6557 |...........|...........|
+#> | U| 447.22094 | 93.66 | -6.201 | -1.016 | -0.1560 |
+#> |.....................| 2.195 | 2.384 | 0.002530 | 0.6435 |
+#> |.....................| 0.08377 | 0.6844 | 0.6801 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | X| 447.22094 | 93.66 | 0.002027 | 0.2657 | 0.8556 |
+#> |.....................| 8.976 | 2.384 | 0.002530 | 0.6435 |
+#> |.....................| 0.08377 | 0.6844 | 0.6801 | 1.564 |
+#> |.....................| 1.328 | 1.302 |...........|...........|
+#> | F| Forward Diff. | 0.7136 | 0.03206 | -1.028 | 0.2620 |
+#> |.....................| -0.3312 | 0.3050 | -0.05505 | -0.8960 |
+#> |.....................| -0.4549 | 0.03409 | 2.494 | -0.1555 |
+#> |.....................| 0.2265 | 0.1085 |...........|...........|
+#> | 111| 447.21344 | 1.005 | -1.898 | -0.9873 | -0.9440 |
+#> |.....................| -0.9418 | 1.242 | -2.723 | -1.758 |
+#> |.....................| 2.683 | -0.9737 | -1.098 | -0.5789 |
+#> |.....................| -0.6286 | -0.6557 |...........|...........|
+#> | U| 447.21344 | 93.62 | -6.201 | -1.016 | -0.1561 |
+#> |.....................| 2.195 | 2.384 | 0.002531 | 0.6439 |
+#> |.....................| 0.08377 | 0.6844 | 0.6789 | 1.564 |
+#> |.....................| 1.327 | 1.302 |...........|...........|
+#> | X| 447.21344 | 93.62 | 0.002027 | 0.2658 | 0.8555 |
+#> |.....................| 8.978 | 2.384 | 0.002531 | 0.6439 |
+#> |.....................| 0.08377 | 0.6844 | 0.6789 | 1.564 |
+#> |.....................| 1.327 | 1.302 |...........|...........|
+#> | F| Forward Diff. | -4.689 | 0.03686 | -1.013 | 0.2539 |
+#> |.....................| -0.3408 | 0.6592 | 0.03740 | -0.5502 |
+#> |.....................| -0.2201 | 0.3219 | 2.382 | -0.1778 |
+#> |.....................| 0.2028 | 0.08770 |...........|...........|
+#> | 112| 447.19216 | 1.006 | -1.899 | -0.9854 | -0.9463 |
+#> |.....................| -0.9420 | 1.239 | -2.724 | -1.756 |
+#> |.....................| 2.680 | -0.9744 | -1.101 | -0.5784 |
+#> |.....................| -0.6293 | -0.6560 |...........|...........|
+#> | U| 447.19216 | 93.64 | -6.203 | -1.014 | -0.1585 |
+#> |.....................| 2.195 | 2.382 | 0.002523 | 0.6453 |
+#> |.....................| 0.08373 | 0.6839 | 0.6759 | 1.564 |
+#> |.....................| 1.327 | 1.302 |...........|...........|
+#> | X| 447.19216 | 93.64 | 0.002024 | 0.2662 | 0.8535 |
+#> |.....................| 8.976 | 2.382 | 0.002523 | 0.6453 |
+#> |.....................| 0.08373 | 0.6839 | 0.6759 | 1.564 |
+#> |.....................| 1.327 | 1.302 |...........|...........|
+#> | 113| 447.14896 | 1.005 | -1.904 | -0.9796 | -0.9535 |
+#> |.....................| -0.9426 | 1.230 | -2.725 | -1.748 |
+#> |.....................| 2.670 | -0.9764 | -1.111 | -0.5767 |
+#> |.....................| -0.6315 | -0.6570 |...........|...........|
+#> | U| 447.14896 | 93.56 | -6.208 | -1.009 | -0.1657 |
+#> |.....................| 2.194 | 2.376 | 0.002500 | 0.6498 |
+#> |.....................| 0.08358 | 0.6823 | 0.6675 | 1.566 |
+#> |.....................| 1.324 | 1.301 |...........|...........|
+#> | X| 447.14896 | 93.56 | 0.002014 | 0.2673 | 0.8473 |
+#> |.....................| 8.971 | 2.376 | 0.002500 | 0.6498 |
+#> |.....................| 0.08358 | 0.6823 | 0.6675 | 1.566 |
+#> |.....................| 1.324 | 1.301 |...........|...........|
+#> | 114| 447.12523 | 1.003 | -1.923 | -0.9566 | -0.9821 |
+#> |.....................| -0.9448 | 1.194 | -2.731 | -1.717 |
+#> |.....................| 2.632 | -0.9846 | -1.149 | -0.5701 |
+#> |.....................| -0.6401 | -0.6607 |...........|...........|
+#> | U| 447.12523 | 93.36 | -6.227 | -0.9868 | -0.1943 |
+#> |.....................| 2.192 | 2.355 | 0.002410 | 0.6677 |
+#> |.....................| 0.08300 | 0.6762 | 0.6336 | 1.574 |
+#> |.....................| 1.315 | 1.297 |...........|...........|
+#> | X| 447.12523 | 93.36 | 0.001976 | 0.2715 | 0.8234 |
+#> |.....................| 8.951 | 2.355 | 0.002410 | 0.6677 |
+#> |.....................| 0.08300 | 0.6762 | 0.6336 | 1.574 |
+#> |.....................| 1.315 | 1.297 |...........|...........|
+#> | F| Forward Diff. | -42.78 | 0.1470 | 0.5793 | -0.8455 |
+#> |.....................| -0.3546 | -0.4331 | -0.1071 | -0.02049 |
+#> |.....................| -0.3358 | -0.3904 | -2.177 | 0.2043 |
+#> |.....................| -0.1377 | -0.3207 |...........|...........|
+#> | 115| 447.09924 | 1.007 | -1.940 | -0.9416 | -1.018 |
+#> |.....................| -0.9550 | 1.181 | -2.719 | -1.734 |
+#> |.....................| 2.734 | -0.9861 | -1.153 | -0.5706 |
+#> |.....................| -0.6433 | -0.6564 |...........|...........|
+#> | U| 447.09924 | 93.80 | -6.243 | -0.9727 | -0.2297 |
+#> |.....................| 2.182 | 2.348 | 0.002591 | 0.6578 |
+#> |.....................| 0.08453 | 0.6750 | 0.6303 | 1.574 |
+#> |.....................| 1.312 | 1.301 |...........|...........|
+#> | X| 447.09924 | 93.80 | 0.001943 | 0.2743 | 0.7947 |
+#> |.....................| 8.860 | 2.348 | 0.002591 | 0.6578 |
+#> |.....................| 0.08453 | 0.6750 | 0.6303 | 1.574 |
+#> |.....................| 1.312 | 1.301 |...........|...........|
+#> | F| Forward Diff. | 15.04 | 0.1387 | 1.646 | -1.777 |
+#> |.....................| -0.3749 | -0.5049 | -0.07528 | 0.1505 |
+#> |.....................| -0.2071 | -0.6675 | -2.129 | 0.2735 |
+#> |.....................| -0.05533 | -0.2849 |...........|...........|
+#> | 116| 447.06926 | 1.008 | -1.968 | -0.9759 | -0.9363 |
+#> |.....................| -0.9300 | 1.192 | -2.714 | -1.733 |
+#> |.....................| 2.676 | -0.9757 | -1.142 | -0.5672 |
+#> |.....................| -0.6383 | -0.6598 |...........|...........|
+#> | U| 447.06926 | 93.90 | -6.272 | -1.005 | -0.1484 |
+#> |.....................| 2.207 | 2.354 | 0.002664 | 0.6586 |
+#> |.....................| 0.08367 | 0.6829 | 0.6398 | 1.578 |
+#> |.....................| 1.317 | 1.298 |...........|...........|
+#> | X| 447.06926 | 93.90 | 0.001889 | 0.2679 | 0.8621 |
+#> |.....................| 9.084 | 2.354 | 0.002664 | 0.6586 |
+#> |.....................| 0.08367 | 0.6829 | 0.6398 | 1.578 |
+#> |.....................| 1.317 | 1.298 |...........|...........|
+#> | F| Forward Diff. | 31.57 | 0.06960 | -0.1881 | 0.5445 |
+#> |.....................| 0.2088 | -0.3879 | -0.06801 | -0.3419 |
+#> |.....................| -0.4021 | 0.02711 | -1.273 | 0.2199 |
+#> |.....................| -0.1004 | -0.4182 |...........|...........|
+#> | 117| 447.12806 | 1.006 | -2.047 | -0.9734 | -0.9587 |
+#> |.....................| -0.9336 | 1.189 | -2.704 | -1.764 |
+#> |.....................| 2.737 | -0.9879 | -1.112 | -0.5826 |
+#> |.....................| -0.6349 | -0.6438 |...........|...........|
+#> | U| 447.12806 | 93.67 | -6.350 | -1.003 | -0.1708 |
+#> |.....................| 2.203 | 2.352 | 0.002825 | 0.6405 |
+#> |.....................| 0.08458 | 0.6737 | 0.6664 | 1.559 |
+#> |.....................| 1.321 | 1.315 |...........|...........|
+#> | X| 447.12806 | 93.67 | 0.001747 | 0.2684 | 0.8430 |
+#> |.....................| 9.052 | 2.352 | 0.002825 | 0.6405 |
+#> |.....................| 0.08458 | 0.6737 | 0.6664 | 1.559 |
+#> |.....................| 1.321 | 1.315 |...........|...........|
+#> | 118| 447.05003 | 1.006 | -1.997 | -0.9750 | -0.9445 |
+#> |.....................| -0.9313 | 1.191 | -2.710 | -1.744 |
+#> |.....................| 2.698 | -0.9801 | -1.131 | -0.5728 |
+#> |.....................| -0.6370 | -0.6539 |...........|...........|
+#> | U| 447.05003 | 93.71 | -6.300 | -1.004 | -0.1566 |
+#> |.....................| 2.205 | 2.354 | 0.002723 | 0.6520 |
+#> |.....................| 0.08400 | 0.6796 | 0.6495 | 1.571 |
+#> |.....................| 1.318 | 1.304 |...........|...........|
+#> | X| 447.05003 | 93.71 | 0.001836 | 0.2681 | 0.8551 |
+#> |.....................| 9.073 | 2.354 | 0.002723 | 0.6520 |
+#> |.....................| 0.08400 | 0.6796 | 0.6495 | 1.571 |
+#> |.....................| 1.318 | 1.304 |...........|...........|
+#> | F| Forward Diff. | 4.860 | -0.01375 | -0.2473 | 0.2780 |
+#> |.....................| 0.08862 | -0.4372 | -0.08802 | -0.3404 |
+#> |.....................| -0.3654 | -0.2345 | -0.3468 | 0.08396 |
+#> |.....................| -0.01035 | -0.06837 |...........|...........|
+#> | 119| 447.04716 | 1.006 | -1.989 | -0.9725 | -0.9518 |
+#> |.....................| -0.9334 | 1.193 | -2.718 | -1.756 |
+#> |.....................| 2.735 | -0.9825 | -1.129 | -0.5738 |
+#> |.....................| -0.6372 | -0.6523 |...........|...........|
+#> | U| 447.04716 | 93.69 | -6.292 | -1.002 | -0.1639 |
+#> |.....................| 2.203 | 2.355 | 0.002610 | 0.6452 |
+#> |.....................| 0.08456 | 0.6777 | 0.6509 | 1.570 |
+#> |.....................| 1.318 | 1.306 |...........|...........|
+#> | X| 447.04716 | 93.69 | 0.001850 | 0.2686 | 0.8488 |
+#> |.....................| 9.053 | 2.355 | 0.002610 | 0.6452 |
+#> |.....................| 0.08456 | 0.6777 | 0.6509 | 1.570 |
+#> |.....................| 1.318 | 1.306 |...........|...........|
+#> | F| Forward Diff. | 2.456 | -0.007589 | -0.1181 | 0.06051 |
+#> |.....................| 0.03158 | -0.4028 | -0.08358 | -0.4018 |
+#> |.....................| -0.3358 | -0.3459 | -0.2609 | 0.03632 |
+#> |.....................| -0.03277 | 0.02331 |...........|...........|
+#> | 120| 447.04716 | 1.006 | -1.989 | -0.9725 | -0.9518 |
+#> |.....................| -0.9334 | 1.193 | -2.718 | -1.756 |
+#> |.....................| 2.735 | -0.9825 | -1.129 | -0.5738 |
+#> |.....................| -0.6372 | -0.6523 |...........|...........|
+#> | U| 447.04716 | 93.69 | -6.292 | -1.002 | -0.1639 |
+#> |.....................| 2.203 | 2.355 | 0.002610 | 0.6452 |
+#> |.....................| 0.08456 | 0.6777 | 0.6509 | 1.570 |
+#> |.....................| 1.318 | 1.306 |...........|...........|
+#> | X| 447.04716 | 93.69 | 0.001850 | 0.2686 | 0.8488 |
+#> |.....................| 9.053 | 2.355 | 0.002610 | 0.6452 |
+#> |.....................| 0.08456 | 0.6777 | 0.6509 | 1.570 |
+#> |.....................| 1.318 | 1.306 |...........|...........|
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc, ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG, addProp = .addProp, tol = .tol, itmax = .itmax, type = .type, powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.799 0.044 0.842
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 9.1294e+01 -5.0486e+00 -1.7441e+00 -3.5640e+00 -2.1387e+00 4.8639e-01 5.5948e+00 1.4680e+00 1.1057e+00 2.3810e+00 4.8150e-01 4.3452e-01 1.0359e+01 2.3790e-05 7.8082e+00 5.1813e-01
+#> 2: 9.1224e+01 -5.2308e+00 -1.9743e+00 -4.0115e+00 -1.8311e+00 9.8058e-02 5.3151e+00 1.3946e+00 1.0504e+00 2.8908e+00 4.5742e-01 5.2252e-01 5.9132e+00 5.7000e-04 6.5362e+00 1.8571e-07
+#> 3: 9.1371e+01 -5.5075e+00 -2.1136e+00 -4.0542e+00 -1.4871e+00 -4.1222e-02 5.0493e+00 1.3249e+00 9.9785e-01 3.4546e+00 4.3455e-01 6.3380e-01 4.0626e+00 1.0302e-05 4.6845e+00 5.0378e-04
+#> 4: 91.3391 -5.7912 -2.1450 -3.9623 -1.3302 -0.1356 4.7969 1.2586 0.9480 3.2819 0.4128 0.6021 3.3624 0.0249 3.6770 0.0248
+#> 5: 91.5018 -6.0214 -2.1492 -3.9323 -1.2118 -0.0647 4.5570 1.1957 0.9006 3.1178 0.3922 0.5720 2.9393 0.0349 3.1610 0.0371
+#> 6: 91.4496 -5.8734 -2.0974 -3.9977 -1.0936 -0.0608 4.3292 1.3347 0.8695 3.1231 0.3726 0.5434 2.5921 0.0366 2.7534 0.0396
+#> 7: 91.6540 -5.8545 -2.1019 -3.9268 -0.9717 -0.1622 4.1127 1.8221 0.8771 2.9670 0.3539 0.5162 2.3468 0.0466 2.4323 0.0474
+#> 8: 91.7226 -5.8139 -2.0764 -4.0030 -0.9804 -0.1283 3.9071 2.3972 0.9978 2.9945 0.3362 0.4904 2.0001 0.0405 2.0620 0.0557
+#> 9: 91.9975 -5.6339 -2.0812 -3.9379 -0.9156 -0.0654 4.4265 2.2773 0.9479 3.0945 0.3194 0.4659 1.8817 0.0397 1.4473 0.0845
+#> 10: 91.9477 -5.6101 -2.0459 -3.8821 -0.9368 -0.0428 4.9868 2.2787 0.9297 3.2162 0.3035 0.4426 1.6910 0.0397 1.3759 0.0892
+#> 11: 92.1798 -5.5425 -2.0676 -3.9349 -0.9248 -0.0339 5.0312 2.1648 0.8832 3.0554 0.2883 0.4205 1.6613 0.0375 1.3387 0.0823
+#> 12: 92.1456 -5.6294 -2.1011 -3.8899 -0.9195 -0.0410 4.7796 2.0565 0.9077 3.1066 0.3013 0.3995 1.6018 0.0393 1.5496 0.0691
+#> 13: 91.6764 -5.5607 -2.0911 -3.8832 -0.9268 -0.0367 4.5407 1.9537 0.9246 3.0425 0.2862 0.3795 1.6900 0.0350 1.4050 0.0712
+#> 14: 91.4832 -5.5007 -2.1133 -3.8869 -0.9208 -0.0202 4.3136 1.8560 0.8795 3.0389 0.2719 0.3605 1.5526 0.0389 1.7056 0.0502
+#> 15: 91.7854 -5.4454 -2.1124 -3.8750 -0.8842 -0.0608 4.0979 1.7632 0.9004 3.0463 0.2583 0.3425 1.6201 0.0384 1.2463 0.0747
+#> 16: 91.7608 -5.4097 -2.1449 -3.8750 -0.8797 -0.0532 3.8930 1.6751 0.9666 3.0463 0.2454 0.3254 1.6086 0.0384 1.0840 0.0850
+#> 17: 91.6692 -5.5401 -2.1688 -3.8762 -0.9022 -0.0101 3.6984 1.8405 1.0323 2.9672 0.2331 0.3091 1.4625 0.0371 1.1135 0.0841
+#> 18: 91.3169 -5.5720 -2.1777 -3.8851 -0.9396 0.0040 3.5135 1.8186 1.0419 3.0783 0.2215 0.2936 1.4778 0.0396 1.3403 0.0732
+#> 19: 91.4384 -5.6696 -2.1469 -3.8892 -0.9318 -0.0103 3.3378 2.2700 1.0489 3.0592 0.2128 0.2790 1.3854 0.0379 1.1760 0.0858
+#> 20: 91.3273 -5.7800 -2.1388 -3.9004 -0.9536 -0.0159 3.1709 2.7506 1.0297 3.0477 0.2021 0.2650 1.4542 0.0419 1.1576 0.0856
+#> 21: 91.7477 -5.7952 -2.1436 -3.9164 -0.9263 -0.0184 3.0124 3.0737 1.0414 3.0435 0.1948 0.2518 1.5026 0.0398 1.1833 0.0791
+#> 22: 91.6492 -6.0575 -2.1196 -3.9168 -0.9471 -0.0153 2.8617 4.1317 1.0322 3.0494 0.1850 0.2392 1.4351 0.0409 1.0739 0.0873
+#> 23: 91.8536 -6.2824 -2.1596 -3.9174 -0.9405 0.0031 2.7187 5.3935 1.0143 3.1085 0.1758 0.2272 1.4534 0.0404 1.0651 0.0805
+#> 24: 92.1616 -6.2246 -2.0912 -3.9224 -0.9338 0.0118 2.5827 5.7533 0.9636 3.0780 0.1741 0.2158 1.5863 0.0336 1.0915 0.0804
+#> 25: 92.2576 -6.2746 -2.1058 -3.9587 -0.9355 0.0189 2.4536 5.4656 0.9706 3.3477 0.1780 0.2051 1.4555 0.0365 1.0838 0.0782
+#> 26: 92.3314 -6.1739 -2.1211 -3.9676 -0.9474 0.0525 2.4934 5.5785 0.9981 3.3705 0.1835 0.1948 1.4433 0.0379 1.1300 0.0783
+#> 27: 92.8206 -6.1111 -2.0900 -3.9787 -0.9472 0.0058 2.5201 5.4329 1.0145 3.5013 0.1856 0.1851 1.4484 0.0391 1.1809 0.0723
+#> 28: 92.8685 -6.0934 -2.0963 -3.9872 -0.9693 0.0053 2.9812 5.1612 0.9925 3.5416 0.1816 0.1758 1.4713 0.0389 1.1766 0.0704
+#> 29: 92.6774 -5.8779 -2.0833 -3.9954 -0.9546 -0.0099 4.3751 4.9032 1.0762 3.5483 0.1755 0.1670 1.4844 0.0378 1.3435 0.0599
+#> 30: 92.6704 -5.9657 -2.0746 -3.9920 -0.9342 -0.0329 4.1563 4.6580 1.0571 3.5382 0.1667 0.1587 1.4510 0.0427 1.2218 0.0678
+#> 31: 92.4139 -5.7428 -2.0922 -3.9765 -0.9178 -0.0302 3.9485 4.4251 1.0210 3.5601 0.1596 0.1507 1.5981 0.0349 1.3086 0.0619
+#> 32: 92.8243 -5.8072 -2.1154 -3.9699 -0.9130 0.0065 3.7511 4.2039 1.0622 3.4768 0.1667 0.1432 1.5321 0.0333 1.3779 0.0611
+#> 33: 92.8737 -5.6655 -2.1132 -3.9763 -0.9155 0.0183 3.5635 3.9937 1.1068 3.5075 0.1583 0.1360 1.5351 0.0341 1.2700 0.0673
+#> 34: 93.0233 -5.7429 -2.1022 -3.9648 -0.9057 0.0202 3.3853 3.7940 1.0830 3.4532 0.1504 0.1292 1.5128 0.0368 1.1942 0.0702
+#> 35: 93.1333 -5.7707 -2.1003 -4.0004 -0.9031 0.0201 3.2161 3.6043 1.1161 3.4701 0.1429 0.1228 1.6003 0.0307 1.1387 0.0734
+#> 36: 93.1398 -5.7700 -2.1168 -3.9678 -0.9038 0.0107 3.0553 3.4241 1.1209 3.4126 0.1358 0.1166 1.4919 0.0331 1.0642 0.0755
+#> 37: 92.8847 -5.6651 -2.1538 -3.9634 -0.9176 0.0364 2.9995 3.2529 1.1108 3.3776 0.1402 0.1173 1.5093 0.0396 1.1550 0.0693
+#> 38: 93.2326 -5.5244 -2.1571 -3.9909 -0.9231 0.0179 2.8832 3.0902 1.0763 3.5170 0.1332 0.1205 1.4962 0.0472 1.1657 0.0679
+#> 39: 92.9946 -5.4516 -2.1475 -3.9365 -0.9067 0.0309 3.0986 2.9357 1.0562 3.4194 0.1265 0.1251 1.4786 0.0464 1.1183 0.0721
+#> 40: 93.2028 -5.6148 -2.1367 -3.9235 -0.9048 0.0099 2.9436 2.7889 1.1256 3.3460 0.1241 0.1288 1.4515 0.0459 1.0449 0.0753
+#> 41: 93.1297 -5.4665 -2.0545 -4.0108 -0.9136 -0.0216 2.7964 2.6495 1.1471 3.4754 0.1281 0.1223 1.7359 0.0321 1.0876 0.0780
+#> 42: 93.0469 -5.3767 -2.0820 -4.0213 -0.9361 -0.0264 2.6566 2.5170 1.0897 3.5120 0.1411 0.1162 1.7070 0.0276 1.2377 0.0691
+#> 43: 93.3305 -5.4943 -2.0910 -4.0226 -0.9414 -0.0201 2.5238 2.3912 1.0896 3.4589 0.1621 0.1126 1.5584 0.0393 1.1485 0.0705
+#> 44: 93.2566 -5.4919 -2.1016 -4.0718 -0.9373 0.0024 2.3976 2.2716 1.0451 3.8959 0.1612 0.1162 1.5769 0.0286 1.2778 0.0693
+#> 45: 93.0284 -5.4885 -2.1012 -4.0740 -0.9202 -0.0197 2.2777 2.1580 1.0268 3.9297 0.1553 0.1104 1.5589 0.0289 1.1388 0.0778
+#> 46: 92.7188 -5.5807 -2.1102 -4.0875 -0.9465 0.0076 2.1638 2.2084 0.9840 4.0322 0.1475 0.1048 1.6729 0.0295 1.2763 0.0735
+#> 47: 92.6718 -5.5108 -2.1268 -4.0638 -0.9220 0.0131 2.0556 2.0980 1.0064 3.8306 0.1475 0.0996 1.6527 0.0271 1.3190 0.0659
+#> 48: 92.6727 -5.5268 -2.1326 -4.0693 -0.8999 0.0259 1.9529 2.2445 1.0387 3.8064 0.1459 0.0946 1.6587 0.0283 1.3555 0.0604
+#> 49: 92.5230 -5.5592 -2.1701 -4.0595 -0.9087 0.0350 1.8552 2.5181 1.0238 3.7514 0.1552 0.0899 1.5473 0.0307 1.2437 0.0662
+#> 50: 92.4920 -5.5778 -2.1309 -4.0711 -0.9317 0.0383 1.7625 2.6771 1.0203 3.7435 0.1587 0.0854 1.5727 0.0330 1.2555 0.0611
+#> 51: 92.4606 -5.5485 -2.1346 -4.0687 -0.9148 0.0638 1.6743 2.8079 1.0402 3.6978 0.1513 0.0811 1.5476 0.0335 1.2744 0.0658
+#> 52: 92.6305 -5.6829 -2.1658 -4.0697 -0.9298 0.0848 1.5906 2.8530 1.0565 3.6998 0.1644 0.0798 1.4751 0.0296 1.1351 0.0747
+#> 53: 92.6412 -5.5519 -2.1984 -4.1605 -0.9472 0.0803 1.8328 2.7103 1.0501 4.4111 0.1626 0.0758 1.5735 0.0343 1.2247 0.0643
+#> 54: 92.7616 -5.5718 -2.1826 -4.2028 -0.9382 0.0939 1.9108 2.5748 1.0708 4.7287 0.1775 0.0720 1.4860 0.0299 1.2190 0.0638
+#> 55: 92.8466 -5.6434 -2.1590 -4.0501 -0.9219 0.0660 2.3709 2.4461 1.0399 4.4922 0.1686 0.0684 1.5899 0.0297 1.2586 0.0598
+#> 56: 92.8839 -5.6503 -2.1758 -4.0467 -0.9265 0.0765 2.2523 2.3238 1.0755 4.2676 0.1698 0.0666 1.5357 0.0319 1.1854 0.0633
+#> 57: 92.8882 -5.3950 -2.1926 -4.0282 -0.9455 0.0600 2.4994 2.2076 1.0411 4.0542 0.1684 0.0633 1.5839 0.0342 1.2789 0.0612
+#> 58: 92.9510 -5.4362 -2.1993 -4.0402 -0.9349 0.0576 2.3744 2.0972 1.0184 3.8515 0.1757 0.0604 1.5796 0.0328 1.3027 0.0570
+#> 59: 92.8806 -5.4605 -2.2176 -4.2201 -0.9360 0.0998 2.2557 1.9923 1.0248 5.1421 0.1904 0.0573 1.6469 0.0325 1.4177 0.0534
+#> 60: 92.8606 -5.4697 -2.2016 -4.1707 -0.9218 0.0747 2.1429 1.8927 1.0489 4.8850 0.1809 0.0545 1.5984 0.0318 1.2879 0.0589
+#> 61: 92.8939 -5.5167 -2.2169 -4.1567 -0.9434 0.0680 2.1067 1.9160 1.0677 4.6408 0.1775 0.0517 1.5223 0.0404 1.2033 0.0623
+#> 62: 93.1569 -5.6121 -2.2073 -4.1427 -0.9431 0.0717 2.5977 2.0627 1.0518 4.5133 0.1758 0.0494 1.4644 0.0364 1.1857 0.0621
+#> 63: 93.2362 -5.5056 -2.1832 -4.0832 -0.9433 0.0754 3.4639 1.9596 1.0905 4.2877 0.1851 0.0536 1.5500 0.0320 1.2533 0.0610
+#> 64: 93.3935 -5.4320 -2.1735 -4.0754 -0.9601 0.0719 5.0337 1.8616 1.0723 4.0733 0.1907 0.0649 1.5436 0.0270 1.4154 0.0546
+#> 65: 93.1102 -5.5419 -2.1870 -4.0496 -0.9481 0.0753 5.0250 1.9760 1.1263 3.8696 0.1902 0.0617 1.4779 0.0262 1.1326 0.0712
+#> 66: 92.9832 -5.7640 -2.1941 -4.0532 -0.9444 0.0635 5.2049 2.6553 1.1258 3.7699 0.1915 0.0586 1.4926 0.0307 1.0960 0.0645
+#> 67: 92.6674 -5.6976 -2.1858 -4.0855 -0.9209 0.0562 4.9447 2.5225 1.1285 4.0204 0.1948 0.0556 1.4667 0.0315 1.1023 0.0650
+#> 68: 92.7718 -5.7724 -2.1760 -4.0242 -0.9354 0.0441 4.6975 2.8536 1.1471 3.8194 0.1922 0.0529 1.4283 0.0329 1.1174 0.0664
+#> 69: 92.8377 -5.7554 -2.1833 -4.0670 -0.9412 0.0834 4.4626 2.7404 1.1565 3.7904 0.1826 0.0502 1.4628 0.0318 1.0793 0.0747
+#> 70: 92.6830 -5.9071 -2.2266 -4.0604 -0.9399 0.0730 4.2394 3.5629 1.1459 3.7282 0.1734 0.0477 1.4892 0.0331 1.1526 0.0683
+#> 71: 92.5729 -5.8185 -2.2009 -4.0623 -0.9401 0.0878 4.0275 3.3847 1.0886 3.7348 0.1648 0.0453 1.4739 0.0373 1.0902 0.0678
+#> 72: 92.1755 -6.0270 -2.2108 -4.1507 -0.9564 0.0665 3.8261 3.9851 1.1200 4.1726 0.1617 0.0431 1.4478 0.0348 1.1400 0.0673
+#> 73: 91.8986 -6.0175 -2.1916 -4.1416 -0.9347 0.0243 3.6348 4.0607 1.1553 4.0576 0.1802 0.0409 1.4330 0.0406 1.0914 0.0712
+#> 74: 91.7729 -5.8767 -2.1898 -4.0934 -0.9122 0.0184 3.4531 3.8577 1.1254 3.8547 0.1827 0.0389 1.3372 0.0524 1.0717 0.0687
+#> 75: 91.3098 -5.9950 -2.1572 -4.1349 -0.9427 0.0190 3.4756 3.8000 1.1626 3.8402 0.1969 0.0369 1.3378 0.0501 1.1602 0.0685
+#> 76: 91.3766 -5.8701 -2.2042 -4.1128 -0.9081 0.0539 3.9350 3.6100 1.2348 3.7994 0.1891 0.0369 1.3400 0.0495 1.0656 0.0738
+#> 77: 91.6057 -5.7437 -2.1988 -4.1241 -0.8890 0.0500 5.0868 3.4295 1.1971 3.8470 0.1950 0.0469 1.4928 0.0397 1.1129 0.0700
+#> 78: 91.7868 -5.7832 -2.1844 -4.1102 -0.9104 0.0698 4.8325 3.2580 1.1670 3.6547 0.1993 0.0502 1.4336 0.0340 0.9512 0.0805
+#> 79: 91.7221 -5.7881 -2.2166 -4.1137 -0.9160 0.0672 4.5909 3.0951 1.1582 3.5765 0.1928 0.0486 1.4632 0.0352 1.0210 0.0728
+#> 80: 91.8608 -5.8064 -2.2006 -4.0971 -0.9209 0.0642 4.3613 3.2163 1.1481 3.4758 0.1832 0.0462 1.4368 0.0356 1.0605 0.0710
+#> 81: 91.6423 -5.8749 -2.2037 -4.0893 -0.9187 0.0503 4.1432 3.5329 1.0907 3.5148 0.2011 0.0451 1.4719 0.0346 1.1684 0.0646
+#> 82: 91.8319 -6.0898 -2.2251 -4.0826 -0.9368 0.0842 4.1509 4.4964 1.0606 3.4836 0.1910 0.0428 1.4468 0.0387 1.1605 0.0637
+#> 83: 91.9794 -6.0417 -2.1947 -4.1042 -0.9114 0.0741 6.5949 4.5668 1.1113 3.6409 0.1815 0.0407 1.4780 0.0346 1.1277 0.0634
+#> 84: 91.8669 -6.1877 -2.1979 -4.1052 -0.9300 0.0807 6.2651 5.1958 1.1750 3.6752 0.1724 0.0386 1.4931 0.0278 1.0401 0.0685
+#> 85: 91.6789 -6.0634 -2.1896 -4.1357 -0.9371 0.0933 5.9519 4.9360 1.1259 3.8493 0.1732 0.0367 1.5058 0.0275 1.1356 0.0670
+#> 86: 91.6989 -6.2114 -2.2056 -4.1542 -0.9646 0.0882 5.6543 5.0411 1.1091 3.9411 0.1988 0.0349 1.4099 0.0338 1.1811 0.0636
+#> 87: 92.3758 -6.3779 -2.2062 -4.1739 -0.9385 0.0916 5.3716 6.2290 1.1213 4.0290 0.1889 0.0331 1.4809 0.0306 1.1443 0.0626
+#> 88: 92.2757 -6.2016 -2.2215 -4.1389 -0.9582 0.0942 5.1030 5.9176 1.0797 4.0768 0.1990 0.0315 1.4282 0.0386 1.2235 0.0629
+#> 89: 92.1970 -6.3356 -2.2081 -4.1412 -0.9555 0.1057 4.8478 5.9597 1.1474 4.0677 0.1890 0.0299 1.3856 0.0377 1.1807 0.0640
+#> 90: 92.0813 -6.4550 -2.2045 -4.1524 -0.9553 0.0885 4.6054 6.9999 1.1542 3.9901 0.1880 0.0284 1.3416 0.0416 1.1379 0.0653
+#> 91: 91.7111 -6.5289 -2.2203 -4.1763 -0.9288 0.0823 5.4933 6.9237 1.1601 4.0435 0.1839 0.0360 1.3387 0.0401 1.1768 0.0591
+#> 92: 92.1217 -6.5567 -2.2232 -4.2082 -0.9411 0.0815 8.0692 6.7286 1.1684 3.9422 0.1763 0.0411 1.3740 0.0463 1.1538 0.0613
+#> 93: 92.7497 -6.3512 -2.2463 -4.1806 -0.9633 0.0724 7.6657 6.3922 1.1870 3.8858 0.1796 0.0391 1.4232 0.0454 1.3749 0.0497
+#> 94: 92.2679 -6.3542 -2.2473 -4.1873 -0.9382 0.0711 7.2824 6.0726 1.1940 3.8847 0.1956 0.0371 1.3812 0.0465 1.2897 0.0521
+#> 95: 92.0257 -6.2448 -2.2624 -4.1681 -0.9624 0.0810 6.9183 5.7690 1.1345 3.8091 0.1858 0.0359 1.3026 0.0509 1.3000 0.0530
+#> 96: 91.5166 -5.9442 -2.2924 -4.2449 -0.9238 0.1058 7.1159 5.4805 1.1231 4.2529 0.1953 0.0343 1.4063 0.0445 1.3479 0.0482
+#> 97: 91.1606 -5.8541 -2.2912 -4.2398 -0.8875 0.1101 9.4515 5.2065 1.1256 4.3194 0.2081 0.0337 1.3436 0.0498 1.3317 0.0496
+#> 98: 91.2787 -6.0967 -2.2703 -4.2641 -0.9260 0.0869 8.9789 4.9462 1.2070 4.2238 0.1977 0.0373 1.3124 0.0495 1.1362 0.0653
+#> 99: 91.6449 -5.9441 -2.2562 -4.2355 -0.9312 0.1237 8.5300 4.6988 1.2343 4.0468 0.1878 0.0369 1.3508 0.0462 1.0542 0.0704
+#> 100: 91.7795 -5.8857 -2.2516 -4.3381 -0.9344 0.1291 8.1035 4.4639 1.2355 4.6941 0.1968 0.0393 1.4327 0.0358 1.1170 0.0668
+#> 101: 92.2537 -5.7930 -2.2345 -4.3477 -0.9272 0.1340 8.3402 4.2407 1.1961 4.7638 0.1933 0.0402 1.4683 0.0375 1.1216 0.0626
+#> 102: 92.3920 -6.0193 -2.2332 -4.3487 -0.9155 0.1565 11.1006 4.2977 1.1700 4.8048 0.2260 0.0444 1.4443 0.0342 1.0888 0.0674
+#> 103: 92.0043 -5.7825 -2.2376 -4.2616 -0.9043 0.1686 10.5455 4.0829 1.1587 4.5646 0.2147 0.0422 1.4198 0.0338 1.1639 0.0625
+#> 104: 92.1575 -5.8497 -2.2470 -4.2456 -0.9128 0.1762 10.0183 3.8787 1.1405 4.3364 0.2040 0.0440 1.3919 0.0379 1.2040 0.0582
+#> 105: 92.2784 -5.7971 -2.2582 -4.2100 -0.9128 0.1731 9.5173 3.6848 1.1351 4.1196 0.1938 0.0418 1.3982 0.0404 1.1069 0.0656
+#> 106: 92.4336 -5.7752 -2.2690 -4.3771 -0.8925 0.1644 9.0415 3.5005 1.1547 5.0970 0.1841 0.0476 1.3670 0.0423 1.1716 0.0625
+#> 107: 92.5128 -5.8328 -2.2549 -4.4193 -0.9403 0.2268 8.5894 3.3255 1.1160 5.2711 0.1749 0.0453 1.4023 0.0347 1.0279 0.0757
+#> 108: 92.8926 -5.7266 -2.2606 -4.5037 -0.9392 0.2394 8.1599 3.1592 1.1293 5.9652 0.1661 0.0447 1.3837 0.0346 0.9545 0.0747
+#> 109: 92.4657 -5.8687 -2.2884 -4.4108 -0.9043 0.2611 7.7519 4.0001 1.0729 5.6669 0.1578 0.0424 1.3441 0.0351 0.9758 0.0708
+#> 110: 92.6620 -5.6900 -2.2825 -4.4337 -0.9003 0.2602 7.3643 3.8001 1.0843 5.3836 0.1499 0.0433 1.4652 0.0302 0.9950 0.0722
+#> 111: 92.8949 -5.6946 -2.2661 -4.5240 -0.9233 0.2372 6.9961 3.6101 1.0845 5.8133 0.1551 0.0411 1.5005 0.0327 0.9284 0.0753
+#> 112: 93.4237 -5.6562 -2.2474 -4.4809 -0.9441 0.2322 6.6463 3.4296 1.1498 5.5227 0.1474 0.0409 1.4612 0.0317 0.9336 0.0762
+#> 113: 93.1883 -5.6891 -2.2846 -4.3984 -0.9416 0.2317 6.3140 3.2581 1.1062 5.2465 0.1596 0.0463 1.3924 0.0380 1.0268 0.0698
+#> 114: 93.4464 -5.7087 -2.2902 -4.4274 -0.9401 0.2638 5.9983 3.0952 1.1170 5.0203 0.1516 0.0495 1.4108 0.0361 1.0355 0.0682
+#> 115: 93.1873 -5.8732 -2.2668 -4.5086 -0.9636 0.2516 5.6984 3.3427 1.1141 5.7549 0.1440 0.0490 1.5010 0.0309 1.0443 0.0679
+#> 116: 92.6878 -5.8520 -2.2903 -4.5349 -0.9663 0.2612 5.4135 3.2444 1.1048 5.8809 0.1471 0.0511 1.3910 0.0360 1.0423 0.0702
+#> 117: 92.7775 -5.7892 -2.2897 -4.4572 -0.9544 0.2380 5.1428 3.0822 1.0731 5.5869 0.1397 0.0703 1.3493 0.0360 0.9831 0.0713
+#> 118: 93.1533 -5.8045 -2.2859 -4.4787 -0.9667 0.2150 4.8857 3.0277 1.0872 5.6786 0.1439 0.0812 1.3838 0.0373 1.0547 0.0696
+#> 119: 92.8370 -5.7208 -2.2738 -4.4627 -0.9462 0.2095 4.6414 2.8764 1.1172 5.6197 0.1643 0.0772 1.3394 0.0348 0.9180 0.0803
+#> 120: 92.5430 -5.7795 -2.3004 -4.4203 -0.9479 0.2313 4.4093 2.8377 1.1312 5.3387 0.1655 0.0803 1.2967 0.0360 1.0699 0.0761
+#> 121: 92.5318 -5.6550 -2.2866 -4.5065 -0.9166 0.2321 4.1888 2.6959 1.0994 6.0180 0.1686 0.0763 1.3882 0.0322 0.9895 0.0733
+#> 122: 92.7380 -5.6688 -2.2968 -4.4523 -0.9279 0.2529 3.9794 2.5611 1.0642 5.7171 0.1601 0.0851 1.3786 0.0316 0.9358 0.0742
+#> 123: 93.0753 -5.7451 -2.2896 -4.5423 -0.9371 0.2724 3.7804 2.9938 1.0758 5.9349 0.1521 0.0808 1.4275 0.0339 0.9652 0.0727
+#> 124: 93.2708 -5.8004 -2.2782 -4.4951 -0.9451 0.2590 3.5914 3.0594 1.0875 5.6382 0.1607 0.0768 1.3628 0.0340 1.0577 0.0693
+#> 125: 93.4025 -5.7710 -2.2990 -4.4498 -0.9661 0.2633 3.4118 2.9276 1.0809 5.3563 0.1527 0.0730 1.3816 0.0406 1.0295 0.0671
+#> 126: 93.4928 -5.7054 -2.3002 -4.4087 -0.9394 0.2965 3.4732 2.7812 1.1275 5.0884 0.1481 0.0693 1.2949 0.0423 0.9084 0.0726
+#> 127: 93.6449 -5.6593 -2.2683 -4.3418 -0.9194 0.2560 4.2986 2.6422 1.1070 4.8340 0.1449 0.0707 1.4258 0.0341 0.8802 0.0777
+#> 128: 93.7430 -5.6359 -2.2686 -4.4174 -0.9500 0.2279 5.2477 2.5101 1.1046 5.5376 0.1512 0.0859 1.4523 0.0327 0.8659 0.0826
+#> 129: 93.7432 -5.6851 -2.2849 -4.2019 -0.9660 0.1995 7.2497 2.8789 1.1315 5.2607 0.1762 0.0972 1.3901 0.0357 1.1264 0.0743
+#> 130: 93.2409 -5.8965 -2.2946 -4.1880 -0.9774 0.1719 7.4467 3.2276 1.1464 4.9977 0.1720 0.0924 1.3517 0.0446 1.0461 0.0705
+#> 131: 92.7780 -6.0551 -2.2647 -4.1894 -0.9579 0.1391 7.0744 3.7584 1.1291 4.7478 0.1714 0.0995 1.2542 0.0438 0.9139 0.0777
+#> 132: 92.7157 -6.1161 -2.2501 -4.1784 -0.9651 0.1146 6.7207 3.9259 1.1674 4.5104 0.1712 0.0957 1.2549 0.0473 0.8964 0.0803
+#> 133: 92.2696 -5.8545 -2.2717 -4.1907 -0.9782 0.0985 6.3846 3.7296 1.1652 4.2849 0.1626 0.1198 1.2208 0.0498 0.9730 0.0822
+#> 134: 92.2067 -5.8603 -2.2743 -4.2095 -0.9754 0.1398 6.0654 3.5431 1.1551 4.0706 0.1695 0.1138 1.3022 0.0432 0.9960 0.0795
+#> 135: 92.3979 -5.9500 -2.3053 -4.1938 -0.9425 0.1134 5.7621 3.3660 1.1771 3.8671 0.1610 0.1081 1.3373 0.0462 1.1323 0.0665
+#> 136: 92.3749 -5.8701 -2.2979 -4.2493 -0.9386 0.1504 5.4740 3.3090 1.1638 3.9609 0.1724 0.1027 1.3578 0.0389 1.1943 0.0650
+#> 137: 92.6942 -5.9020 -2.2755 -4.2318 -0.9464 0.1541 5.2003 3.5521 1.1704 3.8948 0.1685 0.0976 1.4170 0.0399 1.1472 0.0626
+#> 138: 92.7234 -5.8085 -2.2653 -4.2164 -0.9662 0.1808 4.9403 3.3745 1.1977 3.8348 0.1694 0.0927 1.4229 0.0387 1.0934 0.0708
+#> 139: 92.7341 -5.7737 -2.2685 -4.1759 -0.9334 0.1554 4.6933 3.2057 1.1971 3.6962 0.1917 0.0881 1.4324 0.0363 1.1669 0.0652
+#> 140: 92.1593 -5.6287 -2.2576 -4.1977 -0.9232 0.1345 4.6967 3.0455 1.1676 3.8133 0.2060 0.0837 1.5032 0.0349 1.1418 0.0678
+#> 141: 92.3199 -5.8323 -2.2451 -4.1948 -0.9447 0.1295 4.9624 3.3893 1.1408 3.8423 0.1957 0.0795 1.4470 0.0325 1.0892 0.0739
+#> 142: 92.7246 -6.1252 -2.2304 -4.1984 -0.9160 0.0816 4.7143 4.6501 1.1420 3.8554 0.1901 0.0755 1.4847 0.0386 1.2815 0.0576
+#> 143: 92.4130 -6.0231 -2.2261 -4.2205 -0.9495 0.1020 4.4786 4.4176 1.1454 4.0301 0.1929 0.0717 1.4103 0.0410 1.0418 0.0739
+#> 144: 92.4006 -5.9898 -2.2232 -4.2429 -0.9553 0.1131 4.2547 4.1967 1.1579 4.2583 0.1904 0.0681 1.4272 0.0339 1.0591 0.0737
+#> 145: 92.5011 -6.2340 -2.2232 -4.1872 -0.9560 0.1322 6.1775 4.8941 1.1594 4.0453 0.1811 0.0647 1.4059 0.0298 1.0219 0.0752
+#> 146: 92.7460 -6.2989 -2.2417 -4.2501 -0.9650 0.1527 5.8686 5.6454 1.1154 4.0076 0.1720 0.0758 1.4027 0.0348 1.1220 0.0689
+#> 147: 93.0630 -6.0839 -2.2217 -4.1822 -0.9661 0.1634 5.5752 5.3631 1.0596 3.8072 0.1743 0.0733 1.3682 0.0393 1.0992 0.0700
+#> 148: 92.7639 -5.8682 -2.2550 -4.1926 -0.9440 0.1599 5.8048 5.0950 1.0858 3.6230 0.1749 0.0696 1.3364 0.0436 1.0967 0.0721
+#> 149: 92.6183 -6.1270 -2.2379 -4.1103 -0.9643 0.1202 5.8027 4.8402 1.1089 3.4860 0.1661 0.0661 1.3061 0.0457 1.0014 0.0724
+#> 150: 92.7472 -6.1515 -2.2199 -4.1027 -0.9611 0.1014 5.6767 4.5982 1.1061 3.6113 0.1578 0.0654 1.3543 0.0405 1.0847 0.0707
+#> 151: 92.9566 -5.8911 -2.2174 -4.0722 -0.9516 0.0992 5.9638 4.3683 1.1057 3.5122 0.1767 0.0621 1.3619 0.0396 1.0158 0.0734
+#> 152: 93.0035 -5.8395 -2.2559 -4.0650 -0.9389 0.0928 4.4799 3.2331 1.0387 3.4826 0.1713 0.0604 1.3425 0.0428 1.1101 0.0635
+#> 153: 92.7242 -5.7832 -2.2538 -4.1288 -0.9159 0.1047 4.6102 3.0838 1.0527 3.8052 0.1718 0.0597 1.3905 0.0398 1.1371 0.0635
+#> 154: 92.2125 -5.9077 -2.2400 -4.0922 -0.9106 0.1033 4.4732 3.8350 1.0261 3.6148 0.1955 0.0643 1.3176 0.0419 1.1130 0.0635
+#> 155: 92.6226 -5.6271 -2.2239 -4.0122 -0.8948 0.0647 4.5553 2.5675 1.0412 3.0513 0.1845 0.0866 1.3266 0.0459 1.0244 0.0680
+#> 156: 92.6532 -5.5576 -2.2251 -4.0066 -0.9006 0.0922 3.8517 2.3273 1.0455 3.0971 0.1928 0.0863 1.4000 0.0394 0.9203 0.0754
+#> 157: 92.5192 -5.4834 -2.2356 -4.0069 -0.9321 0.0904 3.0410 1.8841 0.9867 3.1990 0.1905 0.0816 1.3927 0.0407 1.1517 0.0614
+#> 158: 92.5628 -5.5318 -2.2044 -4.0269 -0.9319 0.0742 3.5124 1.9585 1.0692 3.1835 0.1958 0.0934 1.4038 0.0324 0.9680 0.0758
+#> 159: 92.9690 -5.6416 -2.2134 -4.0156 -0.9556 0.0560 4.3830 2.2442 1.0543 3.2358 0.1873 0.0951 1.3624 0.0375 1.1207 0.0696
+#> 160: 92.9861 -5.5872 -2.2207 -3.9908 -0.9190 0.0417 4.1202 2.1685 1.0711 3.1521 0.1766 0.0913 1.3760 0.0371 1.0970 0.0713
+#> 161: 93.3139 -5.5349 -2.1972 -3.9860 -0.9365 0.0011 4.2865 1.8741 1.0759 3.0304 0.2007 0.0750 1.3650 0.0411 1.1220 0.0662
+#> 162: 93.3324 -5.6135 -2.1579 -4.0151 -0.9507 -0.0091 4.6402 2.0208 1.0535 3.0349 0.1935 0.0764 1.4069 0.0383 1.2550 0.0598
+#> 163: 93.0110 -5.5253 -2.1419 -4.0151 -0.9197 -0.0072 5.8946 1.9087 1.0965 3.0349 0.1833 0.0814 1.5095 0.0290 1.1314 0.0665
+#> 164: 93.0848 -5.4980 -2.1670 -4.0213 -0.9345 0.0150 4.9128 1.8293 1.0379 3.0653 0.1728 0.0835 1.4913 0.0343 1.0589 0.0687
+#> 165: 92.9407 -5.3978 -2.1707 -4.0090 -0.9480 0.0126 3.4620 1.3870 1.0594 3.0115 0.1702 0.0982 1.5550 0.0296 1.0978 0.0694
+#> 166: 93.1504 -5.4880 -2.1890 -3.9958 -0.9511 0.0316 2.7859 1.8457 1.0294 3.0739 0.1738 0.1031 1.5109 0.0308 1.1800 0.0651
+#> 167: 92.8442 -5.4673 -2.1984 -4.0259 -0.9262 0.0243 2.0497 1.6348 1.0469 3.1258 0.1650 0.0981 1.6185 0.0291 1.1733 0.0655
+#> 168: 92.9484 -5.6255 -2.2012 -4.0136 -0.9309 0.0199 1.8121 2.0784 1.0415 3.1795 0.1816 0.0929 1.5727 0.0268 1.4222 0.0543
+#> 169: 93.0266 -5.6135 -2.1677 -4.0179 -0.9279 0.0375 1.7553 2.1663 1.0298 3.1675 0.2013 0.0926 1.5356 0.0274 1.2960 0.0596
+#> 170: 92.9844 -5.6286 -2.1839 -4.0509 -0.9471 0.0414 1.9485 2.4078 1.0656 3.2787 0.2112 0.0950 1.5210 0.0265 1.3069 0.0616
+#> 171: 92.6832 -5.6238 -2.2059 -4.0710 -0.9175 0.0383 1.5941 2.2918 1.1095 3.3435 0.1921 0.0895 1.4678 0.0345 1.2189 0.0618
+#> 172: 92.5302 -5.5653 -2.2086 -4.0429 -0.9412 0.0773 1.5302 2.2565 1.1293 3.2157 0.1924 0.0680 1.4438 0.0367 1.2084 0.0661
+#> 173: 92.3877 -5.5357 -2.2141 -4.0246 -0.9268 0.0866 1.2153 2.0588 1.0844 3.2941 0.2060 0.0726 1.4686 0.0359 1.3683 0.0596
+#> 174: 92.4410 -5.4921 -2.1955 -4.0398 -0.9269 0.0645 1.6903 2.0042 1.1236 3.3646 0.1847 0.0804 1.5533 0.0310 1.2320 0.0675
+#> 175: 92.4192 -5.4726 -2.1945 -4.0271 -0.9222 0.0728 1.1344 1.9292 1.1085 3.3173 0.1875 0.0912 1.5350 0.0302 1.2461 0.0679
+#> 176: 92.3581 -5.5256 -2.2055 -3.9958 -0.9211 0.0720 1.1140 1.8097 1.0898 3.1459 0.2018 0.1104 1.4391 0.0323 1.2240 0.0677
+#> 177: 92.2144 -5.6699 -2.2357 -4.0017 -0.9402 0.0785 1.1932 2.6190 1.0355 3.1852 0.2266 0.1125 1.4705 0.0327 1.2866 0.0621
+#> 178: 92.3608 -5.7040 -2.2245 -4.0242 -0.9642 0.0596 0.7932 2.6061 0.9408 3.1080 0.1958 0.1180 1.5158 0.0365 1.3571 0.0600
+#> 179: 92.4358 -5.6877 -2.2243 -4.0166 -0.9486 0.0595 0.7591 2.3791 0.9241 3.0638 0.1900 0.1257 1.4317 0.0363 1.2359 0.0686
+#> 180: 92.5146 -5.7856 -2.2343 -4.0098 -0.9522 0.0522 0.4573 2.6882 0.9636 3.0406 0.1835 0.1270 1.4631 0.0361 1.2192 0.0701
+#> 181: 92.5469 -5.7684 -2.2220 -4.0549 -0.9488 0.0901 0.4189 2.4963 0.9873 3.1470 0.1744 0.1268 1.5165 0.0336 1.1359 0.0760
+#> 182: 92.5829 -5.7658 -2.2385 -4.0362 -0.9723 0.0572 0.3720 2.5387 0.9203 3.0397 0.1769 0.1636 1.4781 0.0375 1.2697 0.0677
+#> 183: 92.5737 -5.9187 -2.2130 -4.0638 -0.9876 0.0797 0.3084 3.3137 0.9467 3.0532 0.1737 0.1599 1.4288 0.0309 1.3024 0.0617
+#> 184: 92.4989 -5.9837 -2.1994 -4.0476 -0.9737 0.0594 0.2533 3.6658 0.9248 3.1230 0.1776 0.1552 1.3829 0.0316 1.2818 0.0621
+#> 185: 92.5677 -6.0227 -2.2084 -4.0403 -0.9584 0.0609 0.2215 3.8810 0.9134 3.0961 0.1739 0.1473 1.4202 0.0319 1.2731 0.0579
+#> 186: 92.7090 -5.9641 -2.2218 -4.0319 -0.9573 0.0575 0.2917 3.9574 0.9373 3.0666 0.1691 0.1703 1.4378 0.0296 1.2775 0.0601
+#> 187: 92.7358 -6.2503 -2.2003 -4.0534 -0.9742 0.0691 0.3037 5.2011 0.9333 3.0796 0.1647 0.1553 1.4254 0.0293 1.1987 0.0629
+#> 188: 92.6733 -6.1434 -2.1988 -4.0792 -0.9878 0.0860 0.3122 4.9451 0.9080 3.1891 0.1628 0.1558 1.4099 0.0317 1.3162 0.0593
+#> 189: 92.7256 -6.0886 -2.1766 -4.0419 -0.9672 0.0550 0.3758 4.3461 0.9140 3.0795 0.1697 0.1649 1.5310 0.0301 1.3258 0.0566
+#> 190: 92.5144 -6.1827 -2.2159 -4.0525 -0.9677 0.0728 0.3855 4.3370 0.9706 3.0518 0.1486 0.1841 1.4390 0.0295 1.1259 0.0740
+#> 191: 92.6209 -6.1257 -2.2287 -4.1095 -0.9670 0.1034 0.3340 4.3051 0.9486 3.1970 0.1549 0.1776 1.4397 0.0296 1.2004 0.0684
+#> 192: 92.6156 -6.1289 -2.2067 -4.1191 -0.9900 0.1090 0.3069 4.1314 0.9134 3.1476 0.1596 0.1912 1.4380 0.0301 1.1238 0.0720
+#> 193: 92.5434 -5.9782 -2.1800 -4.0845 -0.9547 0.1173 0.2694 3.6834 0.9005 2.9479 0.1582 0.1733 1.4538 0.0294 0.8798 0.0866
+#> 194: 92.5884 -5.7815 -2.2110 -4.0714 -0.9510 0.0928 0.2493 2.8236 0.9615 2.9852 0.1488 0.1730 1.4409 0.0297 1.1446 0.0677
+#> 195: 92.6180 -5.9277 -2.2213 -4.0714 -0.9379 0.1177 0.1993 3.5172 0.8976 2.9852 0.1449 0.1735 1.5012 0.0299 1.2131 0.0618
+#> 196: 92.5920 -5.7723 -2.2496 -4.0669 -0.9184 0.1262 0.2595 3.2454 0.9419 2.9697 0.1600 0.1881 1.4017 0.0338 0.9594 0.0790
+#> 197: 92.6292 -5.8658 -2.2434 -4.0640 -0.9365 0.1216 0.2491 3.3540 0.9267 2.9523 0.1598 0.1749 1.3953 0.0383 1.0788 0.0702
+#> 198: 92.6911 -5.8407 -2.2605 -4.0640 -0.9319 0.1264 0.1930 3.2321 0.8884 2.9523 0.1320 0.1940 1.4026 0.0358 1.0613 0.0704
+#> 199: 92.6480 -5.6988 -2.2599 -4.0668 -0.9395 0.1328 0.1412 2.6535 0.8915 2.9610 0.1573 0.2052 1.4353 0.0360 0.9900 0.0742
+#> 200: 92.7139 -5.6152 -2.2522 -4.0684 -0.9192 0.1589 0.1686 2.4362 0.9098 3.0185 0.1702 0.1705 1.4153 0.0338 1.1747 0.0705
+#> 201: 92.7134 -5.7029 -2.2504 -4.0502 -0.9270 0.1453 0.1499 2.6851 0.8909 2.9484 0.1749 0.1772 1.3851 0.0363 1.1255 0.0714
+#> 202: 92.7087 -5.7236 -2.2421 -4.0499 -0.9364 0.1238 0.1324 2.7215 0.8810 2.9507 0.1694 0.1913 1.3864 0.0365 1.1192 0.0705
+#> 203: 92.7013 -5.7563 -2.2293 -4.0494 -0.9394 0.1134 0.1269 2.8279 0.8866 2.9501 0.1618 0.1915 1.3981 0.0356 1.0942 0.0710
+#> 204: 92.6964 -5.8134 -2.2208 -4.0646 -0.9373 0.1144 0.1192 3.1058 0.8973 3.0279 0.1523 0.1983 1.4126 0.0345 1.0629 0.0723
+#> 205: 92.6936 -5.8441 -2.2195 -4.0787 -0.9373 0.1144 0.1068 3.2553 0.9029 3.0962 0.1473 0.2001 1.4217 0.0344 1.0532 0.0719
+#> 206: 92.6881 -5.8805 -2.2209 -4.0887 -0.9432 0.1187 0.1016 3.4269 0.9126 3.1477 0.1479 0.1957 1.4251 0.0348 1.0697 0.0712
+#> 207: 92.6929 -5.9304 -2.2259 -4.0987 -0.9473 0.1234 0.1028 3.6444 0.9261 3.1982 0.1469 0.1910 1.4170 0.0348 1.0586 0.0717
+#> 208: 92.6907 -5.9413 -2.2275 -4.1043 -0.9482 0.1267 0.1038 3.6864 0.9313 3.2244 0.1467 0.1889 1.4121 0.0343 1.0499 0.0718
+#> 209: 92.6917 -5.9265 -2.2304 -4.1109 -0.9498 0.1289 0.1022 3.5975 0.9363 3.2487 0.1478 0.1863 1.4053 0.0344 1.0521 0.0716
+#> 210: 92.6966 -5.9218 -2.2322 -4.1164 -0.9516 0.1337 0.0984 3.5650 0.9413 3.2688 0.1493 0.1874 1.3949 0.0342 1.0499 0.0719
+#> 211: 92.7020 -5.9160 -2.2351 -4.1209 -0.9542 0.1385 0.0958 3.5091 0.9390 3.2968 0.1503 0.1873 1.3925 0.0345 1.0547 0.0718
+#> 212: 92.7065 -5.9119 -2.2376 -4.1247 -0.9564 0.1432 0.0933 3.4520 0.9373 3.3205 0.1531 0.1901 1.3869 0.0346 1.0625 0.0717
+#> 213: 92.7107 -5.9047 -2.2402 -4.1286 -0.9575 0.1455 0.0930 3.3990 0.9361 3.3369 0.1536 0.1932 1.3814 0.0349 1.0698 0.0712
+#> 214: 92.7110 -5.9061 -2.2415 -4.1321 -0.9585 0.1483 0.0921 3.3864 0.9364 3.3517 0.1542 0.1963 1.3794 0.0348 1.0721 0.0712
+#> 215: 92.7116 -5.9128 -2.2417 -4.1360 -0.9581 0.1510 0.0941 3.4201 0.9347 3.3646 0.1545 0.1988 1.3764 0.0350 1.0731 0.0712
+#> 216: 92.7135 -5.9184 -2.2432 -4.1383 -0.9589 0.1540 0.0957 3.4623 0.9337 3.3698 0.1541 0.2016 1.3761 0.0353 1.0737 0.0714
+#> 217: 92.7143 -5.9262 -2.2453 -4.1428 -0.9604 0.1568 0.0981 3.5202 0.9323 3.3854 0.1542 0.2053 1.3770 0.0352 1.0779 0.0716
+#> 218: 92.7102 -5.9169 -2.2463 -4.1446 -0.9606 0.1604 0.1000 3.4823 0.9305 3.3851 0.1530 0.2083 1.3802 0.0353 1.0819 0.0716
+#> 219: 92.7062 -5.9089 -2.2470 -4.1481 -0.9597 0.1636 0.1000 3.4465 0.9295 3.3874 0.1529 0.2125 1.3779 0.0352 1.0836 0.0716
+#> 220: 92.7027 -5.9052 -2.2480 -4.1509 -0.9594 0.1668 0.1020 3.4302 0.9264 3.3877 0.1531 0.2168 1.3780 0.0352 1.0893 0.0713
+#> 221: 92.7029 -5.8990 -2.2497 -4.1541 -0.9586 0.1696 0.1017 3.4007 0.9227 3.3916 0.1535 0.2208 1.3781 0.0354 1.0925 0.0709
+#> 222: 92.7063 -5.8993 -2.2519 -4.1604 -0.9582 0.1732 0.1025 3.4099 0.9190 3.4135 0.1537 0.2268 1.3791 0.0355 1.1031 0.0702
+#> 223: 92.7090 -5.8932 -2.2537 -4.1669 -0.9573 0.1757 0.1022 3.3946 0.9157 3.4424 0.1543 0.2319 1.3802 0.0356 1.1040 0.0701
+#> 224: 92.7116 -5.8930 -2.2545 -4.1712 -0.9561 0.1774 0.1017 3.3964 0.9133 3.4673 0.1550 0.2355 1.3795 0.0356 1.1018 0.0701
+#> 225: 92.7136 -5.8911 -2.2564 -4.1715 -0.9551 0.1788 0.1016 3.4013 0.9125 3.4628 0.1548 0.2380 1.3756 0.0359 1.1003 0.0700
+#> 226: 92.7153 -5.8883 -2.2569 -4.1711 -0.9536 0.1793 0.1016 3.4046 0.9134 3.4575 0.1549 0.2398 1.3737 0.0360 1.1016 0.0699
+#> 227: 92.7163 -5.8830 -2.2575 -4.1720 -0.9526 0.1796 0.1019 3.3952 0.9129 3.4575 0.1545 0.2407 1.3718 0.0363 1.1015 0.0698
+#> 228: 92.7182 -5.8865 -2.2578 -4.1728 -0.9528 0.1804 0.1017 3.4198 0.9113 3.4576 0.1538 0.2433 1.3722 0.0363 1.1068 0.0695
+#> 229: 92.7199 -5.8965 -2.2578 -4.1718 -0.9523 0.1812 0.1023 3.5030 0.9097 3.4503 0.1529 0.2463 1.3749 0.0363 1.1093 0.0694
+#> 230: 92.7205 -5.8997 -2.2578 -4.1712 -0.9514 0.1825 0.1025 3.5337 0.9071 3.4446 0.1519 0.2497 1.3802 0.0362 1.1115 0.0693
+#> 231: 92.7208 -5.9001 -2.2581 -4.1711 -0.9511 0.1838 0.1044 3.5537 0.9037 3.4423 0.1510 0.2533 1.3834 0.0361 1.1125 0.0693
+#> 232: 92.7183 -5.9041 -2.2588 -4.1715 -0.9504 0.1855 0.1061 3.5958 0.9001 3.4391 0.1503 0.2572 1.3871 0.0362 1.1161 0.0690
+#> 233: 92.7169 -5.9106 -2.2593 -4.1725 -0.9490 0.1866 0.1073 3.6433 0.8968 3.4367 0.1496 0.2609 1.3900 0.0362 1.1179 0.0688
+#> 234: 92.7125 -5.9165 -2.2594 -4.1728 -0.9479 0.1873 0.1098 3.6870 0.8932 3.4321 0.1498 0.2641 1.3907 0.0363 1.1177 0.0687
+#> 235: 92.7072 -5.9203 -2.2592 -4.1729 -0.9472 0.1876 0.1128 3.7229 0.8899 3.4269 0.1506 0.2676 1.3913 0.0364 1.1212 0.0686
+#> 236: 92.7048 -5.9319 -2.2603 -4.1724 -0.9467 0.1879 0.1147 3.7863 0.8879 3.4175 0.1510 0.2705 1.3898 0.0365 1.1181 0.0688
+#> 237: 92.7037 -5.9349 -2.2609 -4.1720 -0.9461 0.1881 0.1152 3.8047 0.8862 3.4096 0.1512 0.2731 1.3891 0.0367 1.1164 0.0688
+#> 238: 92.7027 -5.9359 -2.2605 -4.1715 -0.9459 0.1884 0.1151 3.7997 0.8842 3.4023 0.1516 0.2755 1.3905 0.0366 1.1171 0.0688
+#> 239: 92.7027 -5.9375 -2.2599 -4.1712 -0.9463 0.1881 0.1143 3.8187 0.8835 3.3954 0.1521 0.2780 1.3923 0.0366 1.1193 0.0688
+#> 240: 92.7025 -5.9409 -2.2593 -4.1710 -0.9467 0.1884 0.1135 3.8437 0.8830 3.3888 0.1530 0.2797 1.3939 0.0366 1.1266 0.0685
+#> 241: 92.7006 -5.9429 -2.2589 -4.1703 -0.9469 0.1887 0.1130 3.8580 0.8825 3.3820 0.1529 0.2815 1.3967 0.0364 1.1299 0.0685
+#> 242: 92.6977 -5.9366 -2.2594 -4.1693 -0.9471 0.1887 0.1130 3.8245 0.8810 3.3742 0.1534 0.2833 1.3967 0.0364 1.1323 0.0685
+#> 243: 92.6951 -5.9310 -2.2605 -4.1683 -0.9473 0.1891 0.1131 3.7904 0.8807 3.3666 0.1541 0.2853 1.3953 0.0364 1.1380 0.0683
+#> 244: 92.6928 -5.9289 -2.2610 -4.1680 -0.9471 0.1899 0.1130 3.7709 0.8797 3.3604 0.1545 0.2880 1.3947 0.0364 1.1399 0.0683
+#> 245: 92.6902 -5.9291 -2.2615 -4.1677 -0.9472 0.1914 0.1129 3.7637 0.8787 3.3538 0.1549 0.2898 1.3942 0.0364 1.1440 0.0681
+#> 246: 92.6880 -5.9271 -2.2617 -4.1677 -0.9472 0.1926 0.1131 3.7457 0.8785 3.3500 0.1549 0.2916 1.3938 0.0364 1.1468 0.0681
+#> 247: 92.6865 -5.9264 -2.2613 -4.1676 -0.9471 0.1930 0.1127 3.7331 0.8793 3.3487 0.1551 0.2918 1.3931 0.0364 1.1464 0.0683
+#> 248: 92.6855 -5.9212 -2.2604 -4.1671 -0.9476 0.1935 0.1116 3.7055 0.8795 3.3451 0.1549 0.2923 1.3942 0.0363 1.1453 0.0684
+#> 249: 92.6848 -5.9190 -2.2600 -4.1667 -0.9482 0.1939 0.1110 3.6857 0.8801 3.3428 0.1548 0.2923 1.3942 0.0363 1.1440 0.0685
+#> 250: 92.6858 -5.9194 -2.2605 -4.1663 -0.9489 0.1945 0.1109 3.6821 0.8806 3.3397 0.1547 0.2920 1.3932 0.0363 1.1430 0.0686
+#> 251: 92.6849 -5.9179 -2.2610 -4.1665 -0.9492 0.1950 0.1111 3.6795 0.8814 3.3392 0.1550 0.2919 1.3922 0.0364 1.1434 0.0685
+#> 252: 92.6848 -5.9141 -2.2615 -4.1660 -0.9493 0.1957 0.1110 3.6611 0.8818 3.3363 0.1548 0.2918 1.3919 0.0364 1.1423 0.0686
+#> 253: 92.6837 -5.9110 -2.2637 -4.1634 -0.9493 0.1952 0.1114 3.6462 0.8788 3.3481 0.1550 0.2920 1.3941 0.0363 1.1417 0.0688
+#> 254: 92.6827 -5.9082 -2.2650 -4.1608 -0.9492 0.1944 0.1117 3.6309 0.8753 3.3595 0.1548 0.2921 1.3964 0.0361 1.1415 0.0688
+#> 255: 92.6829 -5.9076 -2.2662 -4.1585 -0.9495 0.1934 0.1118 3.6221 0.8723 3.3737 0.1547 0.2923 1.3977 0.0359 1.1397 0.0689
+#> 256: 92.6821 -5.9079 -2.2672 -4.1559 -0.9495 0.1923 0.1118 3.6279 0.8697 3.3865 0.1547 0.2925 1.3990 0.0357 1.1387 0.0691
+#> 257: 92.6822 -5.9054 -2.2686 -4.1534 -0.9499 0.1914 0.1119 3.6202 0.8673 3.3988 0.1548 0.2923 1.4010 0.0356 1.1438 0.0690
+#> 258: 92.6828 -5.9054 -2.2700 -4.1509 -0.9498 0.1900 0.1121 3.6166 0.8651 3.4085 0.1547 0.2926 1.4028 0.0356 1.1473 0.0688
+#> 259: 92.6842 -5.9087 -2.2710 -4.1474 -0.9496 0.1890 0.1128 3.6314 0.8629 3.4154 0.1548 0.2923 1.4040 0.0355 1.1482 0.0689
+#> 260: 92.6852 -5.9118 -2.2717 -4.1444 -0.9493 0.1885 0.1124 3.6485 0.8606 3.4227 0.1544 0.2919 1.4073 0.0354 1.1518 0.0688
+#> 261: 92.6858 -5.9137 -2.2721 -4.1419 -0.9493 0.1882 0.1122 3.6641 0.8581 3.4314 0.1543 0.2913 1.4106 0.0353 1.1577 0.0684
+#> 262: 92.6861 -5.9117 -2.2726 -4.1394 -0.9493 0.1881 0.1116 3.6572 0.8558 3.4391 0.1541 0.2908 1.4137 0.0352 1.1613 0.0682
+#> 263: 92.6855 -5.9124 -2.2730 -4.1372 -0.9494 0.1875 0.1113 3.6626 0.8533 3.4465 0.1541 0.2905 1.4152 0.0351 1.1636 0.0681
+#> 264: 92.6841 -5.9137 -2.2734 -4.1351 -0.9496 0.1871 0.1109 3.6703 0.8505 3.4529 0.1538 0.2903 1.4156 0.0350 1.1632 0.0681
+#> 265: 92.6833 -5.9153 -2.2741 -4.1327 -0.9498 0.1867 0.1108 3.6816 0.8472 3.4581 0.1535 0.2899 1.4168 0.0350 1.1647 0.0679
+#> 266: 92.6835 -5.9147 -2.2752 -4.1307 -0.9497 0.1865 0.1107 3.6768 0.8450 3.4641 0.1531 0.2896 1.4176 0.0349 1.1640 0.0679
+#> 267: 92.6835 -5.9167 -2.2761 -4.1283 -0.9499 0.1862 0.1105 3.6851 0.8430 3.4700 0.1530 0.2892 1.4178 0.0348 1.1639 0.0679
+#> 268: 92.6841 -5.9141 -2.2767 -4.1269 -0.9503 0.1860 0.1107 3.6718 0.8407 3.4775 0.1533 0.2891 1.4187 0.0348 1.1673 0.0677
+#> 269: 92.6845 -5.9094 -2.2774 -4.1253 -0.9503 0.1855 0.1112 3.6520 0.8384 3.4840 0.1535 0.2890 1.4192 0.0348 1.1686 0.0675
+#> 270: 92.6847 -5.9042 -2.2779 -4.1239 -0.9505 0.1853 0.1107 3.6288 0.8365 3.4895 0.1536 0.2889 1.4192 0.0347 1.1698 0.0675
+#> 271: 92.6849 -5.9000 -2.2785 -4.1228 -0.9506 0.1853 0.1102 3.6083 0.8348 3.4956 0.1536 0.2889 1.4191 0.0346 1.1692 0.0676
+#> 272: 92.6850 -5.8965 -2.2794 -4.1223 -0.9507 0.1853 0.1092 3.5892 0.8331 3.5071 0.1538 0.2889 1.4194 0.0345 1.1700 0.0676
+#> 273: 92.6851 -5.8916 -2.2805 -4.1222 -0.9508 0.1850 0.1089 3.5697 0.8315 3.5211 0.1538 0.2889 1.4209 0.0345 1.1720 0.0675
+#> 274: 92.6849 -5.8898 -2.2815 -4.1218 -0.9506 0.1852 0.1084 3.5607 0.8301 3.5339 0.1542 0.2886 1.4221 0.0344 1.1728 0.0675
+#> 275: 92.6844 -5.8885 -2.2830 -4.1215 -0.9504 0.1855 0.1080 3.5514 0.8284 3.5491 0.1545 0.2883 1.4238 0.0343 1.1756 0.0673
+#> 276: 92.6834 -5.8885 -2.2843 -4.1210 -0.9501 0.1859 0.1077 3.5477 0.8272 3.5648 0.1547 0.2878 1.4243 0.0343 1.1749 0.0674
+#> 277: 92.6829 -5.8892 -2.2858 -4.1208 -0.9500 0.1862 0.1071 3.5505 0.8257 3.5807 0.1552 0.2872 1.4244 0.0343 1.1747 0.0674
+#> 278: 92.6825 -5.8885 -2.2871 -4.1205 -0.9499 0.1862 0.1072 3.5463 0.8245 3.5960 0.1555 0.2866 1.4247 0.0343 1.1742 0.0675
+#> 279: 92.6815 -5.8887 -2.2883 -4.1201 -0.9501 0.1864 0.1072 3.5433 0.8239 3.6088 0.1556 0.2860 1.4247 0.0343 1.1737 0.0676
+#> 280: 92.6800 -5.8901 -2.2896 -4.1211 -0.9503 0.1865 0.1078 3.5481 0.8238 3.6285 0.1556 0.2848 1.4252 0.0344 1.1742 0.0676
+#> 281: 92.6779 -5.8914 -2.2907 -4.1218 -0.9502 0.1865 0.1084 3.5491 0.8240 3.6471 0.1558 0.2838 1.4251 0.0343 1.1732 0.0677
+#> 282: 92.6767 -5.8906 -2.2919 -4.1236 -0.9501 0.1862 0.1091 3.5462 0.8248 3.6747 0.1558 0.2825 1.4250 0.0344 1.1732 0.0677
+#> 283: 92.6750 -5.8895 -2.2928 -4.1253 -0.9499 0.1857 0.1097 3.5418 0.8260 3.7025 0.1555 0.2814 1.4253 0.0344 1.1712 0.0678
+#> 284: 92.6736 -5.8903 -2.2934 -4.1271 -0.9497 0.1854 0.1107 3.5438 0.8269 3.7297 0.1553 0.2800 1.4257 0.0343 1.1698 0.0678
+#> 285: 92.6730 -5.8917 -2.2942 -4.1284 -0.9497 0.1852 0.1116 3.5481 0.8274 3.7528 0.1551 0.2787 1.4260 0.0343 1.1689 0.0678
+#> 286: 92.6715 -5.8913 -2.2947 -4.1285 -0.9492 0.1849 0.1122 3.5473 0.8274 3.7660 0.1550 0.2775 1.4265 0.0342 1.1678 0.0679
+#> 287: 92.6702 -5.8925 -2.2952 -4.1290 -0.9489 0.1846 0.1125 3.5531 0.8268 3.7818 0.1549 0.2764 1.4269 0.0342 1.1673 0.0678
+#> 288: 92.6688 -5.8918 -2.2959 -4.1290 -0.9490 0.1843 0.1126 3.5495 0.8262 3.7946 0.1546 0.2756 1.4275 0.0341 1.1673 0.0678
+#> 289: 92.6673 -5.8907 -2.2966 -4.1295 -0.9490 0.1841 0.1124 3.5445 0.8260 3.8067 0.1543 0.2750 1.4280 0.0342 1.1690 0.0677
+#> 290: 92.6657 -5.8909 -2.2973 -4.1302 -0.9490 0.1838 0.1123 3.5433 0.8260 3.8201 0.1540 0.2744 1.4279 0.0342 1.1687 0.0676
+#> 291: 92.6642 -5.8902 -2.2978 -4.1312 -0.9493 0.1835 0.1124 3.5399 0.8262 3.8365 0.1538 0.2738 1.4279 0.0342 1.1695 0.0676
+#> 292: 92.6635 -5.8917 -2.2983 -4.1316 -0.9495 0.1831 0.1121 3.5453 0.8263 3.8517 0.1535 0.2733 1.4275 0.0342 1.1695 0.0675
+#> 293: 92.6622 -5.8936 -2.2991 -4.1323 -0.9497 0.1830 0.1121 3.5526 0.8265 3.8692 0.1533 0.2728 1.4274 0.0342 1.1701 0.0675
+#> 294: 92.6604 -5.8936 -2.2999 -4.1328 -0.9499 0.1826 0.1126 3.5505 0.8263 3.8838 0.1533 0.2723 1.4273 0.0342 1.1712 0.0675
+#> 295: 92.6593 -5.8924 -2.3007 -4.1329 -0.9498 0.1823 0.1131 3.5443 0.8262 3.9004 0.1531 0.2717 1.4276 0.0342 1.1718 0.0674
+#> 296: 92.6586 -5.8906 -2.3016 -4.1323 -0.9496 0.1822 0.1133 3.5374 0.8266 3.9103 0.1530 0.2707 1.4272 0.0343 1.1714 0.0674
+#> 297: 92.6578 -5.8889 -2.3026 -4.1329 -0.9494 0.1819 0.1139 3.5315 0.8271 3.9280 0.1528 0.2697 1.4267 0.0343 1.1697 0.0675
+#> 298: 92.6575 -5.8885 -2.3036 -4.1330 -0.9490 0.1814 0.1143 3.5303 0.8275 3.9410 0.1527 0.2689 1.4263 0.0344 1.1688 0.0675
+#> 299: 92.6566 -5.8879 -2.3047 -4.1329 -0.9488 0.1807 0.1147 3.5286 0.8282 3.9507 0.1526 0.2679 1.4263 0.0345 1.1680 0.0674
+#> 300: 92.6555 -5.8862 -2.3057 -4.1325 -0.9483 0.1802 0.1151 3.5225 0.8293 3.9582 0.1527 0.2671 1.4261 0.0345 1.1677 0.0674
+#> 301: 92.6545 -5.8854 -2.3067 -4.1326 -0.9480 0.1795 0.1156 3.5191 0.8300 3.9691 0.1530 0.2665 1.4257 0.0346 1.1672 0.0674
+#> 302: 92.6539 -5.8839 -2.3078 -4.1322 -0.9477 0.1788 0.1161 3.5154 0.8309 3.9769 0.1532 0.2657 1.4252 0.0346 1.1664 0.0675
+#> 303: 92.6541 -5.8799 -2.3089 -4.1327 -0.9474 0.1782 0.1161 3.5012 0.8319 3.9913 0.1534 0.2649 1.4242 0.0347 1.1653 0.0675
+#> 304: 92.6554 -5.8766 -2.3096 -4.1326 -0.9472 0.1774 0.1164 3.4879 0.8328 3.9978 0.1536 0.2641 1.4234 0.0348 1.1644 0.0675
+#> 305: 92.6559 -5.8732 -2.3104 -4.1325 -0.9470 0.1764 0.1161 3.4740 0.8334 4.0037 0.1535 0.2633 1.4231 0.0348 1.1634 0.0676
+#> 306: 92.6564 -5.8717 -2.3113 -4.1322 -0.9470 0.1758 0.1161 3.4705 0.8341 4.0097 0.1537 0.2622 1.4236 0.0348 1.1628 0.0676
+#> 307: 92.6573 -5.8703 -2.3121 -4.1320 -0.9469 0.1748 0.1158 3.4630 0.8349 4.0154 0.1538 0.2614 1.4231 0.0348 1.1617 0.0677
+#> 308: 92.6578 -5.8695 -2.3129 -4.1318 -0.9465 0.1738 0.1154 3.4585 0.8356 4.0210 0.1540 0.2607 1.4229 0.0348 1.1604 0.0677
+#> 309: 92.6577 -5.8691 -2.3132 -4.1317 -0.9465 0.1732 0.1151 3.4548 0.8369 4.0270 0.1540 0.2596 1.4233 0.0348 1.1589 0.0678
+#> 310: 92.6580 -5.8680 -2.3135 -4.1309 -0.9466 0.1727 0.1147 3.4472 0.8377 4.0280 0.1540 0.2587 1.4231 0.0348 1.1569 0.0679
+#> 311: 92.6575 -5.8681 -2.3141 -4.1303 -0.9466 0.1722 0.1144 3.4477 0.8384 4.0303 0.1539 0.2577 1.4236 0.0348 1.1557 0.0679
+#> 312: 92.6571 -5.8685 -2.3145 -4.1299 -0.9467 0.1720 0.1143 3.4498 0.8393 4.0328 0.1538 0.2566 1.4237 0.0348 1.1545 0.0680
+#> 313: 92.6559 -5.8685 -2.3150 -4.1296 -0.9469 0.1718 0.1142 3.4483 0.8403 4.0358 0.1537 0.2555 1.4234 0.0348 1.1532 0.0681
+#> 314: 92.6543 -5.8699 -2.3155 -4.1294 -0.9471 0.1715 0.1142 3.4526 0.8404 4.0401 0.1537 0.2546 1.4236 0.0347 1.1522 0.0681
+#> 315: 92.6528 -5.8713 -2.3161 -4.1289 -0.9472 0.1712 0.1144 3.4584 0.8402 4.0427 0.1537 0.2538 1.4234 0.0347 1.1520 0.0682
+#> 316: 92.6510 -5.8726 -2.3166 -4.1283 -0.9472 0.1705 0.1146 3.4647 0.8404 4.0443 0.1537 0.2528 1.4236 0.0347 1.1511 0.0682
+#> 317: 92.6496 -5.8736 -2.3170 -4.1281 -0.9474 0.1699 0.1147 3.4701 0.8406 4.0497 0.1536 0.2520 1.4238 0.0347 1.1504 0.0683
+#> 318: 92.6479 -5.8745 -2.3174 -4.1276 -0.9475 0.1695 0.1153 3.4729 0.8410 4.0511 0.1535 0.2510 1.4238 0.0347 1.1503 0.0683
+#> 319: 92.6463 -5.8773 -2.3175 -4.1272 -0.9476 0.1690 0.1155 3.4868 0.8409 4.0527 0.1535 0.2502 1.4234 0.0347 1.1484 0.0685
+#> 320: 92.6447 -5.8770 -2.3179 -4.1263 -0.9478 0.1684 0.1158 3.4849 0.8407 4.0516 0.1534 0.2493 1.4238 0.0347 1.1483 0.0685
+#> 321: 92.6433 -5.8768 -2.3181 -4.1255 -0.9479 0.1679 0.1161 3.4850 0.8405 4.0511 0.1533 0.2485 1.4238 0.0346 1.1474 0.0686
+#> 322: 92.6425 -5.8766 -2.3182 -4.1246 -0.9480 0.1673 0.1161 3.4839 0.8403 4.0505 0.1530 0.2474 1.4243 0.0346 1.1458 0.0687
+#> 323: 92.6414 -5.8778 -2.3183 -4.1241 -0.9481 0.1669 0.1162 3.4888 0.8402 4.0517 0.1530 0.2466 1.4244 0.0346 1.1454 0.0687
+#> 324: 92.6404 -5.8771 -2.3186 -4.1236 -0.9482 0.1666 0.1161 3.4855 0.8401 4.0525 0.1529 0.2459 1.4247 0.0345 1.1446 0.0687
+#> 325: 92.6396 -5.8753 -2.3188 -4.1231 -0.9483 0.1664 0.1156 3.4767 0.8396 4.0533 0.1529 0.2454 1.4253 0.0345 1.1438 0.0689
+#> 326: 92.6397 -5.8766 -2.3192 -4.1226 -0.9484 0.1663 0.1152 3.4798 0.8389 4.0542 0.1527 0.2449 1.4253 0.0345 1.1431 0.0690
+#> 327: 92.6395 -5.8785 -2.3197 -4.1224 -0.9483 0.1660 0.1151 3.4880 0.8382 4.0557 0.1528 0.2445 1.4250 0.0345 1.1430 0.0690
+#> 328: 92.6397 -5.8805 -2.3202 -4.1221 -0.9483 0.1657 0.1153 3.5011 0.8373 4.0568 0.1528 0.2442 1.4246 0.0345 1.1427 0.0690
+#> 329: 92.6390 -5.8838 -2.3208 -4.1219 -0.9482 0.1655 0.1161 3.5176 0.8365 4.0580 0.1530 0.2439 1.4241 0.0345 1.1429 0.0690
+#> 330: 92.6380 -5.8862 -2.3215 -4.1216 -0.9484 0.1653 0.1166 3.5286 0.8355 4.0584 0.1529 0.2437 1.4234 0.0346 1.1428 0.0690
+#> 331: 92.6367 -5.8867 -2.3223 -4.1206 -0.9484 0.1651 0.1165 3.5288 0.8348 4.0577 0.1528 0.2435 1.4233 0.0346 1.1429 0.0690
+#> 332: 92.6360 -5.8859 -2.3230 -4.1199 -0.9485 0.1650 0.1165 3.5235 0.8343 4.0572 0.1527 0.2433 1.4227 0.0346 1.1429 0.0689
+#> 333: 92.6361 -5.8839 -2.3237 -4.1194 -0.9485 0.1649 0.1162 3.5142 0.8340 4.0564 0.1527 0.2430 1.4224 0.0347 1.1429 0.0689
+#> 334: 92.6359 -5.8824 -2.3244 -4.1190 -0.9486 0.1649 0.1158 3.5070 0.8337 4.0567 0.1527 0.2424 1.4218 0.0347 1.1442 0.0689
+#> 335: 92.6366 -5.8826 -2.3250 -4.1186 -0.9485 0.1645 0.1157 3.5069 0.8334 4.0574 0.1527 0.2419 1.4214 0.0347 1.1448 0.0688
+#> 336: 92.6374 -5.8816 -2.3253 -4.1182 -0.9486 0.1644 0.1158 3.5034 0.8330 4.0580 0.1528 0.2415 1.4212 0.0347 1.1471 0.0687
+#> 337: 92.6378 -5.8810 -2.3258 -4.1176 -0.9487 0.1642 0.1159 3.5023 0.8325 4.0582 0.1528 0.2410 1.4212 0.0347 1.1467 0.0688
+#> 338: 92.6383 -5.8814 -2.3262 -4.1168 -0.9488 0.1637 0.1160 3.5028 0.8322 4.0571 0.1526 0.2409 1.4216 0.0346 1.1456 0.0689
+#> 339: 92.6392 -5.8808 -2.3266 -4.1160 -0.9490 0.1631 0.1161 3.4989 0.8318 4.0566 0.1524 0.2408 1.4220 0.0346 1.1441 0.0690
+#> 340: 92.6393 -5.8810 -2.3269 -4.1152 -0.9491 0.1626 0.1157 3.4997 0.8316 4.0564 0.1524 0.2407 1.4216 0.0346 1.1419 0.0692
+#> 341: 92.6394 -5.8807 -2.3272 -4.1148 -0.9492 0.1619 0.1153 3.4966 0.8308 4.0552 0.1523 0.2405 1.4218 0.0346 1.1415 0.0692
+#> 342: 92.6394 -5.8806 -2.3274 -4.1141 -0.9493 0.1612 0.1146 3.4936 0.8303 4.0537 0.1522 0.2405 1.4221 0.0346 1.1406 0.0692
+#> 343: 92.6398 -5.8819 -2.3277 -4.1134 -0.9494 0.1606 0.1141 3.4961 0.8297 4.0519 0.1522 0.2402 1.4219 0.0347 1.1404 0.0692
+#> 344: 92.6401 -5.8823 -2.3280 -4.1128 -0.9497 0.1599 0.1137 3.4963 0.8293 4.0504 0.1523 0.2400 1.4214 0.0346 1.1404 0.0692
+#> 345: 92.6404 -5.8829 -2.3283 -4.1124 -0.9498 0.1593 0.1136 3.4958 0.8289 4.0494 0.1523 0.2396 1.4214 0.0346 1.1398 0.0692
+#> 346: 92.6405 -5.8829 -2.3283 -4.1119 -0.9499 0.1587 0.1135 3.4953 0.8287 4.0484 0.1522 0.2394 1.4216 0.0346 1.1397 0.0692
+#> 347: 92.6404 -5.8833 -2.3288 -4.1117 -0.9500 0.1582 0.1133 3.4965 0.8289 4.0480 0.1521 0.2391 1.4211 0.0346 1.1388 0.0692
+#> 348: 92.6407 -5.8838 -2.3293 -4.1113 -0.9502 0.1578 0.1132 3.4978 0.8290 4.0471 0.1520 0.2388 1.4209 0.0346 1.1385 0.0692
+#> 349: 92.6409 -5.8847 -2.3299 -4.1110 -0.9503 0.1571 0.1128 3.5024 0.8290 4.0474 0.1519 0.2386 1.4207 0.0347 1.1379 0.0692
+#> 350: 92.6413 -5.8853 -2.3304 -4.1107 -0.9504 0.1567 0.1125 3.5037 0.8287 4.0478 0.1519 0.2383 1.4207 0.0347 1.1366 0.0693
+#> 351: 92.6415 -5.8868 -2.3310 -4.1104 -0.9504 0.1562 0.1122 3.5109 0.8287 4.0490 0.1518 0.2378 1.4208 0.0347 1.1364 0.0693
+#> 352: 92.6413 -5.8882 -2.3316 -4.1103 -0.9504 0.1557 0.1120 3.5196 0.8287 4.0517 0.1517 0.2375 1.4207 0.0346 1.1361 0.0693
+#> 353: 92.6414 -5.8890 -2.3322 -4.1101 -0.9503 0.1553 0.1117 3.5237 0.8290 4.0533 0.1517 0.2371 1.4202 0.0346 1.1345 0.0693
+#> 354: 92.6417 -5.8879 -2.3327 -4.1099 -0.9502 0.1548 0.1115 3.5206 0.8294 4.0546 0.1515 0.2368 1.4200 0.0346 1.1336 0.0694
+#> 355: 92.6417 -5.8882 -2.3333 -4.1096 -0.9500 0.1541 0.1115 3.5265 0.8296 4.0548 0.1514 0.2364 1.4203 0.0346 1.1325 0.0694
+#> 356: 92.6414 -5.8881 -2.3338 -4.1093 -0.9497 0.1535 0.1115 3.5339 0.8299 4.0553 0.1513 0.2362 1.4204 0.0346 1.1318 0.0694
+#> 357: 92.6414 -5.8874 -2.3343 -4.1087 -0.9497 0.1529 0.1117 3.5320 0.8302 4.0548 0.1512 0.2358 1.4205 0.0346 1.1315 0.0694
+#> 358: 92.6415 -5.8865 -2.3349 -4.1087 -0.9497 0.1523 0.1118 3.5274 0.8308 4.0583 0.1510 0.2354 1.4206 0.0346 1.1308 0.0695
+#> 359: 92.6415 -5.8855 -2.3352 -4.1085 -0.9497 0.1518 0.1123 3.5208 0.8308 4.0597 0.1509 0.2349 1.4205 0.0346 1.1298 0.0695
+#> 360: 92.6413 -5.8851 -2.3356 -4.1080 -0.9496 0.1513 0.1125 3.5176 0.8308 4.0606 0.1508 0.2344 1.4207 0.0346 1.1289 0.0695
+#> 361: 92.6412 -5.8854 -2.3359 -4.1076 -0.9498 0.1508 0.1126 3.5187 0.8308 4.0618 0.1508 0.2338 1.4214 0.0345 1.1279 0.0695
+#> 362: 92.6415 -5.8861 -2.3362 -4.1072 -0.9499 0.1503 0.1126 3.5210 0.8306 4.0636 0.1507 0.2333 1.4218 0.0345 1.1273 0.0695
+#> 363: 92.6412 -5.8884 -2.3364 -4.1066 -0.9499 0.1498 0.1126 3.5327 0.8305 4.0646 0.1507 0.2328 1.4221 0.0345 1.1273 0.0695
+#> 364: 92.6411 -5.8895 -2.3367 -4.1062 -0.9501 0.1494 0.1126 3.5366 0.8306 4.0659 0.1507 0.2322 1.4227 0.0345 1.1280 0.0695
+#> 365: 92.6411 -5.8908 -2.3367 -4.1060 -0.9502 0.1489 0.1125 3.5405 0.8307 4.0690 0.1507 0.2317 1.4228 0.0344 1.1280 0.0695
+#> 366: 92.6412 -5.8926 -2.3366 -4.1062 -0.9502 0.1484 0.1125 3.5483 0.8307 4.0724 0.1507 0.2311 1.4228 0.0344 1.1280 0.0695
+#> 367: 92.6406 -5.8940 -2.3366 -4.1059 -0.9503 0.1483 0.1124 3.5557 0.8308 4.0738 0.1507 0.2305 1.4228 0.0344 1.1273 0.0695
+#> 368: 92.6402 -5.8940 -2.3365 -4.1059 -0.9504 0.1483 0.1122 3.5538 0.8306 4.0773 0.1507 0.2299 1.4228 0.0344 1.1266 0.0696
+#> 369: 92.6398 -5.8933 -2.3366 -4.1058 -0.9504 0.1482 0.1122 3.5489 0.8303 4.0796 0.1507 0.2295 1.4228 0.0343 1.1261 0.0696
+#> 370: 92.6394 -5.8928 -2.3366 -4.1059 -0.9504 0.1481 0.1123 3.5445 0.8302 4.0819 0.1506 0.2291 1.4229 0.0343 1.1258 0.0696
+#> 371: 92.6390 -5.8930 -2.3369 -4.1062 -0.9503 0.1481 0.1125 3.5446 0.8299 4.0854 0.1506 0.2285 1.4230 0.0343 1.1257 0.0696
+#> 372: 92.6387 -5.8926 -2.3372 -4.1064 -0.9503 0.1482 0.1125 3.5424 0.8298 4.0887 0.1505 0.2281 1.4234 0.0343 1.1262 0.0696
+#> 373: 92.6385 -5.8927 -2.3376 -4.1067 -0.9502 0.1483 0.1126 3.5447 0.8297 4.0919 0.1504 0.2275 1.4236 0.0343 1.1268 0.0696
+#> 374: 92.6382 -5.8932 -2.3380 -4.1064 -0.9502 0.1481 0.1131 3.5490 0.8295 4.0929 0.1503 0.2272 1.4238 0.0343 1.1267 0.0696
+#> 375: 92.6385 -5.8944 -2.3383 -4.1062 -0.9502 0.1481 0.1136 3.5562 0.8292 4.0936 0.1503 0.2269 1.4240 0.0343 1.1274 0.0695
+#> 376: 92.6388 -5.8942 -2.3387 -4.1061 -0.9502 0.1481 0.1141 3.5575 0.8295 4.0942 0.1502 0.2267 1.4236 0.0343 1.1272 0.0695
+#> 377: 92.6389 -5.8942 -2.3392 -4.1060 -0.9502 0.1482 0.1145 3.5579 0.8298 4.0950 0.1501 0.2264 1.4233 0.0344 1.1272 0.0695
+#> 378: 92.6388 -5.8939 -2.3397 -4.1060 -0.9502 0.1481 0.1150 3.5558 0.8298 4.0959 0.1500 0.2261 1.4232 0.0344 1.1271 0.0695
+#> 379: 92.6388 -5.8934 -2.3399 -4.1062 -0.9500 0.1483 0.1153 3.5521 0.8294 4.0980 0.1500 0.2257 1.4236 0.0344 1.1279 0.0694
+#> 380: 92.6390 -5.8920 -2.3402 -4.1065 -0.9499 0.1484 0.1155 3.5446 0.8292 4.1007 0.1500 0.2254 1.4241 0.0344 1.1285 0.0694
+#> 381: 92.6394 -5.8906 -2.3404 -4.1069 -0.9498 0.1485 0.1157 3.5378 0.8290 4.1040 0.1500 0.2250 1.4249 0.0343 1.1296 0.0694
+#> 382: 92.6403 -5.8893 -2.3406 -4.1085 -0.9498 0.1487 0.1157 3.5319 0.8289 4.1195 0.1500 0.2246 1.4250 0.0343 1.1301 0.0694
+#> 383: 92.6402 -5.8882 -2.3408 -4.1096 -0.9499 0.1488 0.1155 3.5269 0.8287 4.1290 0.1500 0.2243 1.4253 0.0343 1.1300 0.0694
+#> 384: 92.6401 -5.8871 -2.3412 -4.1102 -0.9498 0.1490 0.1155 3.5219 0.8285 4.1340 0.1499 0.2241 1.4254 0.0343 1.1297 0.0694
+#> 385: 92.6396 -5.8867 -2.3417 -4.1105 -0.9497 0.1493 0.1155 3.5195 0.8281 4.1364 0.1498 0.2238 1.4252 0.0343 1.1297 0.0695
+#> 386: 92.6393 -5.8863 -2.3423 -4.1116 -0.9496 0.1497 0.1153 3.5190 0.8280 4.1452 0.1497 0.2235 1.4251 0.0343 1.1307 0.0694
+#> 387: 92.6391 -5.8865 -2.3429 -4.1124 -0.9495 0.1498 0.1155 3.5219 0.8280 4.1502 0.1497 0.2234 1.4247 0.0343 1.1301 0.0695
+#> 388: 92.6389 -5.8861 -2.3436 -4.1129 -0.9494 0.1501 0.1158 3.5228 0.8278 4.1540 0.1496 0.2233 1.4243 0.0343 1.1293 0.0695
+#> 389: 92.6384 -5.8849 -2.3442 -4.1132 -0.9491 0.1504 0.1159 3.5195 0.8276 4.1571 0.1496 0.2231 1.4242 0.0343 1.1284 0.0696
+#> 390: 92.6382 -5.8838 -2.3447 -4.1134 -0.9489 0.1506 0.1159 3.5172 0.8276 4.1603 0.1497 0.2230 1.4242 0.0343 1.1273 0.0697
+#> 391: 92.6380 -5.8821 -2.3454 -4.1140 -0.9486 0.1509 0.1159 3.5134 0.8274 4.1661 0.1498 0.2228 1.4238 0.0343 1.1266 0.0697
+#> 392: 92.6374 -5.8800 -2.3460 -4.1140 -0.9485 0.1513 0.1158 3.5069 0.8274 4.1673 0.1499 0.2226 1.4235 0.0343 1.1258 0.0698
+#> 393: 92.6372 -5.8785 -2.3467 -4.1140 -0.9485 0.1514 0.1159 3.5019 0.8275 4.1684 0.1499 0.2223 1.4232 0.0343 1.1258 0.0698
+#> 394: 92.6372 -5.8765 -2.3473 -4.1142 -0.9485 0.1515 0.1161 3.4955 0.8275 4.1710 0.1499 0.2221 1.4228 0.0344 1.1260 0.0697
+#> 395: 92.6371 -5.8761 -2.3476 -4.1145 -0.9485 0.1515 0.1164 3.4940 0.8273 4.1739 0.1498 0.2220 1.4227 0.0344 1.1254 0.0698
+#> 396: 92.6370 -5.8759 -2.3480 -4.1147 -0.9485 0.1516 0.1166 3.4942 0.8269 4.1764 0.1498 0.2217 1.4222 0.0344 1.1252 0.0698
+#> 397: 92.6371 -5.8756 -2.3483 -4.1149 -0.9486 0.1516 0.1167 3.4914 0.8267 4.1796 0.1498 0.2214 1.4219 0.0344 1.1253 0.0697
+#> 398: 92.6371 -5.8756 -2.3486 -4.1155 -0.9486 0.1518 0.1167 3.4909 0.8268 4.1840 0.1498 0.2210 1.4216 0.0344 1.1250 0.0697
+#> 399: 92.6368 -5.8765 -2.3489 -4.1157 -0.9485 0.1519 0.1170 3.4958 0.8266 4.1866 0.1498 0.2205 1.4213 0.0344 1.1245 0.0698
+#> 400: 92.6368 -5.8769 -2.3491 -4.1158 -0.9485 0.1522 0.1174 3.4972 0.8266 4.1888 0.1499 0.2200 1.4209 0.0344 1.1242 0.0698
+#> 401: 92.6366 -5.8768 -2.3493 -4.1161 -0.9484 0.1524 0.1175 3.4964 0.8267 4.1913 0.1499 0.2196 1.4204 0.0344 1.1240 0.0698
+#> 402: 92.6362 -5.8767 -2.3495 -4.1164 -0.9483 0.1525 0.1176 3.4961 0.8267 4.1937 0.1499 0.2192 1.4201 0.0344 1.1240 0.0698
+#> 403: 92.6362 -5.8769 -2.3497 -4.1166 -0.9483 0.1526 0.1178 3.4981 0.8270 4.1960 0.1499 0.2187 1.4197 0.0345 1.1236 0.0698
+#> 404: 92.6359 -5.8772 -2.3499 -4.1166 -0.9483 0.1527 0.1179 3.4997 0.8272 4.1968 0.1499 0.2183 1.4193 0.0345 1.1232 0.0698
+#> 405: 92.6355 -5.8763 -2.3501 -4.1165 -0.9483 0.1527 0.1180 3.4946 0.8273 4.1976 0.1500 0.2180 1.4189 0.0345 1.1230 0.0698
+#> 406: 92.6351 -5.8768 -2.3503 -4.1164 -0.9482 0.1528 0.1184 3.4953 0.8274 4.1979 0.1500 0.2176 1.4184 0.0345 1.1227 0.0698
+#> 407: 92.6346 -5.8772 -2.3505 -4.1165 -0.9481 0.1527 0.1187 3.4965 0.8275 4.1999 0.1500 0.2173 1.4182 0.0344 1.1222 0.0698
+#> 408: 92.6344 -5.8786 -2.3508 -4.1167 -0.9482 0.1528 0.1190 3.5025 0.8276 4.2020 0.1500 0.2171 1.4178 0.0344 1.1215 0.0699
+#> 409: 92.6342 -5.8806 -2.3511 -4.1168 -0.9484 0.1529 0.1193 3.5134 0.8277 4.2037 0.1500 0.2167 1.4176 0.0344 1.1212 0.0699
+#> 410: 92.6341 -5.8826 -2.3514 -4.1170 -0.9486 0.1531 0.1193 3.5229 0.8279 4.2061 0.1500 0.2163 1.4175 0.0344 1.1212 0.0699
+#> 411: 92.6339 -5.8840 -2.3517 -4.1172 -0.9488 0.1532 0.1192 3.5280 0.8280 4.2087 0.1499 0.2159 1.4175 0.0345 1.1208 0.0699
+#> 412: 92.6338 -5.8850 -2.3520 -4.1175 -0.9489 0.1534 0.1193 3.5311 0.8280 4.2121 0.1497 0.2155 1.4177 0.0345 1.1204 0.0699
+#> 413: 92.6343 -5.8859 -2.3523 -4.1177 -0.9491 0.1536 0.1191 3.5337 0.8282 4.2156 0.1497 0.2151 1.4176 0.0345 1.1198 0.0699
+#> 414: 92.6350 -5.8861 -2.3526 -4.1184 -0.9491 0.1540 0.1191 3.5350 0.8283 4.2209 0.1496 0.2147 1.4177 0.0345 1.1196 0.0699
+#> 415: 92.6354 -5.8866 -2.3528 -4.1191 -0.9492 0.1543 0.1191 3.5373 0.8284 4.2258 0.1496 0.2142 1.4179 0.0345 1.1191 0.0699
+#> 416: 92.6360 -5.8873 -2.3531 -4.1201 -0.9493 0.1548 0.1193 3.5431 0.8286 4.2328 0.1495 0.2137 1.4178 0.0345 1.1187 0.0699
+#> 417: 92.6361 -5.8878 -2.3533 -4.1213 -0.9494 0.1551 0.1192 3.5465 0.8288 4.2415 0.1494 0.2131 1.4182 0.0345 1.1189 0.0699
+#> 418: 92.6366 -5.8883 -2.3535 -4.1221 -0.9495 0.1555 0.1194 3.5499 0.8291 4.2477 0.1493 0.2127 1.4180 0.0345 1.1184 0.0699
+#> 419: 92.6367 -5.8885 -2.3536 -4.1236 -0.9495 0.1560 0.1195 3.5517 0.8292 4.2588 0.1492 0.2123 1.4179 0.0345 1.1180 0.0700
+#> 420: 92.6371 -5.8874 -2.3536 -4.1249 -0.9495 0.1564 0.1197 3.5474 0.8293 4.2666 0.1491 0.2118 1.4181 0.0345 1.1182 0.0700
+#> 421: 92.6374 -5.8860 -2.3537 -4.1263 -0.9494 0.1569 0.1197 3.5416 0.8292 4.2759 0.1492 0.2114 1.4184 0.0345 1.1188 0.0699
+#> 422: 92.6377 -5.8850 -2.3538 -4.1279 -0.9493 0.1572 0.1197 3.5365 0.8292 4.2865 0.1491 0.2110 1.4185 0.0345 1.1188 0.0700
+#> 423: 92.6380 -5.8844 -2.3540 -4.1299 -0.9494 0.1576 0.1196 3.5323 0.8290 4.2999 0.1491 0.2106 1.4186 0.0345 1.1192 0.0699
+#> 424: 92.6382 -5.8842 -2.3541 -4.1312 -0.9495 0.1581 0.1198 3.5309 0.8290 4.3092 0.1491 0.2103 1.4184 0.0345 1.1197 0.0699
+#> 425: 92.6382 -5.8838 -2.3543 -4.1320 -0.9495 0.1584 0.1197 3.5281 0.8289 4.3140 0.1491 0.2099 1.4185 0.0346 1.1196 0.0699
+#> 426: 92.6380 -5.8829 -2.3545 -4.1327 -0.9494 0.1587 0.1196 3.5234 0.8293 4.3183 0.1491 0.2096 1.4182 0.0346 1.1194 0.0699
+#> 427: 92.6375 -5.8823 -2.3548 -4.1335 -0.9494 0.1589 0.1197 3.5189 0.8295 4.3233 0.1492 0.2092 1.4180 0.0346 1.1196 0.0699
+#> 428: 92.6370 -5.8813 -2.3552 -4.1343 -0.9494 0.1592 0.1199 3.5140 0.8295 4.3286 0.1491 0.2088 1.4182 0.0346 1.1198 0.0699
+#> 429: 92.6368 -5.8802 -2.3556 -4.1356 -0.9495 0.1597 0.1202 3.5093 0.8296 4.3372 0.1491 0.2086 1.4182 0.0346 1.1208 0.0699
+#> 430: 92.6370 -5.8794 -2.3560 -4.1366 -0.9496 0.1602 0.1201 3.5058 0.8297 4.3439 0.1492 0.2084 1.4183 0.0346 1.1216 0.0698
+#> 431: 92.6371 -5.8792 -2.3564 -4.1372 -0.9497 0.1606 0.1201 3.5029 0.8298 4.3473 0.1493 0.2082 1.4182 0.0346 1.1215 0.0698
+#> 432: 92.6371 -5.8793 -2.3567 -4.1377 -0.9499 0.1609 0.1201 3.5008 0.8297 4.3499 0.1494 0.2080 1.4180 0.0346 1.1218 0.0698
+#> 433: 92.6370 -5.8799 -2.3570 -4.1387 -0.9501 0.1612 0.1201 3.5014 0.8298 4.3560 0.1495 0.2078 1.4180 0.0346 1.1218 0.0699
+#> 434: 92.6371 -5.8790 -2.3573 -4.1398 -0.9501 0.1615 0.1200 3.4982 0.8300 4.3624 0.1496 0.2076 1.4179 0.0346 1.1213 0.0699
+#> 435: 92.6368 -5.8789 -2.3576 -4.1409 -0.9501 0.1619 0.1199 3.4979 0.8302 4.3697 0.1496 0.2074 1.4176 0.0346 1.1205 0.0699
+#> 436: 92.6365 -5.8792 -2.3579 -4.1424 -0.9500 0.1623 0.1197 3.4987 0.8304 4.3798 0.1497 0.2073 1.4173 0.0346 1.1198 0.0699
+#> 437: 92.6364 -5.8798 -2.3582 -4.1439 -0.9500 0.1627 0.1195 3.5017 0.8307 4.3905 0.1497 0.2071 1.4172 0.0346 1.1191 0.0700
+#> 438: 92.6362 -5.8803 -2.3585 -4.1450 -0.9499 0.1631 0.1193 3.5053 0.8309 4.3973 0.1497 0.2070 1.4172 0.0346 1.1186 0.0700
+#> 439: 92.6361 -5.8811 -2.3588 -4.1463 -0.9498 0.1634 0.1190 3.5101 0.8312 4.4052 0.1496 0.2069 1.4172 0.0346 1.1188 0.0700
+#> 440: 92.6360 -5.8816 -2.3591 -4.1477 -0.9498 0.1637 0.1187 3.5127 0.8315 4.4145 0.1495 0.2068 1.4172 0.0346 1.1189 0.0700
+#> 441: 92.6357 -5.8816 -2.3594 -4.1492 -0.9499 0.1640 0.1185 3.5136 0.8319 4.4252 0.1494 0.2069 1.4175 0.0346 1.1191 0.0700
+#> 442: 92.6356 -5.8819 -2.3596 -4.1501 -0.9500 0.1642 0.1181 3.5151 0.8323 4.4310 0.1494 0.2070 1.4176 0.0346 1.1193 0.0700
+#> 443: 92.6356 -5.8825 -2.3598 -4.1512 -0.9501 0.1643 0.1180 3.5178 0.8324 4.4379 0.1493 0.2071 1.4179 0.0346 1.1196 0.0700
+#> 444: 92.6352 -5.8827 -2.3602 -4.1525 -0.9502 0.1644 0.1180 3.5169 0.8327 4.4458 0.1493 0.2073 1.4178 0.0346 1.1198 0.0700
+#> 445: 92.6348 -5.8828 -2.3605 -4.1534 -0.9502 0.1643 0.1180 3.5178 0.8329 4.4505 0.1493 0.2074 1.4178 0.0346 1.1202 0.0700
+#> 446: 92.6342 -5.8830 -2.3609 -4.1541 -0.9503 0.1643 0.1183 3.5182 0.8331 4.4539 0.1494 0.2077 1.4176 0.0346 1.1199 0.0700
+#> 447: 92.6334 -5.8832 -2.3613 -4.1548 -0.9503 0.1643 0.1188 3.5188 0.8333 4.4571 0.1494 0.2079 1.4172 0.0346 1.1198 0.0700
+#> 448: 92.6331 -5.8833 -2.3616 -4.1557 -0.9503 0.1643 0.1190 3.5190 0.8335 4.4613 0.1494 0.2080 1.4170 0.0346 1.1198 0.0700
+#> 449: 92.6327 -5.8835 -2.3619 -4.1563 -0.9504 0.1641 0.1192 3.5191 0.8335 4.4636 0.1493 0.2081 1.4172 0.0346 1.1196 0.0700
+#> 450: 92.6322 -5.8831 -2.3620 -4.1566 -0.9505 0.1639 0.1194 3.5152 0.8340 4.4647 0.1492 0.2083 1.4172 0.0346 1.1189 0.0700
+#> 451: 92.6315 -5.8835 -2.3622 -4.1569 -0.9505 0.1635 0.1194 3.5192 0.8343 4.4648 0.1492 0.2084 1.4169 0.0346 1.1187 0.0700
+#> 452: 92.6312 -5.8834 -2.3625 -4.1572 -0.9506 0.1632 0.1193 3.5173 0.8345 4.4654 0.1492 0.2086 1.4166 0.0346 1.1183 0.0700
+#> 453: 92.6309 -5.8838 -2.3628 -4.1574 -0.9506 0.1629 0.1193 3.5175 0.8348 4.4660 0.1493 0.2087 1.4166 0.0346 1.1180 0.0700
+#> 454: 92.6307 -5.8832 -2.3629 -4.1574 -0.9507 0.1625 0.1193 3.5128 0.8354 4.4658 0.1493 0.2087 1.4164 0.0346 1.1176 0.0700
+#> 455: 92.6305 -5.8821 -2.3632 -4.1579 -0.9508 0.1624 0.1192 3.5071 0.8360 4.4678 0.1494 0.2089 1.4164 0.0346 1.1171 0.0701
+#> 456: 92.6307 -5.8811 -2.3634 -4.1589 -0.9509 0.1623 0.1190 3.5014 0.8364 4.4730 0.1494 0.2088 1.4168 0.0346 1.1168 0.0701
+#> 457: 92.6307 -5.8808 -2.3636 -4.1597 -0.9509 0.1621 0.1188 3.4980 0.8368 4.4772 0.1494 0.2089 1.4168 0.0347 1.1166 0.0701
+#> 458: 92.6308 -5.8813 -2.3638 -4.1607 -0.9510 0.1621 0.1185 3.4994 0.8369 4.4823 0.1494 0.2088 1.4168 0.0347 1.1161 0.0701
+#> 459: 92.6308 -5.8819 -2.3639 -4.1615 -0.9511 0.1620 0.1184 3.5008 0.8371 4.4861 0.1494 0.2086 1.4167 0.0347 1.1155 0.0701
+#> 460: 92.6309 -5.8824 -2.3642 -4.1621 -0.9511 0.1621 0.1182 3.5024 0.8374 4.4886 0.1493 0.2085 1.4164 0.0347 1.1148 0.0702
+#> 461: 92.6309 -5.8821 -2.3647 -4.1631 -0.9511 0.1621 0.1181 3.5000 0.8378 4.4937 0.1493 0.2084 1.4160 0.0347 1.1141 0.0702
+#> 462: 92.6309 -5.8825 -2.3651 -4.1638 -0.9511 0.1623 0.1180 3.5006 0.8381 4.4975 0.1492 0.2082 1.4156 0.0348 1.1133 0.0702
+#> 463: 92.6307 -5.8824 -2.3656 -4.1654 -0.9510 0.1624 0.1179 3.5000 0.8382 4.5074 0.1491 0.2081 1.4154 0.0348 1.1124 0.0702
+#> 464: 92.6305 -5.8825 -2.3660 -4.1668 -0.9510 0.1625 0.1178 3.5001 0.8384 4.5171 0.1491 0.2080 1.4149 0.0348 1.1115 0.0703
+#> 465: 92.6302 -5.8828 -2.3664 -4.1681 -0.9511 0.1626 0.1179 3.5012 0.8386 4.5247 0.1490 0.2079 1.4151 0.0348 1.1107 0.0703
+#> 466: 92.6300 -5.8827 -2.3668 -4.1697 -0.9511 0.1626 0.1179 3.5005 0.8390 4.5370 0.1490 0.2079 1.4148 0.0349 1.1098 0.0704
+#> 467: 92.6301 -5.8828 -2.3671 -4.1721 -0.9512 0.1628 0.1180 3.4991 0.8393 4.5562 0.1490 0.2078 1.4148 0.0349 1.1092 0.0704
+#> 468: 92.6303 -5.8833 -2.3675 -4.1745 -0.9513 0.1630 0.1181 3.4996 0.8397 4.5756 0.1489 0.2078 1.4148 0.0349 1.1086 0.0704
+#> 469: 92.6304 -5.8835 -2.3680 -4.1759 -0.9513 0.1630 0.1181 3.4991 0.8401 4.5829 0.1490 0.2080 1.4145 0.0349 1.1082 0.0704
+#> 470: 92.6304 -5.8839 -2.3685 -4.1772 -0.9512 0.1630 0.1183 3.4993 0.8405 4.5904 0.1490 0.2081 1.4142 0.0349 1.1079 0.0704
+#> 471: 92.6304 -5.8838 -2.3690 -4.1786 -0.9511 0.1631 0.1182 3.4992 0.8408 4.5981 0.1489 0.2082 1.4143 0.0350 1.1075 0.0704
+#> 472: 92.6301 -5.8839 -2.3695 -4.1800 -0.9511 0.1631 0.1182 3.5005 0.8413 4.6063 0.1488 0.2083 1.4143 0.0350 1.1072 0.0704
+#> 473: 92.6296 -5.8841 -2.3699 -4.1811 -0.9510 0.1630 0.1182 3.5019 0.8417 4.6119 0.1487 0.2085 1.4142 0.0350 1.1065 0.0704
+#> 474: 92.6293 -5.8843 -2.3704 -4.1823 -0.9510 0.1629 0.1184 3.5038 0.8422 4.6182 0.1487 0.2087 1.4145 0.0350 1.1060 0.0704
+#> 475: 92.6293 -5.8851 -2.3709 -4.1839 -0.9509 0.1628 0.1185 3.5084 0.8426 4.6277 0.1487 0.2089 1.4142 0.0351 1.1057 0.0704
+#> 476: 92.6293 -5.8854 -2.3713 -4.1847 -0.9509 0.1627 0.1185 3.5137 0.8430 4.6318 0.1486 0.2092 1.4139 0.0351 1.1057 0.0704
+#> 477: 92.6292 -5.8858 -2.3718 -4.1859 -0.9508 0.1627 0.1183 3.5201 0.8430 4.6397 0.1485 0.2095 1.4139 0.0351 1.1060 0.0704
+#> 478: 92.6291 -5.8871 -2.3722 -4.1867 -0.9508 0.1625 0.1181 3.5291 0.8432 4.6449 0.1483 0.2098 1.4140 0.0351 1.1058 0.0704
+#> 479: 92.6293 -5.8891 -2.3726 -4.1873 -0.9509 0.1623 0.1178 3.5422 0.8435 4.6486 0.1482 0.2100 1.4139 0.0352 1.1056 0.0704
+#> 480: 92.6294 -5.8910 -2.3730 -4.1881 -0.9509 0.1622 0.1175 3.5568 0.8437 4.6535 0.1482 0.2102 1.4140 0.0352 1.1053 0.0705
+#> 481: 92.6297 -5.8919 -2.3734 -4.1888 -0.9509 0.1621 0.1174 3.5650 0.8440 4.6572 0.1482 0.2104 1.4138 0.0353 1.1051 0.0705
+#> 482: 92.6293 -5.8929 -2.3737 -4.1894 -0.9509 0.1619 0.1173 3.5745 0.8444 4.6620 0.1482 0.2107 1.4134 0.0353 1.1047 0.0705
+#> 483: 92.6284 -5.8939 -2.3741 -4.1901 -0.9508 0.1616 0.1176 3.5832 0.8446 4.6672 0.1482 0.2109 1.4131 0.0353 1.1044 0.0705
+#> 484: 92.6276 -5.8943 -2.3744 -4.1904 -0.9507 0.1615 0.1179 3.5877 0.8447 4.6692 0.1483 0.2113 1.4128 0.0353 1.1041 0.0705
+#> 485: 92.6266 -5.8947 -2.3746 -4.1912 -0.9507 0.1616 0.1182 3.5903 0.8448 4.6751 0.1483 0.2115 1.4126 0.0354 1.1042 0.0705
+#> 486: 92.6258 -5.8952 -2.3749 -4.1918 -0.9508 0.1615 0.1185 3.5929 0.8450 4.6799 0.1485 0.2115 1.4125 0.0354 1.1045 0.0704
+#> 487: 92.6250 -5.8956 -2.3750 -4.1923 -0.9509 0.1614 0.1189 3.5922 0.8452 4.6835 0.1486 0.2115 1.4122 0.0354 1.1050 0.0704
+#> 488: 92.6242 -5.8956 -2.3752 -4.1927 -0.9510 0.1613 0.1191 3.5898 0.8453 4.6866 0.1487 0.2115 1.4119 0.0354 1.1051 0.0704
+#> 489: 92.6238 -5.8954 -2.3753 -4.1932 -0.9511 0.1611 0.1190 3.5871 0.8454 4.6905 0.1487 0.2115 1.4118 0.0354 1.1057 0.0704
+#> 490: 92.6237 -5.8951 -2.3754 -4.1936 -0.9511 0.1611 0.1188 3.5839 0.8454 4.6945 0.1487 0.2114 1.4117 0.0354 1.1064 0.0703
+#> 491: 92.6235 -5.8942 -2.3755 -4.1941 -0.9511 0.1610 0.1187 3.5790 0.8455 4.6981 0.1488 0.2115 1.4118 0.0354 1.1068 0.0703
+#> 492: 92.6234 -5.8938 -2.3755 -4.1952 -0.9512 0.1609 0.1186 3.5760 0.8454 4.7074 0.1488 0.2115 1.4119 0.0354 1.1074 0.0703
+#> 493: 92.6236 -5.8938 -2.3755 -4.1958 -0.9512 0.1608 0.1186 3.5747 0.8454 4.7121 0.1488 0.2114 1.4120 0.0354 1.1078 0.0702
+#> 494: 92.6239 -5.8945 -2.3756 -4.1964 -0.9513 0.1607 0.1186 3.5772 0.8455 4.7167 0.1488 0.2115 1.4120 0.0354 1.1082 0.0702
+#> 495: 92.6242 -5.8950 -2.3756 -4.1971 -0.9514 0.1605 0.1187 3.5798 0.8454 4.7227 0.1489 0.2117 1.4122 0.0354 1.1084 0.0702
+#> 496: 92.6242 -5.8962 -2.3757 -4.1978 -0.9514 0.1603 0.1189 3.5870 0.8455 4.7283 0.1489 0.2119 1.4121 0.0354 1.1090 0.0702
+#> 497: 92.6241 -5.8972 -2.3757 -4.1981 -0.9514 0.1602 0.1191 3.5934 0.8454 4.7298 0.1488 0.2120 1.4123 0.0354 1.1096 0.0701
+#> 498: 92.6244 -5.8973 -2.3758 -4.1981 -0.9514 0.1601 0.1190 3.5947 0.8454 4.7296 0.1488 0.2121 1.4123 0.0354 1.1101 0.0701
+#> 499: 92.6244 -5.8968 -2.3759 -4.1980 -0.9514 0.1600 0.1188 3.5935 0.8453 4.7290 0.1488 0.2124 1.4123 0.0354 1.1108 0.0701
+#> 500: 92.6245 -5.8959 -2.3759 -4.1978 -0.9513 0.1597 0.1188 3.5912 0.8452 4.7282 0.1488 0.2126 1.4123 0.0354 1.1111 0.0701
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Model:
#> cmt(parent);
-#> cmt(A1);
-#> rx_expr_6~ETA[1]+THETA[1];
-#> parent(0)=rx_expr_6;
-#> rx_expr_7~ETA[4]+THETA[4];
-#> rx_expr_8~ETA[6]+THETA[6];
-#> rx_expr_9~ETA[5]+THETA[5];
-#> rx_expr_12~exp(rx_expr_7);
-#> rx_expr_13~exp(rx_expr_9);
-#> rx_expr_15~t*rx_expr_12;
-#> rx_expr_16~t*rx_expr_13;
-#> rx_expr_17~exp(-(rx_expr_8));
-#> rx_expr_19~1+rx_expr_17;
-#> rx_expr_24~1/(rx_expr_19);
-#> rx_expr_26~(rx_expr_24);
-#> rx_expr_27~1-rx_expr_26;
-#> d/dt(parent)=-parent*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));
-#> rx_expr_10~ETA[2]+THETA[2];
-#> rx_expr_14~exp(rx_expr_10);
-#> d/dt(A1)=-rx_expr_14*A1+parent*f_parent_to_A1*(exp(rx_expr_7-rx_expr_15)/(rx_expr_19)+exp(rx_expr_9-rx_expr_16)*(rx_expr_27))/(exp(-t*rx_expr_12)/(rx_expr_19)+exp(-t*rx_expr_13)*(rx_expr_27));
-#> rx_expr_0~CMT==2;
-#> rx_expr_1~CMT==1;
-#> rx_expr_2~1-(rx_expr_0);
-#> rx_yj_~2*(rx_expr_2)*(rx_expr_1)+2*(rx_expr_0);
-#> rx_expr_3~(rx_expr_0);
-#> rx_expr_5~(rx_expr_2);
-#> rx_expr_18~rx_expr_5*(rx_expr_1);
-#> rx_lambda_~rx_expr_18+rx_expr_3;
-#> rx_hi_~rx_expr_18+rx_expr_3;
-#> rx_low_~0;
-#> rx_expr_4~A1*(rx_expr_0);
-#> rx_expr_11~parent*(rx_expr_2);
-#> rx_expr_22~rx_expr_11*(rx_expr_1);
-#> rx_pred_=(rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1);
-#> rx_r_=(rx_expr_0)*(Rx_pow_di(((rx_expr_4+rx_expr_22)*(rx_expr_0)+(rx_expr_4+rx_expr_22)*(rx_expr_2)*(rx_expr_1)),2)*Rx_pow_di(THETA[10],2)+Rx_pow_di(THETA[9],2))+(Rx_pow_di(THETA[8],2)*Rx_pow_di(((rx_expr_4+rx_expr_22)*(rx_expr_1)),2)+Rx_pow_di(THETA[7],2))*(rx_expr_2)*(rx_expr_1);
-#> parent_0=THETA[1];
-#> log_k_A1=THETA[2];
-#> f_parent_qlogis=THETA[3];
-#> log_k1=THETA[4];
-#> log_k2=THETA[5];
-#> g_qlogis=THETA[6];
-#> sigma_low_parent=THETA[7];
-#> rsd_high_parent=THETA[8];
-#> sigma_low_A1=THETA[9];
-#> rsd_high_A1=THETA[10];
-#> eta.parent_0=ETA[1];
-#> eta.log_k_A1=ETA[2];
-#> eta.f_parent_qlogis=ETA[3];
-#> eta.log_k1=ETA[4];
-#> eta.log_k2=ETA[5];
-#> eta.g_qlogis=ETA[6];
-#> parent_0_model=rx_expr_6;
-#> k_A1=rx_expr_14;
-#> k1=rx_expr_12;
-#> k2=rx_expr_13;
-#> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
-#> g=1/(rx_expr_19);
-#> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL, lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL, control = foceiControl(), thetaNames = NULL, etaNames = NULL, etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) { set.seed(control$seed) .pt <- proc.time() RxODE::.setWarnIdSort(FALSE) on.exit(RxODE::.setWarnIdSort(TRUE)) loadNamespace("n1qn1") if (!RxODE::rxIs(control, "foceiControl")) { control <- do.call(foceiControl, control) } if (is.null(env)) { .ret <- new.env(parent = emptyenv()) } else { .ret <- env } .ret$origData <- data .ret$etaNames <- etaNames .ret$thetaFixed <- fixed .ret$control <- control .ret$control$focei.mu.ref <- integer(0) if (is(model, "RxODE") || is(model, "character")) { .ret$ODEmodel <- TRUE if (class(pred) != "function") { stop("pred must be a function specifying the prediction variables in this model.") } } else { .ret$ODEmodel <- TRUE model <- RxODE::rxGetLin(PKpars) pred <- eval(parse(text = "function(){return(Central);}")) } .square <- function(x) x * x .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform] if (is.null(err)) { err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]], collapse = ""), "}"))) } .covNames <- .parNames <- c() .ret$adjLik <- control$adjLik .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0 if (!exists("noLik", envir = .ret)) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state)) .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, interaction = (control$interaction == 1L), only.numeric = !.mixed, run.internal = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssAtol))) .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.ssRtol))) .ret$control$rxControl$ssAtol <- .ssAtol .ret$control$rxControl$ssRtol <- .ssRtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { if (.ret$noLik) { .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state)) .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state)) .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars, err, grad = FALSE, pred.minus.dv = TRUE, sum.prod = control$sumProd, theta.derivs = FALSE, optExpression = control$optExpression, run.internal = TRUE, only.numeric = TRUE, addProp = control$addProp) if (!is.null(.ret$model$inner)) { .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.atol))) .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) - length(.rtol))) .ret$control$rxControl$atol <- .atol .ret$control$rxControl$rtol <- .rtol } .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only) .covNames <- .covNames[regexpr(rex::rex(start, or("THETA", "ETA"), "[", numbers, "]", end), .covNames) == -1] colnames(data) <- sapply(names(data), function(x) { if (any(x == .covNames)) { return(x) } else { return(toupper(x)) } }) .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)), RxODE::rxLhs(.ret$model$pred.only)) if (length(.lhs) > 0) { .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs), end), .covNames) == -1] } if (length(.covNames) > 0) { if (!all(.covNames %in% names(data))) { message("Model:") RxODE::rxCat(.ret$model$pred.only) message("Needed Covariates:") nlmixrPrint(.covNames) stop("Not all the covariates are in the dataset.") } message("Needed Covariates:") print(.covNames) } .extraPars <- .ret$model$extra.pars } else { .extraPars <- NULL } } .ret$skipCov <- skipCov if (is.null(skipCov)) { if (is.null(fixed)) { .tmp <- rep(FALSE, length(inits$THTA)) } else { if (length(fixed) < length(inits$THTA)) { .tmp <- c(fixed, rep(FALSE, length(inits$THTA) - length(fixed))) } else { .tmp <- fixed[1:length(inits$THTA)] } } if (exists("uif", envir = .ret)) { .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)] .uifErr <- sapply(.uifErr, function(x) { if (is.na(x)) { return(FALSE) } return(!any(x == c("pow2", "tbs", "tbsYj"))) }) .tmp <- (.tmp | .uifErr) } .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars))) .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref } if (is.null(.extraPars)) { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA))) } else { .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)), sprintf("ERR[%s]", seq_along(.extraPars))) } if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) == length(thetaNames)) { .nms <- thetaNames } .ret$thetaNames <- .nms .thetaReset$thetaNames <- .nms if (length(lower) == 1) { lower <- rep(lower, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { print(inits$THTA) print(lower) stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (length(upper) == 1) { upper <- rep(upper, length(inits$THTA)) } else if (length(lower) != length(inits$THTA)) { stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.") } if (!is.null(.extraPars)) { .ret$model$extra.pars <- eval(call(control$diagXform, .ret$model$extra.pars)) if (length(.ret$model$extra.pars) > 0) { inits$THTA <- c(inits$THTA, .ret$model$extra.pars) .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars)) .upperErr <- rep(Inf, length(.ret$model$extra.pars)) lower <- c(lower, .lowerErr) upper <- c(upper, .upperErr) } } if (is.null(data$ID)) stop("\"ID\" not found in data") if (is.null(data$DV)) stop("\"DV\" not found in data") if (is.null(data$EVID)) data$EVID <- 0 if (is.null(data$AMT)) data$AMT <- 0 for (.v in c("TIME", "AMT", "DV", .covNames)) { data[[.v]] <- as.double(data[[.v]]) } .ret$dataSav <- data .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME", "AMT", "EVID", .covNames)] .w <- which(tolower(names(data)) == "limit") .limitName <- NULL if (length(.w) == 1L) { .limitName <- names(data)[.w] } .censName <- NULL .w <- which(tolower(names(data)) == "cens") if (length(.w) == 1L) { .censName <- names(data[.w]) } data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME", "DV", "EVID", .covNames, .limitName, .censName)] .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep))) names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w])) if (.mixed) { .lh <- .parseOM(inits$OMGA) .nlh <- sapply(.lh, length) .osplt <- rep(1:length(.lh), .nlh) .lini <- list(inits$THTA, unlist(.lh)) .nlini <- sapply(.lini, length) .nsplt <- rep(1:length(.lini), .nlini) .om0 <- .genOM(.lh) if (length(etaNames) == dim(.om0)[1]) { .ret$etaNames <- .ret$etaNames } else { .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1])) } .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform) .ret$xType <- .ret$rxInv$xType .om0a <- .om0 .om0a <- .om0a/control$diagOmegaBoundLower .om0b <- .om0 .om0b <- .om0b * control$diagOmegaBoundUpper .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform) .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform) .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta, b = .om0b$theta, diag = .om0a$theta.diag) .omdf$lower <- with(.omdf, ifelse(a > b, b, a)) .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower)) .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower)) .omdf$upper <- with(.omdf, ifelse(a < b, b, a)) .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper)) .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper)) .ret$control$nomega <- length(.omdf$lower) .ret$control$neta <- sum(.omdf$diag) .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) lower <- c(lower, .omdf$lower) upper <- c(upper, .omdf$upper) } else { .ret$control$nomega <- 0 .ret$control$neta <- 0 .ret$xType <- -1 .ret$control$ntheta <- length(lower) .ret$control$nfixed <- sum(fixed) } .ret$lower <- lower .ret$upper <- upper .ret$thetaIni <- inits$THTA .scaleC <- double(length(lower)) if (is.null(control$scaleC)) { .scaleC <- rep(NA_real_, length(lower)) } else { .scaleC <- as.double(control$scaleC) if (length(lower) > length(.scaleC)) { .scaleC <- c(.scaleC, rep(NA_real_, length(lower) - length(.scaleC))) } else if (length(lower) < length(.scaleC)) { .scaleC <- .scaleC[seq(1, length(lower))] warning("scaleC control option has more options than estimated population parameters, please check.") } } .ret$scaleC <- .scaleC if (exists("uif", envir = .ret)) { .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err), c("est", "err", "ntheta")] for (.i in seq_along(.ini$err)) { if (is.na(.ret$scaleC[.ini$ntheta[.i]])) { if (any(.ini$err[.i] == c("boxCox", "yeoJohnson", "pow2", "tbs", "tbsYj"))) { .ret$scaleC[.ini$ntheta[.i]] <- 1 } else if (any(.ini$err[.i] == c("prop", "add", "norm", "dnorm", "logn", "dlogn", "lnorm", "dlnorm"))) { .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i]) } } } for (.i in .ini$model$extraProps$powTheta) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- 1 } .ini <- as.data.frame(.ret$uif$ini) for (.i in .ini$model$extraProps$factorial) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] + 1)) } for (.i in .ini$model$extraProps$gamma) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i])) } for (.i in .ini$model$extraProps$log) { if (is.na(.ret$scaleC[.i])) .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i]) } for (.i in .ret$logitThetas) { .b <- .ret$logitThetasLow[.i] .c <- .ret$logitThetasHi[.i] .a <- .ini$est[.i] if (is.na(.ret$scaleC[.i])) { .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 + exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a)))) } } } names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni)) if (is.null(etaMat) & !is.null(control$etaMat)) { .ret$etaMat <- control$etaMat } else { .ret$etaMat <- etaMat } .ret$setupTime <- (proc.time() - .pt)["elapsed"] if (exists("uif", envir = .ret)) { .tmp <- .ret$uif$logThetasList .ret$logThetas <- .tmp[[1]] .ret$logThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasList .ret$logitThetas <- .tmp[[1]] .ret$logitThetasF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListLow .ret$logitThetasLow <- .tmp[[1]] .ret$logitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$logitThetasListHi .ret$logitThetasHi <- .tmp[[1]] .ret$logitThetasHiF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasList .ret$probitThetas <- .tmp[[1]] .ret$probitThetasF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListLow .ret$probitThetasLow <- .tmp[[1]] .ret$probitThetasLowF <- .tmp[[2]] .tmp <- .ret$uif$probitThetasListHi .ret$probitThetasHi <- .tmp[[1]] .ret$probitThetasHiF <- .tmp[[2]] } else { .ret$logThetasF <- integer(0) .ret$logitThetasF <- integer(0) .ret$logitThetasHiF <- numeric(0) .ret$logitThetasLowF <- numeric(0) .ret$logitThetas <- integer(0) .ret$logitThetasHi <- numeric(0) .ret$logitThetasLow <- numeric(0) .ret$probitThetasF <- integer(0) .ret$probitThetasHiF <- numeric(0) .ret$probitThetasLowF <- numeric(0) .ret$probitThetas <- integer(0) .ret$probitThetasHi <- numeric(0) .ret$probitThetasLow <- numeric(0) } if (exists("noLik", envir = .ret)) { if (!.ret$noLik) { .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)), sprintf("ETA[%d]", seq(1, dim(.om0)[1]))) .ret$.thetan <- length(.ret$thetaIni) .ret$nobs <- sum(data$EVID == 0) } } .ret$control$printTop <- TRUE .ret$control$nF <- 0 .est0 <- .ret$thetaIni if (!is.null(.ret$model$pred.nolhs)) { .ret$control$predNeq <- length(.ret$model$pred.nolhs$state) } else { .ret$control$predNeq <- 0L } .fitFun <- function(.ret) { this.env <- environment() assign("err", "theta reset", this.env) while (this.env$err == "theta reset") { assign("err", "", this.env) .ret0 <- tryCatch({ foceiFitCpp_(.ret) }, error = function(e) { if (regexpr("theta reset", e$message) != -1) { assign("zeroOuter", FALSE, this.env) assign("zeroGrad", FALSE, this.env) if (regexpr("theta reset0", e$message) != -1) { assign("zeroGrad", TRUE, this.env) } else if (regexpr("theta resetZ", e$message) != -1) { assign("zeroOuter", TRUE, this.env) } assign("err", "theta reset", this.env) } else { assign("err", e$message, this.env) } }) if (this.env$err == "theta reset") { .nm <- names(.ret$thetaIni) .ret$thetaIni <- setNames(.thetaReset$thetaIni + 0, .nm) .ret$rxInv$theta <- .thetaReset$omegaTheta .ret$control$printTop <- FALSE .ret$etaMat <- .thetaReset$etaMat .ret$control$etaMat <- .thetaReset$etaMat .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations .ret$control$nF <- .thetaReset$nF .ret$control$gillRetC <- .thetaReset$gillRetC .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillRet <- .thetaReset$gillRet .ret$control$gillDf <- .thetaReset$gillDf .ret$control$gillDf2 <- .thetaReset$gillDf2 .ret$control$gillErr <- .thetaReset$gillErr .ret$control$rEps <- .thetaReset$rEps .ret$control$aEps <- .thetaReset$aEps .ret$control$rEpsC <- .thetaReset$rEpsC .ret$control$aEpsC <- .thetaReset$aEpsC .ret$control$c1 <- .thetaReset$c1 .ret$control$c2 <- .thetaReset$c2 if (this.env$zeroOuter) { message("Posthoc reset") .ret$control$maxOuterIterations <- 0L } else if (this.env$zeroGrad) { message("Theta reset (zero gradient values); Switch to bobyqa") RxODE::rxReq("minqa") .ret$control$outerOptFun <- .bobyqa .ret$control$outerOpt <- -1L } else { message("Theta reset (ETA drift)") } } } if (this.env$err != "") { stop(this.env$err) } else { return(.ret0) } } .ret0 <- try(.fitFun(.ret)) .n <- 1 while (inherits(.ret0, "try-error") && control$maxOuterIterations != 0 && .n <= control$nRetries) { message(sprintf("Restart %s", .n)) .ret$control$nF <- 0 .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) - 0.1 * .n .estNew <- sapply(seq_along(.est0), function(.i) { if (.ret$thetaFixed[.i]) { return(.est0[.i]) } else if (.estNew[.i] < lower[.i]) { return(lower + (.Machine$double.eps)^(1/7)) } else if (.estNew[.i] > upper[.i]) { return(upper - (.Machine$double.eps)^(1/7)) } else { return(.estNew[.i]) } }) .ret$thetaIni <- .estNew .ret0 <- try(.fitFun(.ret)) .n <- .n + 1 } if (inherits(.ret0, "try-error")) stop("Could not fit data.") .ret <- .ret0 if (exists("parHistData", .ret)) { .tmp <- .ret$parHistData .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) != "type"] .iter <- .tmp$iter .tmp <- .tmp[, names(.tmp) != "iter"] .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter) names(.ret$parHistStacked) <- c("val", "par", "iter") .ret$parHist <- data.frame(iter = .iter, .tmp) } if (.mixed) { .etas <- .ret$ranef .thetas <- .ret$fixef .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas) .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega, .pars$eta.lst, length(.etas$ID)) .updateParFixed(.ret) } else { .updateParFixed(.ret) } if (!exists("table", .ret)) { .ret$table <- tableControl() } if (control$calcTables) { .ret <- addTable(.ret, updateObject = "no", keep = keep, drop = drop, table = .ret$table) } .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod, pred = function() { return(nlmixr_pred) }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper, fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names, control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.5 0.646 18.15
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
+#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
+#> F: Forward difference gradient approximation
+#> C: Central difference gradient approximation
+#> M: Mixed forward and central difference gradient approximation
+#> Unscaled parameters for Omegas=chol(solve(omega));
+#> Diagonals are transformed, as specified by foceiControl(diagXform=)
+#> |-----+---------------+-----------+-----------+-----------+-----------|
+#> | #| Objective Fun | parent_0 | log_k_A1 |f_parent_qlogis | log_k1 |
+#> |.....................| log_k2 | g_qlogis |sigma_low_parent |rsd_high_parent |
+#> |.....................|sigma_low_A1 |rsd_high_A1 | o1 | o2 |
+#> |.....................| o3 | o4 | o5 | o6 |
+#> | 1| 495.80376 | 1.000 | -1.000 | -0.9110 | -0.9380 |
+#> |.....................| -0.9885 | -0.8832 | -0.8755 | -0.8915 |
+#> |.....................| -0.8755 | -0.8915 | -0.8776 | -0.8741 |
+#> |.....................| -0.8681 | -0.8727 | -0.8749 | -0.8675 |
+#> | U| 495.80376 | 91.48 | -5.189 | -0.8875 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8280 | 0.05769 |
+#> |.....................| 0.8280 | 0.05769 | 0.7296 | 0.8969 |
+#> |.....................| 1.185 | 0.9628 | 0.8582 | 1.216 |
+#> | X| 495.80376 | 91.48 | 0.005580 | 0.2916 | 0.1119 |
+#> |.....................| 0.009750 | 0.6128 | 0.8280 | 0.05769 |
+#> |.....................| 0.8280 | 0.05769 | 0.7296 | 0.8969 |
+#> |.....................| 1.185 | 0.9628 | 0.8582 | 1.216 |
+#> | G| Gill Diff. | 40.10 | 2.344 | -0.09792 | 0.01304 |
+#> |.....................| -0.4854 | 0.6353 | -23.92 | -17.76 |
+#> |.....................| -5.723 | -2.232 | 1.261 | 9.993 |
+#> |.....................| -12.68 | -0.7774 | 8.106 | -12.55 |
+#> | 2| 3318.3701 | 0.2710 | -1.043 | -0.9092 | -0.9382 |
+#> |.....................| -0.9796 | -0.8947 | -0.4406 | -0.5686 |
+#> |.....................| -0.7715 | -0.8509 | -0.9005 | -1.056 |
+#> |.....................| -0.6376 | -0.8586 | -1.022 | -0.6393 |
+#> | U| 3318.3701 | 24.79 | -5.231 | -0.8859 | -2.190 |
+#> |.....................| -4.622 | 0.4536 | 1.008 | 0.06701 |
+#> |.....................| 0.8711 | 0.05887 | 0.7129 | 0.7340 |
+#> |.....................| 1.458 | 0.9764 | 0.7317 | 1.493 |
+#> | X| 3318.3701 | 24.79 | 0.005347 | 0.2920 | 0.1119 |
+#> |.....................| 0.009837 | 0.6115 | 1.008 | 0.06701 |
+#> |.....................| 0.8711 | 0.05887 | 0.7129 | 0.7340 |
+#> |.....................| 1.458 | 0.9764 | 0.7317 | 1.493 |
+#> | 3| 512.37365 | 0.9271 | -1.004 | -0.9108 | -0.9380 |
+#> |.....................| -0.9876 | -0.8843 | -0.8320 | -0.8592 |
+#> |.....................| -0.8651 | -0.8874 | -0.8799 | -0.8923 |
+#> |.....................| -0.8451 | -0.8713 | -0.8896 | -0.8447 |
+#> | U| 512.37365 | 84.82 | -5.193 | -0.8873 | -2.190 |
+#> |.....................| -4.630 | 0.4584 | 0.8460 | 0.05863 |
+#> |.....................| 0.8323 | 0.05781 | 0.7279 | 0.8806 |
+#> |.....................| 1.212 | 0.9641 | 0.8455 | 1.244 |
+#> | X| 512.37365 | 84.82 | 0.005556 | 0.2917 | 0.1119 |
+#> |.....................| 0.009759 | 0.6126 | 0.8460 | 0.05863 |
+#> |.....................| 0.8323 | 0.05781 | 0.7279 | 0.8806 |
+#> |.....................| 1.212 | 0.9641 | 0.8455 | 1.244 |
+#> | 4| 495.44913 | 0.9909 | -1.001 | -0.9110 | -0.9380 |
+#> |.....................| -0.9883 | -0.8833 | -0.8701 | -0.8874 |
+#> |.....................| -0.8742 | -0.8910 | -0.8778 | -0.8764 |
+#> |.....................| -0.8653 | -0.8726 | -0.8767 | -0.8647 |
+#> | U| 495.44913 | 90.65 | -5.189 | -0.8874 | -2.190 |
+#> |.....................| -4.630 | 0.4589 | 0.8303 | 0.05781 |
+#> |.....................| 0.8286 | 0.05771 | 0.7294 | 0.8949 |
+#> |.....................| 1.189 | 0.9629 | 0.8566 | 1.219 |
+#> | X| 495.44913 | 90.65 | 0.005577 | 0.2916 | 0.1119 |
+#> |.....................| 0.009751 | 0.6127 | 0.8303 | 0.05781 |
+#> |.....................| 0.8286 | 0.05771 | 0.7294 | 0.8949 |
+#> |.....................| 1.189 | 0.9629 | 0.8566 | 1.219 |
+#> | F| Forward Diff. | -32.24 | 2.221 | -0.3999 | 0.1183 |
+#> |.....................| -0.4367 | 0.6696 | -24.35 | -18.50 |
+#> |.....................| -5.733 | -2.007 | 1.154 | 9.098 |
+#> |.....................| -12.48 | -0.2426 | 8.051 | -12.28 |
+#> | 5| 495.09570 | 0.9990 | -1.001 | -0.9109 | -0.9380 |
+#> |.....................| -0.9882 | -0.8835 | -0.8640 | -0.8828 |
+#> |.....................| -0.8728 | -0.8905 | -0.8781 | -0.8786 |
+#> |.....................| -0.8621 | -0.8725 | -0.8788 | -0.8616 |
+#> | U| 495.0957 | 91.39 | -5.190 | -0.8874 | -2.190 |
+#> |.....................| -4.630 | 0.4588 | 0.8328 | 0.05794 |
+#> |.....................| 0.8291 | 0.05772 | 0.7292 | 0.8928 |
+#> |.....................| 1.192 | 0.9630 | 0.8549 | 1.223 |
+#> | X| 495.0957 | 91.39 | 0.005574 | 0.2917 | 0.1119 |
+#> |.....................| 0.009752 | 0.6127 | 0.8328 | 0.05794 |
+#> |.....................| 0.8291 | 0.05772 | 0.7292 | 0.8928 |
+#> |.....................| 1.192 | 0.9630 | 0.8549 | 1.223 |
+#> | F| Forward Diff. | 32.16 | 2.311 | -0.1335 | 0.03619 |
+#> |.....................| -0.4432 | 0.6445 | -23.23 | -17.46 |
+#> |.....................| -5.567 | -2.162 | 1.281 | 9.656 |
+#> |.....................| -12.09 | -0.7018 | 7.779 | -12.29 |
+#> | 6| 494.75975 | 0.9908 | -1.002 | -0.9109 | -0.9380 |
+#> |.....................| -0.9881 | -0.8836 | -0.8581 | -0.8783 |
+#> |.....................| -0.8714 | -0.8899 | -0.8785 | -0.8811 |
+#> |.....................| -0.8590 | -0.8723 | -0.8807 | -0.8584 |
+#> | U| 494.75975 | 90.64 | -5.190 | -0.8873 | -2.190 |
+#> |.....................| -4.630 | 0.4587 | 0.8352 | 0.05807 |
+#> |.....................| 0.8297 | 0.05774 | 0.7290 | 0.8906 |
+#> |.....................| 1.196 | 0.9632 | 0.8532 | 1.227 |
+#> | X| 494.75975 | 90.64 | 0.005570 | 0.2917 | 0.1119 |
+#> |.....................| 0.009754 | 0.6127 | 0.8352 | 0.05807 |
+#> |.....................| 0.8297 | 0.05774 | 0.7290 | 0.8906 |
+#> |.....................| 1.196 | 0.9632 | 0.8532 | 1.227 |
+#> | F| Forward Diff. | -33.18 | 2.192 | -0.4095 | 0.1210 |
+#> |.....................| -0.4089 | 0.6743 | -23.19 | -17.83 |
+#> |.....................| -5.624 | -1.860 | 1.146 | 8.868 |
+#> |.....................| -11.42 | -0.05808 | 7.519 | -12.11 |
+#> | 7| 494.42957 | 0.9992 | -1.002 | -0.9108 | -0.9380 |
+#> |.....................| -0.9880 | -0.8838 | -0.8522 | -0.8738 |
+#> |.....................| -0.8699 | -0.8894 | -0.8788 | -0.8834 |
+#> |.....................| -0.8561 | -0.8723 | -0.8827 | -0.8554 |
+#> | U| 494.42957 | 91.41 | -5.191 | -0.8872 | -2.190 |
+#> |.....................| -4.630 | 0.4586 | 0.8377 | 0.05820 |
+#> |.....................| 0.8303 | 0.05775 | 0.7287 | 0.8886 |
+#> |.....................| 1.199 | 0.9632 | 0.8515 | 1.231 |
+#> | X| 494.42957 | 91.41 | 0.005567 | 0.2917 | 0.1119 |
+#> |.....................| 0.009755 | 0.6127 | 0.8377 | 0.05820 |
+#> |.....................| 0.8303 | 0.05775 | 0.7287 | 0.8886 |
+#> |.....................| 1.199 | 0.9632 | 0.8515 | 1.231 |
+#> | F| Forward Diff. | 33.60 | 2.291 | -0.1177 | 0.03548 |
+#> |.....................| -0.4327 | 0.6500 | -23.13 | -16.67 |
+#> |.....................| -5.444 | -2.054 | 1.165 | 9.367 |
+#> |.....................| -12.23 | 0.1305 | 7.522 | -12.12 |
+#> | 8| 494.10805 | 0.9907 | -1.003 | -0.9107 | -0.9380 |
+#> |.....................| -0.9879 | -0.8840 | -0.8463 | -0.8696 |
+#> |.....................| -0.8686 | -0.8889 | -0.8791 | -0.8857 |
+#> |.....................| -0.8530 | -0.8723 | -0.8846 | -0.8523 |
+#> | U| 494.10805 | 90.63 | -5.191 | -0.8872 | -2.190 |
+#> |.....................| -4.630 | 0.4586 | 0.8401 | 0.05833 |
+#> |.....................| 0.8309 | 0.05777 | 0.7285 | 0.8865 |
+#> |.....................| 1.203 | 0.9632 | 0.8499 | 1.234 |
+#> | X| 494.10805 | 90.63 | 0.005564 | 0.2917 | 0.1119 |
+#> |.....................| 0.009756 | 0.6127 | 0.8401 | 0.05833 |
+#> |.....................| 0.8309 | 0.05777 | 0.7285 | 0.8865 |
+#> |.....................| 1.203 | 0.9632 | 0.8499 | 1.234 |
+#> | F| Forward Diff. | -33.55 | 2.169 | -0.4095 | 0.1317 |
+#> |.....................| -0.3875 | 0.6809 | -22.57 | -17.16 |
+#> |.....................| -5.560 | -1.906 | 1.113 | 8.554 |
+#> |.....................| -12.00 | -0.1191 | 7.606 | -11.94 |
+#> | 9| 493.79074 | 0.9992 | -1.003 | -0.9106 | -0.9381 |
+#> |.....................| -0.9878 | -0.8841 | -0.8406 | -0.8652 |
+#> |.....................| -0.8671 | -0.8884 | -0.8793 | -0.8879 |
+#> |.....................| -0.8500 | -0.8723 | -0.8865 | -0.8493 |
+#> | U| 493.79074 | 91.41 | -5.192 | -0.8871 | -2.190 |
+#> |.....................| -4.630 | 0.4585 | 0.8425 | 0.05845 |
+#> |.....................| 0.8315 | 0.05778 | 0.7283 | 0.8845 |
+#> |.....................| 1.207 | 0.9632 | 0.8482 | 1.238 |
+#> | X| 493.79074 | 91.41 | 0.005561 | 0.2917 | 0.1119 |
+#> |.....................| 0.009757 | 0.6127 | 0.8425 | 0.05845 |
+#> |.....................| 0.8315 | 0.05778 | 0.7283 | 0.8845 |
+#> |.....................| 1.207 | 0.9632 | 0.8482 | 1.238 |
+#> | F| Forward Diff. | 33.91 | 2.267 | -0.1078 | 0.03893 |
+#> |.....................| -0.4090 | 0.6560 | -22.34 | -15.94 |
+#> |.....................| -5.274 | -2.001 | 1.140 | 9.131 |
+#> |.....................| -12.00 | -0.1724 | 7.294 | -11.95 |
+#> | 10| 493.48645 | 0.9905 | -1.004 | -0.9106 | -0.9381 |
+#> |.....................| -0.9877 | -0.8843 | -0.8348 | -0.8611 |
+#> |.....................| -0.8658 | -0.8879 | -0.8796 | -0.8903 |
+#> |.....................| -0.8469 | -0.8723 | -0.8884 | -0.8462 |
+#> | U| 493.48645 | 90.62 | -5.193 | -0.8871 | -2.190 |
+#> |.....................| -4.630 | 0.4584 | 0.8449 | 0.05857 |
+#> |.....................| 0.8320 | 0.05780 | 0.7281 | 0.8824 |
+#> |.....................| 1.210 | 0.9632 | 0.8466 | 1.242 |
+#> | X| 493.48645 | 90.62 | 0.005558 | 0.2917 | 0.1119 |
+#> |.....................| 0.009758 | 0.6126 | 0.8449 | 0.05857 |
+#> |.....................| 0.8320 | 0.05780 | 0.7281 | 0.8824 |
+#> |.....................| 1.210 | 0.9632 | 0.8466 | 1.242 |
+#> | F| Forward Diff. | -34.40 | 2.145 | -0.4154 | 0.1312 |
+#> |.....................| -0.3648 | 0.6865 | -22.08 | -16.36 |
+#> |.....................| -5.345 | -1.756 | 1.231 | 8.303 |
+#> |.....................| -11.76 | -0.07864 | 7.355 | -11.77 |
+#> | 11| 493.18511 | 0.9993 | -1.004 | -0.9105 | -0.9381 |
+#> |.....................| -0.9876 | -0.8845 | -0.8292 | -0.8570 |
+#> |.....................| -0.8644 | -0.8875 | -0.8799 | -0.8924 |
+#> |.....................| -0.8439 | -0.8722 | -0.8902 | -0.8432 |
+#> | U| 493.18511 | 91.42 | -5.193 | -0.8870 | -2.190 |
+#> |.....................| -4.630 | 0.4583 | 0.8472 | 0.05869 |
+#> |.....................| 0.8326 | 0.05781 | 0.7279 | 0.8805 |
+#> |.....................| 1.214 | 0.9633 | 0.8450 | 1.246 |
+#> | X| 493.18511 | 91.42 | 0.005555 | 0.2917 | 0.1119 |
+#> |.....................| 0.009759 | 0.6126 | 0.8472 | 0.05869 |
+#> |.....................| 0.8326 | 0.05781 | 0.7279 | 0.8805 |
+#> |.....................| 1.214 | 0.9633 | 0.8450 | 1.246 |
+#> | F| Forward Diff. | 34.43 | 2.240 | -0.1040 | 0.04282 |
+#> |.....................| -0.3912 | 0.6547 | -21.84 | -15.27 |
+#> |.....................| -5.158 | -1.914 | 1.030 | 8.876 |
+#> |.....................| -11.77 | -0.1415 | 7.047 | -11.78 |
+#> | 12| 492.89407 | 0.9905 | -1.005 | -0.9105 | -0.9381 |
+#> |.....................| -0.9875 | -0.8847 | -0.8236 | -0.8530 |
+#> |.....................| -0.8631 | -0.8870 | -0.8802 | -0.8947 |
+#> |.....................| -0.8409 | -0.8722 | -0.8921 | -0.8401 |
+#> | U| 492.89407 | 90.61 | -5.194 | -0.8870 | -2.190 |
+#> |.....................| -4.630 | 0.4582 | 0.8495 | 0.05880 |
+#> |.....................| 0.8332 | 0.05782 | 0.7277 | 0.8785 |
+#> |.....................| 1.217 | 0.9633 | 0.8434 | 1.249 |
+#> | X| 492.89407 | 90.61 | 0.005551 | 0.2917 | 0.1119 |
+#> |.....................| 0.009760 | 0.6126 | 0.8495 | 0.05880 |
+#> |.....................| 0.8332 | 0.05782 | 0.7277 | 0.8785 |
+#> |.....................| 1.217 | 0.9633 | 0.8434 | 1.249 |
+#> | F| Forward Diff. | -34.81 | 2.117 | -0.4182 | 0.1353 |
+#> |.....................| -0.3428 | 0.6933 | -21.54 | -15.66 |
+#> |.....................| -5.188 | -1.708 | 1.147 | 8.020 |
+#> |.....................| -11.52 | -0.06705 | 7.151 | -11.60 |
+#> | 13| 492.59250 | 0.9992 | -1.006 | -0.9104 | -0.9382 |
+#> |.....................| -0.9874 | -0.8848 | -0.8179 | -0.8489 |
+#> |.....................| -0.8617 | -0.8865 | -0.8805 | -0.8968 |
+#> |.....................| -0.8378 | -0.8722 | -0.8940 | -0.8371 |
+#> | U| 492.5925 | 91.41 | -5.194 | -0.8869 | -2.190 |
+#> |.....................| -4.629 | 0.4582 | 0.8519 | 0.05892 |
+#> |.....................| 0.8337 | 0.05784 | 0.7275 | 0.8766 |
+#> |.....................| 1.221 | 0.9633 | 0.8418 | 1.253 |
+#> | X| 492.5925 | 91.41 | 0.005548 | 0.2918 | 0.1119 |
+#> |.....................| 0.009760 | 0.6126 | 0.8519 | 0.05892 |
+#> |.....................| 0.8337 | 0.05784 | 0.7275 | 0.8766 |
+#> |.....................| 1.221 | 0.9633 | 0.8418 | 1.253 |
+#> | F| Forward Diff. | 33.40 | 2.217 | -0.09736 | 0.04377 |
+#> |.....................| -0.3664 | 0.6618 | -21.29 | -14.62 |
+#> |.....................| -5.018 | -1.838 | 0.9818 | 8.628 |
+#> |.....................| -11.52 | -0.1307 | 6.857 | -11.62 |
+#> | 14| 492.30478 | 0.9905 | -1.006 | -0.9103 | -0.9382 |
+#> |.....................| -0.9873 | -0.8850 | -0.8121 | -0.8449 |
+#> |.....................| -0.8604 | -0.8860 | -0.8808 | -0.8991 |
+#> |.....................| -0.8347 | -0.8722 | -0.8958 | -0.8339 |
+#> | U| 492.30478 | 90.62 | -5.195 | -0.8868 | -2.190 |
+#> |.....................| -4.629 | 0.4581 | 0.8543 | 0.05904 |
+#> |.....................| 0.8343 | 0.05785 | 0.7273 | 0.8745 |
+#> |.....................| 1.225 | 0.9633 | 0.8402 | 1.257 |
+#> | X| 492.30478 | 90.62 | 0.005545 | 0.2918 | 0.1119 |
+#> |.....................| 0.009761 | 0.6126 | 0.8543 | 0.05904 |
+#> |.....................| 0.8343 | 0.05785 | 0.7273 | 0.8745 |
+#> |.....................| 1.225 | 0.9633 | 0.8402 | 1.257 |
+#> | F| Forward Diff. | -34.08 | 2.096 | -0.4157 | 0.1370 |
+#> |.....................| -0.3212 | 0.6979 | -20.95 | -14.99 |
+#> |.....................| -5.046 | -1.607 | 1.055 | 8.026 |
+#> |.....................| -11.31 | 0.3535 | 6.819 | -11.49 |
+#> | 15| 492.00325 | 0.9991 | -1.007 | -0.9102 | -0.9382 |
+#> |.....................| -0.9872 | -0.8852 | -0.8063 | -0.8408 |
+#> |.....................| -0.8590 | -0.8856 | -0.8811 | -0.9014 |
+#> |.....................| -0.8316 | -0.8723 | -0.8977 | -0.8307 |
+#> | U| 492.00325 | 91.40 | -5.195 | -0.8867 | -2.190 |
+#> |.....................| -4.629 | 0.4580 | 0.8567 | 0.05916 |
+#> |.....................| 0.8349 | 0.05786 | 0.7271 | 0.8725 |
+#> |.....................| 1.229 | 0.9632 | 0.8386 | 1.261 |
+#> | X| 492.00325 | 91.40 | 0.005542 | 0.2918 | 0.1119 |
+#> |.....................| 0.009762 | 0.6125 | 0.8567 | 0.05916 |
+#> |.....................| 0.8349 | 0.05786 | 0.7271 | 0.8725 |
+#> |.....................| 1.229 | 0.9632 | 0.8386 | 1.261 |
+#> | F| Forward Diff. | 32.19 | 2.189 | -0.09620 | 0.04245 |
+#> |.....................| -0.3450 | 0.6659 | -21.28 | -14.00 |
+#> |.....................| -4.881 | -1.759 | 1.243 | 8.359 |
+#> |.....................| -10.62 | -0.07477 | 6.614 | -11.44 |
+#> | 16| 491.72015 | 0.9906 | -1.007 | -0.9102 | -0.9382 |
+#> |.....................| -0.9871 | -0.8854 | -0.8003 | -0.8368 |
+#> |.....................| -0.8576 | -0.8851 | -0.8814 | -0.9037 |
+#> |.....................| -0.8285 | -0.8722 | -0.8996 | -0.8275 |
+#> | U| 491.72015 | 90.62 | -5.196 | -0.8867 | -2.190 |
+#> |.....................| -4.629 | 0.4579 | 0.8592 | 0.05927 |
+#> |.....................| 0.8354 | 0.05788 | 0.7268 | 0.8703 |
+#> |.....................| 1.232 | 0.9633 | 0.8370 | 1.265 |
+#> | X| 491.72015 | 90.62 | 0.005538 | 0.2918 | 0.1119 |
+#> |.....................| 0.009763 | 0.6125 | 0.8592 | 0.05927 |
+#> |.....................| 0.8354 | 0.05788 | 0.7268 | 0.8703 |
+#> |.....................| 1.232 | 0.9633 | 0.8370 | 1.265 |
+#> | F| Forward Diff. | -33.41 | 2.074 | -0.4123 | 0.1389 |
+#> |.....................| -0.2981 | 0.7039 | -20.39 | -14.31 |
+#> |.....................| -4.887 | -1.550 | 0.9656 | 7.818 |
+#> |.....................| -11.05 | -0.4282 | 6.582 | -11.31 |
+#> | 17| 491.42294 | 0.9990 | -1.008 | -0.9101 | -0.9383 |
+#> |.....................| -0.9870 | -0.8856 | -0.7943 | -0.8327 |
+#> |.....................| -0.8562 | -0.8846 | -0.8817 | -0.9060 |
+#> |.....................| -0.8254 | -0.8721 | -0.9015 | -0.8242 |
+#> | U| 491.42294 | 91.39 | -5.197 | -0.8866 | -2.190 |
+#> |.....................| -4.629 | 0.4578 | 0.8616 | 0.05939 |
+#> |.....................| 0.8360 | 0.05789 | 0.7266 | 0.8683 |
+#> |.....................| 1.236 | 0.9634 | 0.8354 | 1.269 |
+#> | X| 491.42294 | 91.39 | 0.005535 | 0.2918 | 0.1119 |
+#> |.....................| 0.009764 | 0.6125 | 0.8616 | 0.05939 |
+#> |.....................| 0.8360 | 0.05789 | 0.7266 | 0.8683 |
+#> |.....................| 1.236 | 0.9634 | 0.8354 | 1.269 |
+#> | F| Forward Diff. | 31.50 | 2.165 | -0.08876 | 0.04676 |
+#> |.....................| -0.3226 | 0.6753 | -20.70 | -13.34 |
+#> |.....................| -4.747 | -1.707 | 0.9017 | 8.141 |
+#> |.....................| -10.29 | -0.02981 | 6.402 | -11.28 |
+#> | 18| 491.14065 | 0.9907 | -1.009 | -0.9100 | -0.9383 |
+#> |.....................| -0.9870 | -0.8858 | -0.7882 | -0.8287 |
+#> |.....................| -0.8548 | -0.8841 | -0.8820 | -0.9084 |
+#> |.....................| -0.8223 | -0.8721 | -0.9034 | -0.8208 |
+#> | U| 491.14065 | 90.64 | -5.197 | -0.8866 | -2.190 |
+#> |.....................| -4.629 | 0.4577 | 0.8642 | 0.05950 |
+#> |.....................| 0.8366 | 0.05791 | 0.7264 | 0.8661 |
+#> |.....................| 1.240 | 0.9634 | 0.8337 | 1.273 |
+#> | X| 491.14065 | 90.64 | 0.005531 | 0.2918 | 0.1119 |
+#> |.....................| 0.009765 | 0.6125 | 0.8642 | 0.05950 |
+#> |.....................| 0.8366 | 0.05791 | 0.7264 | 0.8661 |
+#> |.....................| 1.240 | 0.9634 | 0.8337 | 1.273 |
+#> | F| Forward Diff. | -32.29 | 2.052 | -0.4043 | 0.1403 |
+#> |.....................| -0.2785 | 0.7107 | -20.12 | -13.83 |
+#> |.....................| -4.879 | -1.515 | 0.4622 | 7.293 |
+#> |.....................| -10.82 | -0.3681 | 6.384 | -11.14 |
+#> | 19| 490.84537 | 0.9989 | -1.009 | -0.9099 | -0.9383 |
+#> |.....................| -0.9869 | -0.8860 | -0.7821 | -0.8246 |
+#> |.....................| -0.8533 | -0.8837 | -0.8821 | -0.9106 |
+#> |.....................| -0.8190 | -0.8720 | -0.9053 | -0.8174 |
+#> | U| 490.84537 | 91.38 | -5.198 | -0.8865 | -2.190 |
+#> |.....................| -4.629 | 0.4576 | 0.8667 | 0.05962 |
+#> |.....................| 0.8372 | 0.05792 | 0.7263 | 0.8641 |
+#> |.....................| 1.243 | 0.9635 | 0.8321 | 1.277 |
+#> | X| 490.84537 | 91.38 | 0.005528 | 0.2918 | 0.1119 |
+#> |.....................| 0.009766 | 0.6124 | 0.8667 | 0.05962 |
+#> |.....................| 0.8372 | 0.05792 | 0.7263 | 0.8641 |
+#> |.....................| 1.243 | 0.9635 | 0.8321 | 1.277 |
+#> | F| Forward Diff. | 30.35 | 2.134 | -0.08371 | 0.04933 |
+#> |.....................| -0.3000 | 0.6785 | -20.24 | -12.73 |
+#> |.....................| -4.623 | -1.604 | 1.054 | 8.092 |
+#> |.....................| -10.77 | -0.4405 | 6.181 | -11.10 |
+#> | 20| 490.56963 | 0.9908 | -1.010 | -0.9099 | -0.9383 |
+#> |.....................| -0.9868 | -0.8862 | -0.7758 | -0.8207 |
+#> |.....................| -0.8519 | -0.8832 | -0.8824 | -0.9131 |
+#> |.....................| -0.8157 | -0.8719 | -0.9072 | -0.8140 |
+#> | U| 490.56963 | 90.64 | -5.199 | -0.8865 | -2.190 |
+#> |.....................| -4.629 | 0.4575 | 0.8693 | 0.05974 |
+#> |.....................| 0.8378 | 0.05793 | 0.7261 | 0.8619 |
+#> |.....................| 1.247 | 0.9636 | 0.8305 | 1.281 |
+#> | X| 490.56963 | 90.64 | 0.005524 | 0.2918 | 0.1119 |
+#> |.....................| 0.009767 | 0.6124 | 0.8693 | 0.05974 |
+#> |.....................| 0.8378 | 0.05793 | 0.7261 | 0.8619 |
+#> |.....................| 1.247 | 0.9636 | 0.8305 | 1.281 |
+#> | F| Forward Diff. | -31.85 | 2.030 | -0.4014 | 0.1424 |
+#> |.....................| -0.2574 | 0.7152 | -19.39 | -13.12 |
+#> |.....................| -4.602 | -1.387 | 0.5883 | 7.042 |
+#> |.....................| -10.56 | -0.3115 | 6.249 | -10.92 |
+#> | 21| 490.28521 | 0.9989 | -1.011 | -0.9098 | -0.9384 |
+#> |.....................| -0.9867 | -0.8865 | -0.7697 | -0.8166 |
+#> |.....................| -0.8504 | -0.8827 | -0.8826 | -0.9153 |
+#> |.....................| -0.8124 | -0.8718 | -0.9092 | -0.8105 |
+#> | U| 490.28521 | 91.39 | -5.199 | -0.8864 | -2.190 |
+#> |.....................| -4.629 | 0.4574 | 0.8718 | 0.05985 |
+#> |.....................| 0.8384 | 0.05795 | 0.7259 | 0.8599 |
+#> |.....................| 1.251 | 0.9637 | 0.8288 | 1.285 |
+#> | X| 490.28521 | 91.39 | 0.005521 | 0.2919 | 0.1119 |
+#> |.....................| 0.009767 | 0.6124 | 0.8718 | 0.05985 |
+#> |.....................| 0.8384 | 0.05795 | 0.7259 | 0.8599 |
+#> |.....................| 1.251 | 0.9637 | 0.8288 | 1.285 |
+#> | F| Forward Diff. | 30.53 | 2.112 | -0.07114 | 0.05276 |
+#> |.....................| -0.2779 | 0.6845 | -19.81 | -12.13 |
+#> |.....................| -4.498 | -1.539 | 0.6449 | 7.769 |
+#> |.....................| -10.55 | -0.3696 | 5.980 | -10.93 |
+#> | 22| 489.99923 | 0.9911 | -1.011 | -0.9097 | -0.9384 |
+#> |.....................| -0.9866 | -0.8867 | -0.7633 | -0.8127 |
+#> |.....................| -0.8489 | -0.8823 | -0.8828 | -0.9178 |
+#> |.....................| -0.8089 | -0.8716 | -0.9111 | -0.8070 |
+#> | U| 489.99923 | 90.67 | -5.200 | -0.8863 | -2.190 |
+#> |.....................| -4.629 | 0.4573 | 0.8745 | 0.05997 |
+#> |.....................| 0.8390 | 0.05796 | 0.7258 | 0.8577 |
+#> |.....................| 1.255 | 0.9638 | 0.8271 | 1.290 |
+#> | X| 489.99923 | 90.67 | 0.005517 | 0.2919 | 0.1119 |
+#> |.....................| 0.009768 | 0.6124 | 0.8745 | 0.05997 |
+#> |.....................| 0.8390 | 0.05796 | 0.7258 | 0.8577 |
+#> |.....................| 1.255 | 0.9638 | 0.8271 | 1.290 |
+#> | F| Forward Diff. | -29.14 | 2.012 | -0.3844 | 0.1417 |
+#> |.....................| -0.2358 | 0.7218 | -18.90 | -12.37 |
+#> |.....................| -4.517 | -1.329 | 0.4904 | 6.799 |
+#> |.....................| -10.31 | -0.2514 | 6.013 | -10.75 |
+#> | 23| 489.73483 | 0.9991 | -1.012 | -0.9096 | -0.9384 |
+#> |.....................| -0.9865 | -0.8869 | -0.7571 | -0.8087 |
+#> |.....................| -0.8475 | -0.8818 | -0.8829 | -0.9201 |
+#> |.....................| -0.8055 | -0.8715 | -0.9131 | -0.8034 |
+#> | U| 489.73483 | 91.40 | -5.201 | -0.8862 | -2.190 |
+#> |.....................| -4.629 | 0.4572 | 0.8771 | 0.06008 |
+#> |.....................| 0.8396 | 0.05797 | 0.7257 | 0.8557 |
+#> |.....................| 1.259 | 0.9639 | 0.8254 | 1.294 |
+#> | X| 489.73483 | 91.40 | 0.005513 | 0.2919 | 0.1119 |
+#> |.....................| 0.009769 | 0.6123 | 0.8771 | 0.06008 |
+#> |.....................| 0.8396 | 0.05797 | 0.7257 | 0.8557 |
+#> |.....................| 1.259 | 0.9639 | 0.8254 | 1.294 |
+#> | F| Forward Diff. | 31.68 | 2.089 | -0.05219 | 0.05312 |
+#> |.....................| -0.2568 | 0.6912 | -19.25 | -11.50 |
+#> |.....................| -4.291 | -1.478 | 0.6044 | 7.316 |
+#> |.....................| -10.30 | -0.3159 | 5.756 | -10.75 |
+#> | 24| 489.43925 | 0.9914 | -1.013 | -0.9096 | -0.9385 |
+#> |.....................| -0.9865 | -0.8872 | -0.7505 | -0.8049 |
+#> |.....................| -0.8460 | -0.8813 | -0.8831 | -0.9225 |
+#> |.....................| -0.8020 | -0.8714 | -0.9150 | -0.7997 |
+#> | U| 489.43925 | 90.70 | -5.201 | -0.8862 | -2.190 |
+#> |.....................| -4.628 | 0.4571 | 0.8798 | 0.06019 |
+#> |.....................| 0.8402 | 0.05799 | 0.7256 | 0.8535 |
+#> |.....................| 1.264 | 0.9640 | 0.8238 | 1.298 |
+#> | X| 489.43925 | 90.70 | 0.005509 | 0.2919 | 0.1119 |
+#> |.....................| 0.009770 | 0.6123 | 0.8798 | 0.06019 |
+#> |.....................| 0.8402 | 0.05799 | 0.7256 | 0.8535 |
+#> |.....................| 1.264 | 0.9640 | 0.8238 | 1.298 |
+#> | F| Forward Diff. | -26.48 | 1.993 | -0.3684 | 0.1403 |
+#> |.....................| -0.2166 | 0.7270 | -18.36 | -11.77 |
+#> |.....................| -4.393 | -1.275 | 0.4390 | 6.578 |
+#> |.....................| -10.04 | -0.2187 | 5.799 | -10.58 |
+#> | 25| 489.19181 | 0.9992 | -1.013 | -0.9095 | -0.9385 |
+#> |.....................| -0.9864 | -0.8874 | -0.7441 | -0.8009 |
+#> |.....................| -0.8445 | -0.8809 | -0.8833 | -0.9248 |
+#> |.....................| -0.7985 | -0.8714 | -0.9170 | -0.7960 |
+#> | U| 489.19181 | 91.41 | -5.202 | -0.8861 | -2.190 |
+#> |.....................| -4.628 | 0.4570 | 0.8824 | 0.06031 |
+#> |.....................| 0.8409 | 0.05800 | 0.7255 | 0.8514 |
+#> |.....................| 1.268 | 0.9641 | 0.8221 | 1.303 |
+#> | X| 489.19181 | 91.41 | 0.005505 | 0.2919 | 0.1119 |
+#> |.....................| 0.009770 | 0.6123 | 0.8824 | 0.06031 |
+#> |.....................| 0.8409 | 0.05800 | 0.7255 | 0.8514 |
+#> |.....................| 1.268 | 0.9641 | 0.8221 | 1.303 |
+#> | F| Forward Diff. | 32.48 | 2.067 | -0.03453 | 0.05414 |
+#> |.....................| -0.2360 | 0.6938 | -18.67 | -10.89 |
+#> |.....................| -4.178 | -1.425 | 0.5548 | 7.078 |
+#> |.....................| -10.01 | -0.2144 | 5.548 | -10.57 |
+#> | 26| 488.89118 | 0.9917 | -1.014 | -0.9094 | -0.9385 |
+#> |.....................| -0.9863 | -0.8877 | -0.7375 | -0.7972 |
+#> |.....................| -0.8430 | -0.8804 | -0.8834 | -0.9272 |
+#> |.....................| -0.7949 | -0.8713 | -0.9189 | -0.7921 |
+#> | U| 488.89118 | 90.73 | -5.203 | -0.8860 | -2.190 |
+#> |.....................| -4.628 | 0.4568 | 0.8852 | 0.06041 |
+#> |.....................| 0.8415 | 0.05801 | 0.7253 | 0.8493 |
+#> |.....................| 1.272 | 0.9642 | 0.8204 | 1.308 |
+#> | X| 488.89118 | 90.73 | 0.005501 | 0.2919 | 0.1119 |
+#> |.....................| 0.009771 | 0.6123 | 0.8852 | 0.06041 |
+#> |.....................| 0.8415 | 0.05801 | 0.7253 | 0.8493 |
+#> |.....................| 1.272 | 0.9642 | 0.8204 | 1.308 |
+#> | F| Forward Diff. | -24.34 | 1.974 | -0.3522 | 0.1400 |
+#> |.....................| -0.1957 | 0.7323 | -17.88 | -11.06 |
+#> |.....................| -4.245 | -1.195 | 0.3418 | 6.336 |
+#> |.....................| -9.795 | -0.1748 | 5.588 | -10.40 |
+#> | 27| 488.65823 | 0.9993 | -1.015 | -0.9093 | -0.9386 |
+#> |.....................| -0.9862 | -0.8880 | -0.7310 | -0.7933 |
+#> |.....................| -0.8415 | -0.8800 | -0.8835 | -0.9295 |
+#> |.....................| -0.7913 | -0.8712 | -0.9210 | -0.7883 |
+#> | U| 488.65823 | 91.42 | -5.204 | -0.8859 | -2.190 |
+#> |.....................| -4.628 | 0.4567 | 0.8878 | 0.06053 |
+#> |.....................| 0.8421 | 0.05803 | 0.7253 | 0.8472 |
+#> |.....................| 1.276 | 0.9642 | 0.8187 | 1.312 |
+#> | X| 488.65823 | 91.42 | 0.005497 | 0.2919 | 0.1119 |
+#> |.....................| 0.009772 | 0.6122 | 0.8878 | 0.06053 |
+#> |.....................| 0.8421 | 0.05803 | 0.7253 | 0.8472 |
+#> |.....................| 1.276 | 0.9642 | 0.8187 | 1.312 |
+#> | F| Forward Diff. | 33.05 | 2.045 | -0.01570 | 0.05526 |
+#> |.....................| -0.2154 | 0.6997 | -18.21 | -10.28 |
+#> |.....................| -4.052 | -1.334 | 0.4619 | 6.811 |
+#> |.....................| -9.752 | -0.1974 | 5.317 | -10.39 |
+#> | 28| 488.35451 | 0.9920 | -1.016 | -0.9093 | -0.9386 |
+#> |.....................| -0.9862 | -0.8883 | -0.7243 | -0.7897 |
+#> |.....................| -0.8399 | -0.8795 | -0.8836 | -0.9319 |
+#> |.....................| -0.7876 | -0.8712 | -0.9229 | -0.7844 |
+#> | U| 488.35451 | 90.75 | -5.204 | -0.8859 | -2.190 |
+#> |.....................| -4.628 | 0.4566 | 0.8906 | 0.06063 |
+#> |.....................| 0.8427 | 0.05804 | 0.7252 | 0.8450 |
+#> |.....................| 1.281 | 0.9643 | 0.8170 | 1.317 |
+#> | X| 488.35451 | 90.75 | 0.005493 | 0.2920 | 0.1119 |
+#> |.....................| 0.009772 | 0.6122 | 0.8906 | 0.06063 |
+#> |.....................| 0.8427 | 0.05804 | 0.7252 | 0.8450 |
+#> |.....................| 1.281 | 0.9643 | 0.8170 | 1.317 |
+#> | F| Forward Diff. | -22.42 | 1.954 | -0.3353 | 0.1391 |
+#> |.....................| -0.1757 | 0.7405 | -17.32 | -10.46 |
+#> |.....................| -4.053 | -1.161 | 0.2825 | 6.114 |
+#> |.....................| -9.506 | -0.1281 | 5.370 | -10.21 |
+#> | 29| 488.13711 | 0.9995 | -1.016 | -0.9092 | -0.9387 |
+#> |.....................| -0.9861 | -0.8886 | -0.7177 | -0.7858 |
+#> |.....................| -0.8384 | -0.8791 | -0.8837 | -0.9342 |
+#> |.....................| -0.7840 | -0.8711 | -0.9249 | -0.7804 |
+#> | U| 488.13711 | 91.44 | -5.205 | -0.8858 | -2.190 |
+#> |.....................| -4.628 | 0.4565 | 0.8934 | 0.06074 |
+#> |.....................| 0.8434 | 0.05805 | 0.7251 | 0.8430 |
+#> |.....................| 1.285 | 0.9643 | 0.8153 | 1.322 |
+#> | X| 488.13711 | 91.44 | 0.005489 | 0.2920 | 0.1119 |
+#> |.....................| 0.009773 | 0.6122 | 0.8934 | 0.06074 |
+#> |.....................| 0.8434 | 0.05805 | 0.7251 | 0.8430 |
+#> |.....................| 1.285 | 0.9643 | 0.8153 | 1.322 |
+#> | F| Forward Diff. | 33.81 | 2.022 | 0.006720 | 0.05587 |
+#> |.....................| -0.1935 | 0.7042 | -17.76 | -9.667 |
+#> |.....................| -3.890 | -1.276 | 0.4404 | 6.589 |
+#> |.....................| -9.459 | -0.1517 | 5.102 | -10.20 |
+#> | 30| 487.82953 | 0.9922 | -1.017 | -0.9091 | -0.9387 |
+#> |.....................| -0.9861 | -0.8889 | -0.7108 | -0.7824 |
+#> |.....................| -0.8369 | -0.8787 | -0.8838 | -0.9367 |
+#> |.....................| -0.7803 | -0.8711 | -0.9268 | -0.7763 |
+#> | U| 487.82953 | 90.77 | -5.206 | -0.8858 | -2.190 |
+#> |.....................| -4.628 | 0.4563 | 0.8962 | 0.06084 |
+#> |.....................| 0.8440 | 0.05806 | 0.7251 | 0.8408 |
+#> |.....................| 1.289 | 0.9644 | 0.8136 | 1.327 |
+#> | X| 487.82953 | 90.77 | 0.005484 | 0.2920 | 0.1119 |
+#> |.....................| 0.009774 | 0.6121 | 0.8962 | 0.06084 |
+#> |.....................| 0.8440 | 0.05806 | 0.7251 | 0.8408 |
+#> |.....................| 1.289 | 0.9644 | 0.8136 | 1.327 |
+#> | F| Forward Diff. | -20.31 | 1.935 | -0.3119 | 0.1382 |
+#> |.....................| -0.1555 | 0.7438 | -16.49 | -9.852 |
+#> |.....................| -3.955 | -1.103 | 0.2044 | 5.876 |
+#> |.....................| -9.237 | -0.1098 | 5.167 | -10.02 |
+#> | 31| 487.63293 | 0.9997 | -1.018 | -0.9090 | -0.9388 |
+#> |.....................| -0.9860 | -0.8892 | -0.7043 | -0.7786 |
+#> |.....................| -0.8354 | -0.8782 | -0.8838 | -0.9390 |
+#> |.....................| -0.7766 | -0.8711 | -0.9289 | -0.7723 |
+#> | U| 487.63293 | 91.46 | -5.207 | -0.8857 | -2.191 |
+#> |.....................| -4.628 | 0.4562 | 0.8989 | 0.06095 |
+#> |.....................| 0.8446 | 0.05808 | 0.7250 | 0.8387 |
+#> |.....................| 1.294 | 0.9644 | 0.8119 | 1.332 |
+#> | X| 487.63293 | 91.46 | 0.005480 | 0.2920 | 0.1119 |
+#> |.....................| 0.009774 | 0.6121 | 0.8989 | 0.06095 |
+#> |.....................| 0.8446 | 0.05808 | 0.7250 | 0.8387 |
+#> |.....................| 1.294 | 0.9644 | 0.8119 | 1.332 |
+#> | F| Forward Diff. | 35.34 | 2.001 | 0.03668 | 0.05608 |
+#> |.....................| -0.1731 | 0.7098 | -16.98 | -9.135 |
+#> |.....................| -3.742 | -1.209 | 0.3780 | 6.351 |
+#> |.....................| -9.183 | 0.6525 | 4.885 | -10.01 |
+#> | 32| 487.31820 | 0.9926 | -1.019 | -0.9090 | -0.9388 |
+#> |.....................| -0.9860 | -0.8895 | -0.6975 | -0.7753 |
+#> |.....................| -0.8338 | -0.8778 | -0.8838 | -0.9414 |
+#> |.....................| -0.7728 | -0.8714 | -0.9308 | -0.7679 |
+#> | U| 487.3182 | 90.81 | -5.208 | -0.8856 | -2.191 |
+#> |.....................| -4.628 | 0.4560 | 0.9017 | 0.06104 |
+#> |.....................| 0.8453 | 0.05809 | 0.7250 | 0.8366 |
+#> |.....................| 1.298 | 0.9641 | 0.8102 | 1.337 |
+#> | X| 487.3182 | 90.81 | 0.005475 | 0.2920 | 0.1119 |
+#> |.....................| 0.009775 | 0.6121 | 0.9017 | 0.06104 |
+#> |.....................| 0.8453 | 0.05809 | 0.7250 | 0.8366 |
+#> |.....................| 1.298 | 0.9641 | 0.8102 | 1.337 |
+#> | F| Forward Diff. | -17.75 | 1.917 | -0.2852 | 0.1361 |
+#> |.....................| -0.1360 | 0.7493 | -16.63 | -9.386 |
+#> |.....................| -3.766 | -1.006 | 0.1674 | 5.665 |
+#> |.....................| -8.945 | 0.7251 | 4.960 | -9.828 |
+#> | 33| 487.13531 | 0.9998 | -1.020 | -0.9089 | -0.9389 |
+#> |.....................| -0.9859 | -0.8898 | -0.6907 | -0.7715 |
+#> |.....................| -0.8323 | -0.8774 | -0.8839 | -0.9437 |
+#> |.....................| -0.7691 | -0.8717 | -0.9328 | -0.7639 |
+#> | U| 487.13531 | 91.47 | -5.208 | -0.8855 | -2.191 |
+#> |.....................| -4.628 | 0.4559 | 0.9045 | 0.06116 |
+#> |.....................| 0.8459 | 0.05810 | 0.7250 | 0.8345 |
+#> |.....................| 1.303 | 0.9638 | 0.8084 | 1.342 |
+#> | X| 487.13531 | 91.47 | 0.005471 | 0.2920 | 0.1118 |
+#> |.....................| 0.009775 | 0.6120 | 0.9045 | 0.06116 |
+#> |.....................| 0.8459 | 0.05810 | 0.7250 | 0.8345 |
+#> |.....................| 1.303 | 0.9638 | 0.8084 | 1.342 |
+#> | F| Forward Diff. | 35.92 | 1.979 | 0.06301 | 0.05698 |
+#> |.....................| -0.1526 | 0.7131 | -16.77 | -8.520 |
+#> |.....................| -3.634 | -1.163 | 0.3177 | 6.099 |
+#> |.....................| -8.917 | 0.6421 | 4.685 | -9.820 |
+#> | 34| 486.82694 | 0.9926 | -1.021 | -0.9088 | -0.9389 |
+#> |.....................| -0.9859 | -0.8902 | -0.6837 | -0.7686 |
+#> |.....................| -0.8308 | -0.8770 | -0.8839 | -0.9460 |
+#> |.....................| -0.7654 | -0.8723 | -0.9347 | -0.7596 |
+#> | U| 486.82694 | 90.81 | -5.209 | -0.8855 | -2.191 |
+#> |.....................| -4.628 | 0.4557 | 0.9074 | 0.06124 |
+#> |.....................| 0.8465 | 0.05811 | 0.7250 | 0.8324 |
+#> |.....................| 1.307 | 0.9632 | 0.8069 | 1.347 |
+#> | X| 486.82694 | 90.81 | 0.005466 | 0.2920 | 0.1118 |
+#> |.....................| 0.009775 | 0.6120 | 0.9074 | 0.06124 |
+#> |.....................| 0.8465 | 0.05811 | 0.7250 | 0.8324 |
+#> |.....................| 1.307 | 0.9632 | 0.8069 | 1.347 |
+#> | F| Forward Diff. | -17.49 | 1.895 | -0.2726 | 0.1382 |
+#> |.....................| -0.1159 | 0.7566 | -16.14 | -8.833 |
+#> |.....................| -3.638 | -0.9303 | 0.1285 | 5.442 |
+#> |.....................| -8.630 | 0.7091 | 4.774 | -9.639 |
+#> | 35| 486.64804 | 0.9998 | -1.021 | -0.9087 | -0.9390 |
+#> |.....................| -0.9858 | -0.8905 | -0.6768 | -0.7649 |
+#> |.....................| -0.8293 | -0.8767 | -0.8839 | -0.9483 |
+#> |.....................| -0.7617 | -0.8727 | -0.9367 | -0.7554 |
+#> | U| 486.64804 | 91.46 | -5.210 | -0.8854 | -2.191 |
+#> |.....................| -4.628 | 0.4556 | 0.9103 | 0.06135 |
+#> |.....................| 0.8472 | 0.05812 | 0.7250 | 0.8304 |
+#> |.....................| 1.311 | 0.9629 | 0.8051 | 1.352 |
+#> | X| 486.64804 | 91.46 | 0.005462 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6120 | 0.9103 | 0.06135 |
+#> |.....................| 0.8472 | 0.05812 | 0.7250 | 0.8304 |
+#> |.....................| 1.311 | 0.9629 | 0.8051 | 1.352 |
+#> | F| Forward Diff. | 35.26 | 1.955 | 0.07649 | 0.05940 |
+#> |.....................| -0.1319 | 0.7217 | -16.38 | -8.030 |
+#> |.....................| -3.491 | -1.078 | 0.2504 | 5.851 |
+#> |.....................| -8.624 | 0.5993 | 4.494 | -9.625 |
+#> | 36| 486.34524 | 0.9928 | -1.022 | -0.9087 | -0.9390 |
+#> |.....................| -0.9858 | -0.8909 | -0.6696 | -0.7621 |
+#> |.....................| -0.8278 | -0.8763 | -0.8838 | -0.9506 |
+#> |.....................| -0.7579 | -0.8733 | -0.9385 | -0.7509 |
+#> | U| 486.34524 | 90.82 | -5.211 | -0.8854 | -2.191 |
+#> |.....................| -4.628 | 0.4554 | 0.9133 | 0.06143 |
+#> |.....................| 0.8478 | 0.05813 | 0.7251 | 0.8283 |
+#> |.....................| 1.316 | 0.9622 | 0.8036 | 1.358 |
+#> | X| 486.34524 | 90.82 | 0.005456 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6119 | 0.9133 | 0.06143 |
+#> |.....................| 0.8478 | 0.05813 | 0.7251 | 0.8283 |
+#> |.....................| 1.316 | 0.9622 | 0.8036 | 1.358 |
+#> | F| Forward Diff. | -16.53 | 1.875 | -0.2661 | 0.1390 |
+#> |.....................| -0.09763 | 0.7654 | -15.70 | -8.237 |
+#> |.....................| -3.491 | -0.9040 | 0.06392 | 5.213 |
+#> |.....................| -8.361 | 0.6621 | 4.584 | -9.445 |
+#> | 37| 486.17476 | 0.9998 | -1.023 | -0.9086 | -0.9391 |
+#> |.....................| -0.9858 | -0.8913 | -0.6626 | -0.7586 |
+#> |.....................| -0.8262 | -0.8759 | -0.8838 | -0.9529 |
+#> |.....................| -0.7542 | -0.8736 | -0.9406 | -0.7467 |
+#> | U| 486.17476 | 91.47 | -5.212 | -0.8853 | -2.191 |
+#> |.....................| -4.628 | 0.4552 | 0.9162 | 0.06153 |
+#> |.....................| 0.8484 | 0.05814 | 0.7250 | 0.8263 |
+#> |.....................| 1.320 | 0.9619 | 0.8018 | 1.363 |
+#> | X| 486.17476 | 91.47 | 0.005452 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6119 | 0.9162 | 0.06153 |
+#> |.....................| 0.8484 | 0.05814 | 0.7250 | 0.8263 |
+#> |.....................| 1.320 | 0.9619 | 0.8018 | 1.363 |
+#> | F| Forward Diff. | 35.23 | 1.932 | 0.08715 | 0.05955 |
+#> |.....................| -0.1122 | 0.7274 | -16.01 | -7.627 |
+#> |.....................| -3.363 | -1.024 | 0.1942 | 5.616 |
+#> |.....................| -8.345 | 0.5641 | 4.322 | -9.424 |
+#> | 38| 485.87468 | 0.9930 | -1.024 | -0.9086 | -0.9392 |
+#> |.....................| -0.9858 | -0.8917 | -0.6553 | -0.7561 |
+#> |.....................| -0.8248 | -0.8756 | -0.8837 | -0.9551 |
+#> |.....................| -0.7504 | -0.8743 | -0.9424 | -0.7420 |
+#> | U| 485.87468 | 90.84 | -5.213 | -0.8853 | -2.191 |
+#> |.....................| -4.628 | 0.4550 | 0.9192 | 0.06160 |
+#> |.....................| 0.8490 | 0.05815 | 0.7252 | 0.8243 |
+#> |.....................| 1.325 | 0.9613 | 0.8003 | 1.369 |
+#> | X| 485.87468 | 90.84 | 0.005446 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6118 | 0.9192 | 0.06160 |
+#> |.....................| 0.8490 | 0.05815 | 0.7252 | 0.8243 |
+#> |.....................| 1.325 | 0.9613 | 0.8003 | 1.369 |
+#> | F| Forward Diff. | -15.16 | 1.855 | -0.2494 | 0.1393 |
+#> |.....................| -0.07811 | 0.7704 | -15.31 | -7.716 |
+#> |.....................| -3.357 | -0.8175 | -0.03012 | 4.971 |
+#> |.....................| -8.100 | 0.5955 | 4.407 | -9.242 |
+#> | 39| 485.71812 | 1.000 | -1.025 | -0.9085 | -0.9392 |
+#> |.....................| -0.9858 | -0.8921 | -0.6482 | -0.7526 |
+#> |.....................| -0.8232 | -0.8752 | -0.8836 | -0.9573 |
+#> |.....................| -0.7467 | -0.8746 | -0.9444 | -0.7377 |
+#> | U| 485.71812 | 91.48 | -5.214 | -0.8852 | -2.191 |
+#> |.....................| -4.628 | 0.4548 | 0.9221 | 0.06170 |
+#> |.....................| 0.8497 | 0.05816 | 0.7252 | 0.8222 |
+#> |.....................| 1.329 | 0.9610 | 0.7985 | 1.374 |
+#> | X| 485.71812 | 91.48 | 0.005442 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6118 | 0.9221 | 0.06170 |
+#> |.....................| 0.8497 | 0.05816 | 0.7252 | 0.8222 |
+#> |.....................| 1.329 | 0.9610 | 0.7985 | 1.374 |
+#> | F| Forward Diff. | 36.02 | 1.911 | 0.1144 | 0.05926 |
+#> |.....................| -0.09370 | 0.7314 | -15.47 | -7.071 |
+#> |.....................| -3.248 | -0.9743 | 0.1265 | 5.377 |
+#> |.....................| -7.775 | 0.5175 | 4.130 | -9.229 |
+#> | 40| 485.42108 | 0.9931 | -1.026 | -0.9085 | -0.9393 |
+#> |.....................| -0.9858 | -0.8926 | -0.6408 | -0.7505 |
+#> |.....................| -0.8218 | -0.8750 | -0.8834 | -0.9594 |
+#> |.....................| -0.7430 | -0.8752 | -0.9461 | -0.7328 |
+#> | U| 485.42108 | 90.85 | -5.215 | -0.8852 | -2.191 |
+#> |.....................| -4.628 | 0.4546 | 0.9252 | 0.06176 |
+#> |.....................| 0.8503 | 0.05817 | 0.7254 | 0.8204 |
+#> |.....................| 1.333 | 0.9604 | 0.7970 | 1.380 |
+#> | X| 485.42108 | 90.85 | 0.005436 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6117 | 0.9252 | 0.06176 |
+#> |.....................| 0.8503 | 0.05817 | 0.7254 | 0.8204 |
+#> |.....................| 1.333 | 0.9604 | 0.7970 | 1.380 |
+#> | F| Forward Diff. | -14.37 | 1.836 | -0.2333 | 0.1389 |
+#> |.....................| -0.05951 | 0.7785 | -14.33 | -7.292 |
+#> |.....................| -3.229 | -0.7699 | -0.05471 | 4.764 |
+#> |.....................| -7.801 | 0.5597 | 4.229 | -9.048 |
+#> | 41| 485.26815 | 0.9999 | -1.027 | -0.9084 | -0.9394 |
+#> |.....................| -0.9858 | -0.8930 | -0.6338 | -0.7470 |
+#> |.....................| -0.8202 | -0.8746 | -0.8833 | -0.9618 |
+#> |.....................| -0.7392 | -0.8755 | -0.9482 | -0.7284 |
+#> | U| 485.26815 | 91.48 | -5.216 | -0.8851 | -2.191 |
+#> |.....................| -4.628 | 0.4544 | 0.9281 | 0.06186 |
+#> |.....................| 0.8509 | 0.05818 | 0.7254 | 0.8183 |
+#> |.....................| 1.338 | 0.9601 | 0.7953 | 1.385 |
+#> | X| 485.26815 | 91.48 | 0.005431 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6117 | 0.9281 | 0.06186 |
+#> |.....................| 0.8509 | 0.05818 | 0.7254 | 0.8183 |
+#> |.....................| 1.338 | 0.9601 | 0.7953 | 1.385 |
+#> | F| Forward Diff. | 35.37 | 1.889 | 0.1323 | 0.06297 |
+#> |.....................| -0.07437 | 0.7390 | -14.80 | -6.641 |
+#> |.....................| -3.116 | -0.8690 | 0.09880 | 5.162 |
+#> |.....................| -7.761 | 0.4865 | 3.967 | -9.019 |
+#> | 42| 484.97448 | 0.9934 | -1.028 | -0.9084 | -0.9395 |
+#> |.....................| -0.9859 | -0.8935 | -0.6264 | -0.7452 |
+#> |.....................| -0.8188 | -0.8744 | -0.8830 | -0.9639 |
+#> |.....................| -0.7352 | -0.8762 | -0.9500 | -0.7231 |
+#> | U| 484.97448 | 90.88 | -5.217 | -0.8851 | -2.191 |
+#> |.....................| -4.628 | 0.4542 | 0.9311 | 0.06191 |
+#> |.....................| 0.8515 | 0.05819 | 0.7257 | 0.8164 |
+#> |.....................| 1.343 | 0.9594 | 0.7937 | 1.392 |
+#> | X| 484.97448 | 90.88 | 0.005424 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6116 | 0.9311 | 0.06191 |
+#> |.....................| 0.8515 | 0.05819 | 0.7257 | 0.8164 |
+#> |.....................| 1.343 | 0.9594 | 0.7937 | 1.392 |
+#> | F| Forward Diff. | -12.51 | 1.817 | -0.2072 | 0.1320 |
+#> |.....................| -0.04147 | 0.7868 | -13.90 | -6.839 |
+#> |.....................| -3.097 | -0.6966 | -0.09701 | 4.567 |
+#> |.....................| -7.500 | 0.5336 | 4.059 | -8.839 |
+#> | 43| 484.82513 | 0.9998 | -1.029 | -0.9083 | -0.9395 |
+#> |.....................| -0.9858 | -0.8939 | -0.6193 | -0.7417 |
+#> |.....................| -0.8172 | -0.8741 | -0.8829 | -0.9662 |
+#> |.....................| -0.7313 | -0.8765 | -0.9521 | -0.7185 |
+#> | U| 484.82513 | 91.47 | -5.218 | -0.8851 | -2.191 |
+#> |.....................| -4.628 | 0.4540 | 0.9341 | 0.06202 |
+#> |.....................| 0.8522 | 0.05820 | 0.7257 | 0.8143 |
+#> |.....................| 1.347 | 0.9592 | 0.7919 | 1.397 |
+#> | X| 484.82513 | 91.47 | 0.005419 | 0.2921 | 0.1118 |
+#> |.....................| 0.009776 | 0.6116 | 0.9341 | 0.06202 |
+#> |.....................| 0.8522 | 0.05820 | 0.7257 | 0.8143 |
+#> |.....................| 1.347 | 0.9592 | 0.7919 | 1.397 |
+#> | F| Forward Diff. | 34.86 | 1.871 | 0.1566 | 0.07097 |
+#> |.....................| -0.05046 | 0.7508 | -14.35 | -6.106 |
+#> |.....................| -2.960 | -0.8322 | 0.03576 | 4.926 |
+#> |.....................| -7.463 | 0.4624 | 3.813 | -8.806 |
+#> | 44| 484.54032 | 0.9935 | -1.030 | -0.9084 | -0.9396 |
+#> |.....................| -0.9859 | -0.8946 | -0.6118 | -0.7403 |
+#> |.....................| -0.8157 | -0.8739 | -0.8825 | -0.9682 |
+#> |.....................| -0.7274 | -0.8772 | -0.9538 | -0.7130 |
+#> | U| 484.54032 | 90.89 | -5.219 | -0.8851 | -2.191 |
+#> |.....................| -4.628 | 0.4537 | 0.9372 | 0.06206 |
+#> |.....................| 0.8528 | 0.05820 | 0.7260 | 0.8125 |
+#> |.....................| 1.352 | 0.9585 | 0.7904 | 1.404 |
+#> | X| 484.54032 | 90.89 | 0.005412 | 0.2921 | 0.1118 |
+#> |.....................| 0.009775 | 0.6115 | 0.9372 | 0.06206 |
+#> |.....................| 0.8528 | 0.05820 | 0.7260 | 0.8125 |
+#> |.....................| 1.352 | 0.9585 | 0.7904 | 1.404 |
+#> | F| Forward Diff. | -11.88 | 1.798 | -0.1931 | 0.1288 |
+#> |.....................| -0.02100 | 0.7941 | -13.56 | -6.327 |
+#> |.....................| -2.985 | -0.6346 | -0.1369 | 4.355 |
+#> |.....................| -7.207 | 0.4876 | 3.910 | -8.603 |
+#> | 45| 484.39828 | 0.9999 | -1.031 | -0.9082 | -0.9397 |
+#> |.....................| -0.9859 | -0.8950 | -0.6045 | -0.7369 |
+#> |.....................| -0.8141 | -0.8736 | -0.8824 | -0.9706 |
+#> |.....................| -0.7235 | -0.8774 | -0.9559 | -0.7084 |
+#> | U| 484.39828 | 91.47 | -5.220 | -0.8850 | -2.191 |
+#> |.....................| -4.628 | 0.4535 | 0.9402 | 0.06215 |
+#> |.....................| 0.8534 | 0.05821 | 0.7261 | 0.8104 |
+#> |.....................| 1.357 | 0.9582 | 0.7886 | 1.409 |
+#> | X| 484.39828 | 91.47 | 0.005407 | 0.2921 | 0.1118 |
+#> |.....................| 0.009775 | 0.6115 | 0.9402 | 0.06215 |
+#> |.....................| 0.8534 | 0.05821 | 0.7261 | 0.8104 |
+#> |.....................| 1.357 | 0.9582 | 0.7886 | 1.409 |
+#> | F| Forward Diff. | 34.75 | 1.847 | 0.1787 | 0.06647 |
+#> |.....................| -0.03069 | 0.7556 | -13.39 | -5.638 |
+#> |.....................| -2.842 | -0.7351 | -0.07352 | 4.648 |
+#> |.....................| -7.153 | 0.4383 | 3.662 | -8.575 |
+#> | 46| 484.12389 | 0.9935 | -1.033 | -0.9083 | -0.9398 |
+#> |.....................| -0.9861 | -0.8957 | -0.5972 | -0.7360 |
+#> |.....................| -0.8127 | -0.8736 | -0.8818 | -0.9724 |
+#> |.....................| -0.7196 | -0.8781 | -0.9577 | -0.7026 |
+#> | U| 484.12389 | 90.89 | -5.221 | -0.8851 | -2.192 |
+#> |.....................| -4.628 | 0.4532 | 0.9432 | 0.06218 |
+#> |.....................| 0.8540 | 0.05821 | 0.7265 | 0.8087 |
+#> |.....................| 1.361 | 0.9576 | 0.7871 | 1.416 |
+#> | X| 484.12389 | 90.89 | 0.005400 | 0.2921 | 0.1117 |
+#> |.....................| 0.009773 | 0.6114 | 0.9432 | 0.06218 |
+#> |.....................| 0.8540 | 0.05821 | 0.7265 | 0.8087 |
+#> |.....................| 1.361 | 0.9576 | 0.7871 | 1.416 |
+#> | F| Forward Diff. | -12.23 | 1.776 | -0.1772 | 0.1286 |
+#> |.....................| -0.003904 | 0.8005 | -13.23 | -5.967 |
+#> |.....................| -2.801 | -0.5825 | -0.1993 | 4.126 |
+#> |.....................| -6.930 | 0.4309 | 3.746 | -8.373 |
+#> | 47| 483.96910 | 0.9995 | -1.034 | -0.9082 | -0.9399 |
+#> |.....................| -0.9861 | -0.8963 | -0.5897 | -0.7331 |
+#> |.....................| -0.8111 | -0.8733 | -0.8815 | -0.9747 |
+#> |.....................| -0.7157 | -0.8785 | -0.9598 | -0.6976 |
+#> | U| 483.9691 | 91.44 | -5.222 | -0.8850 | -2.192 |
+#> |.....................| -4.628 | 0.4529 | 0.9464 | 0.06226 |
+#> |.....................| 0.8547 | 0.05822 | 0.7267 | 0.8067 |
+#> |.....................| 1.366 | 0.9573 | 0.7854 | 1.423 |
+#> | X| 483.9691 | 91.44 | 0.005394 | 0.2921 | 0.1117 |
+#> |.....................| 0.009773 | 0.6113 | 0.9464 | 0.06226 |
+#> |.....................| 0.8547 | 0.05822 | 0.7267 | 0.8067 |
+#> |.....................| 1.366 | 0.9573 | 0.7854 | 1.423 |
+#> | F| Forward Diff. | 31.42 | 1.822 | 0.1778 | 0.07033 |
+#> |.....................| -0.01094 | 0.7681 | -13.66 | -5.343 |
+#> |.....................| -2.704 | -0.6601 | -0.05834 | 4.483 |
+#> |.....................| -6.846 | 0.3977 | 3.514 | -8.343 |
+#> | 48| 483.71026 | 0.9937 | -1.035 | -0.9084 | -0.9400 |
+#> |.....................| -0.9863 | -0.8970 | -0.5817 | -0.7327 |
+#> |.....................| -0.8099 | -0.8734 | -0.8808 | -0.9764 |
+#> |.....................| -0.7120 | -0.8790 | -0.9614 | -0.6918 |
+#> | U| 483.71026 | 90.90 | -5.224 | -0.8851 | -2.192 |
+#> |.....................| -4.628 | 0.4526 | 0.9497 | 0.06228 |
+#> |.....................| 0.8552 | 0.05822 | 0.7272 | 0.8052 |
+#> |.....................| 1.370 | 0.9567 | 0.7840 | 1.430 |
+#> | X| 483.71026 | 90.90 | 0.005386 | 0.2921 | 0.1117 |
+#> |.....................| 0.009771 | 0.6112 | 0.9497 | 0.06228 |
+#> |.....................| 0.8552 | 0.05822 | 0.7272 | 0.8052 |
+#> |.....................| 1.370 | 0.9567 | 0.7840 | 1.430 |
+#> | F| Forward Diff. | -11.41 | 1.753 | -0.1608 | 0.1222 |
+#> |.....................| 0.01159 | 0.8050 | -10.44 | -3.810 |
+#> |.....................| -1.727 | 0.1311 | 2.133 | 3.863 |
+#> |.....................| -5.017 | 1.937 | 3.587 | -8.159 |
+#> | 49| 483.59835 | 1.000 | -1.037 | -0.9083 | -0.9401 |
+#> |.....................| -0.9863 | -0.8977 | -0.5748 | -0.7309 |
+#> |.....................| -0.8089 | -0.8737 | -0.8826 | -0.9789 |
+#> |.....................| -0.7088 | -0.8807 | -0.9637 | -0.6861 |
+#> | U| 483.59835 | 91.50 | -5.225 | -0.8850 | -2.192 |
+#> |.....................| -4.628 | 0.4523 | 0.9525 | 0.06233 |
+#> |.....................| 0.8556 | 0.05821 | 0.7260 | 0.8029 |
+#> |.....................| 1.374 | 0.9551 | 0.7819 | 1.437 |
+#> | X| 483.59835 | 91.50 | 0.005379 | 0.2921 | 0.1117 |
+#> |.....................| 0.009771 | 0.6112 | 0.9525 | 0.06233 |
+#> |.....................| 0.8556 | 0.05821 | 0.7260 | 0.8029 |
+#> |.....................| 1.374 | 0.9551 | 0.7819 | 1.437 |
+#> | F| Forward Diff. | 35.70 | 1.806 | 0.2381 | 0.06477 |
+#> |.....................| 0.008951 | 0.7715 | -12.71 | -4.946 |
+#> |.....................| -2.552 | -0.6506 | -0.07612 | 4.309 |
+#> |.....................| -6.609 | 0.2622 | 3.318 | -8.104 |
+#> | 50| 483.34903 | 0.9946 | -1.038 | -0.9084 | -0.9402 |
+#> |.....................| -0.9865 | -0.8986 | -0.5687 | -0.7321 |
+#> |.....................| -0.8087 | -0.8746 | -0.8853 | -0.9811 |
+#> |.....................| -0.7064 | -0.8834 | -0.9659 | -0.6790 |
+#> | U| 483.34903 | 90.99 | -5.227 | -0.8851 | -2.192 |
+#> |.....................| -4.629 | 0.4518 | 0.9551 | 0.06229 |
+#> |.....................| 0.8557 | 0.05818 | 0.7240 | 0.8009 |
+#> |.....................| 1.377 | 0.9526 | 0.7800 | 1.445 |
+#> | X| 483.34903 | 90.99 | 0.005370 | 0.2921 | 0.1117 |
+#> |.....................| 0.009769 | 0.6111 | 0.9551 | 0.06229 |
+#> |.....................| 0.8557 | 0.05818 | 0.7240 | 0.8009 |
+#> |.....................| 1.377 | 0.9526 | 0.7800 | 1.445 |
+#> | F| Forward Diff. | -5.120 | 1.736 | -0.09503 | 0.1090 |
+#> |.....................| 0.03046 | 0.8092 | -12.63 | -5.226 |
+#> |.....................| -2.620 | -0.5304 | -0.3057 | 3.753 |
+#> |.....................| -6.427 | 0.07650 | 3.398 | -7.915 |
+#> | 51| 483.15597 | 0.9980 | -1.040 | -0.9083 | -0.9402 |
+#> |.....................| -0.9866 | -0.8991 | -0.5603 | -0.7286 |
+#> |.....................| -0.8069 | -0.8742 | -0.8851 | -0.9836 |
+#> |.....................| -0.7022 | -0.8834 | -0.9682 | -0.6737 |
+#> | U| 483.15597 | 91.30 | -5.228 | -0.8851 | -2.192 |
+#> |.....................| -4.629 | 0.4516 | 0.9585 | 0.06239 |
+#> |.....................| 0.8564 | 0.05819 | 0.7241 | 0.7987 |
+#> |.....................| 1.382 | 0.9525 | 0.7781 | 1.452 |
+#> | X| 483.15597 | 91.30 | 0.005364 | 0.2921 | 0.1117 |
+#> |.....................| 0.009769 | 0.6110 | 0.9585 | 0.06239 |
+#> |.....................| 0.8564 | 0.05819 | 0.7241 | 0.7987 |
+#> |.....................| 1.382 | 0.9525 | 0.7781 | 1.452 |
+#> | 52| 483.02721 | 1.004 | -1.042 | -0.9082 | -0.9404 |
+#> |.....................| -0.9866 | -0.9001 | -0.5449 | -0.7222 |
+#> |.....................| -0.8037 | -0.8736 | -0.8847 | -0.9882 |
+#> |.....................| -0.6943 | -0.8835 | -0.9723 | -0.6641 |
+#> | U| 483.02721 | 91.87 | -5.230 | -0.8850 | -2.192 |
+#> |.....................| -4.629 | 0.4511 | 0.9649 | 0.06258 |
+#> |.....................| 0.8577 | 0.05821 | 0.7244 | 0.7946 |
+#> |.....................| 1.391 | 0.9524 | 0.7746 | 1.463 |
+#> | X| 483.02721 | 91.87 | 0.005352 | 0.2921 | 0.1117 |
+#> |.....................| 0.009768 | 0.6109 | 0.9649 | 0.06258 |
+#> |.....................| 0.8577 | 0.05821 | 0.7244 | 0.7946 |
+#> |.....................| 1.391 | 0.9524 | 0.7746 | 1.463 |
+#> | F| Forward Diff. | 64.04 | 1.793 | 0.5284 | 0.01389 |
+#> |.....................| 0.02898 | 0.7509 | -12.63 | -3.976 |
+#> |.....................| -2.339 | -0.6213 | 0.1061 | 4.124 |
+#> |.....................| -6.092 | 0.06517 | 2.880 | -7.726 |
+#> | 53| 482.23689 | 0.9946 | -1.047 | -0.9090 | -0.9407 |
+#> |.....................| -0.9878 | -0.9036 | -0.5201 | -0.7284 |
+#> |.....................| -0.8010 | -0.8752 | -0.8830 | -0.9901 |
+#> |.....................| -0.6858 | -0.8831 | -0.9756 | -0.6451 |
+#> | U| 482.23689 | 90.99 | -5.236 | -0.8857 | -2.192 |
+#> |.....................| -4.630 | 0.4496 | 0.9752 | 0.06240 |
+#> |.....................| 0.8589 | 0.05816 | 0.7257 | 0.7929 |
+#> |.....................| 1.401 | 0.9528 | 0.7717 | 1.486 |
+#> | X| 482.23689 | 90.99 | 0.005323 | 0.2920 | 0.1116 |
+#> |.....................| 0.009757 | 0.6105 | 0.9752 | 0.06240 |
+#> |.....................| 0.8589 | 0.05816 | 0.7257 | 0.7929 |
+#> |.....................| 1.401 | 0.9528 | 0.7717 | 1.486 |
+#> | F| Forward Diff. | -6.401 | 1.688 | -0.06693 | 0.1101 |
+#> |.....................| 0.07752 | 0.8485 | -12.38 | -4.258 |
+#> |.....................| -2.381 | -0.3971 | -0.4532 | 3.327 |
+#> |.....................| -5.692 | 0.09795 | 3.049 | -7.221 |
+#> | 54| 481.84664 | 1.002 | -1.052 | -0.9094 | -0.9410 |
+#> |.....................| -0.9885 | -0.9064 | -0.4925 | -0.7287 |
+#> |.....................| -0.7974 | -0.8758 | -0.8811 | -0.9941 |
+#> |.....................| -0.6765 | -0.8831 | -0.9802 | -0.6288 |
+#> | U| 481.84664 | 91.67 | -5.240 | -0.8860 | -2.193 |
+#> |.....................| -4.631 | 0.4482 | 0.9866 | 0.06239 |
+#> |.....................| 0.8604 | 0.05815 | 0.7270 | 0.7893 |
+#> |.....................| 1.412 | 0.9528 | 0.7678 | 1.506 |
+#> | X| 481.84664 | 91.67 | 0.005298 | 0.2919 | 0.1116 |
+#> |.....................| 0.009749 | 0.6102 | 0.9866 | 0.06239 |
+#> |.....................| 0.8604 | 0.05815 | 0.7270 | 0.7893 |
+#> |.....................| 1.412 | 0.9528 | 0.7678 | 1.506 |
+#> | F| Forward Diff. | 47.13 | 1.726 | 0.4206 | 0.02536 |
+#> |.....................| 0.06828 | 0.8062 | -11.83 | -3.346 |
+#> |.....................| -2.102 | -0.4847 | -0.09759 | 3.731 |
+#> |.....................| -5.096 | -0.5769 | 2.736 | -6.997 |
+#> | 55| 481.27209 | 0.9943 | -1.058 | -0.9105 | -0.9413 |
+#> |.....................| -0.9900 | -0.9106 | -0.4653 | -0.7394 |
+#> |.....................| -0.7957 | -0.8780 | -0.8782 | -0.9956 |
+#> |.....................| -0.6736 | -0.8789 | -0.9829 | -0.6135 |
+#> | U| 481.27209 | 90.96 | -5.246 | -0.8870 | -2.193 |
+#> |.....................| -4.632 | 0.4464 | 0.9978 | 0.06208 |
+#> |.....................| 0.8611 | 0.05808 | 0.7292 | 0.7879 |
+#> |.....................| 1.416 | 0.9569 | 0.7655 | 1.525 |
+#> | X| 481.27209 | 90.96 | 0.005268 | 0.2917 | 0.1116 |
+#> |.....................| 0.009735 | 0.6098 | 0.9978 | 0.06208 |
+#> |.....................| 0.8611 | 0.05808 | 0.7292 | 0.7879 |
+#> |.....................| 1.416 | 0.9569 | 0.7655 | 1.525 |
+#> | F| Forward Diff. | -10.35 | 1.643 | -0.1028 | 0.1091 |
+#> |.....................| 0.1039 | 0.8949 | -11.59 | -3.607 |
+#> |.....................| -2.172 | -0.3207 | -0.4703 | 3.042 |
+#> |.....................| -5.188 | 0.5388 | 2.890 | -6.602 |
+#> | 56| 480.86800 | 0.9992 | -1.064 | -0.9113 | -0.9415 |
+#> |.....................| -0.9915 | -0.9152 | -0.4371 | -0.7498 |
+#> |.....................| -0.7937 | -0.8800 | -0.8752 | -0.9980 |
+#> |.....................| -0.6700 | -0.8785 | -0.9867 | -0.5989 |
+#> | U| 480.868 | 91.41 | -5.252 | -0.8877 | -2.193 |
+#> |.....................| -4.634 | 0.4442 | 1.010 | 0.06178 |
+#> |.....................| 0.8619 | 0.05803 | 0.7313 | 0.7858 |
+#> |.....................| 1.420 | 0.9572 | 0.7622 | 1.543 |
+#> | X| 480.868 | 91.41 | 0.005236 | 0.2916 | 0.1115 |
+#> |.....................| 0.009720 | 0.6093 | 1.010 | 0.06178 |
+#> |.....................| 0.8619 | 0.05803 | 0.7313 | 0.7858 |
+#> |.....................| 1.420 | 0.9572 | 0.7622 | 1.543 |
+#> | 57| 480.18757 | 0.9994 | -1.075 | -0.9131 | -0.9420 |
+#> |.....................| -0.9946 | -0.9242 | -0.3882 | -0.7756 |
+#> |.....................| -0.7917 | -0.8845 | -0.8694 | -1.000 |
+#> |.....................| -0.6674 | -0.8772 | -0.9919 | -0.5742 |
+#> | U| 480.18757 | 91.43 | -5.264 | -0.8893 | -2.194 |
+#> |.....................| -4.637 | 0.4401 | 1.030 | 0.06104 |
+#> |.....................| 0.8627 | 0.05790 | 0.7356 | 0.7839 |
+#> |.....................| 1.423 | 0.9585 | 0.7577 | 1.573 |
+#> | X| 480.18757 | 91.43 | 0.005177 | 0.2913 | 0.1115 |
+#> |.....................| 0.009690 | 0.6083 | 1.030 | 0.06104 |
+#> |.....................| 0.8627 | 0.05790 | 0.7356 | 0.7839 |
+#> |.....................| 1.423 | 0.9585 | 0.7577 | 1.573 |
+#> | 58| 477.33677 | 1.000 | -1.128 | -0.9215 | -0.9444 |
+#> |.....................| -1.009 | -0.9662 | -0.1601 | -0.8958 |
+#> |.....................| -0.7824 | -0.9055 | -0.8420 | -1.010 |
+#> |.....................| -0.6551 | -0.8713 | -1.016 | -0.4591 |
+#> | U| 477.33677 | 91.51 | -5.317 | -0.8967 | -2.196 |
+#> |.....................| -4.651 | 0.4208 | 1.124 | 0.05757 |
+#> |.....................| 0.8666 | 0.05729 | 0.7556 | 0.7749 |
+#> |.....................| 1.438 | 0.9642 | 0.7367 | 1.713 |
+#> | X| 477.33677 | 91.51 | 0.004910 | 0.2897 | 0.1112 |
+#> |.....................| 0.009550 | 0.6037 | 1.124 | 0.05757 |
+#> |.....................| 0.8666 | 0.05729 | 0.7556 | 0.7749 |
+#> |.....................| 1.438 | 0.9642 | 0.7367 | 1.713 |
+#> | 59| 470.34077 | 1.005 | -1.340 | -0.9551 | -0.9536 |
+#> |.....................| -1.067 | -1.134 | 0.7520 | -1.376 |
+#> |.....................| -0.7448 | -0.9894 | -0.7326 | -1.050 |
+#> |.....................| -0.6055 | -0.8475 | -1.115 | 0.001078 |
+#> | U| 470.34077 | 91.93 | -5.528 | -0.9265 | -2.205 |
+#> |.....................| -4.709 | 0.3439 | 1.502 | 0.04372 |
+#> |.....................| 0.8821 | 0.05487 | 0.8354 | 0.7391 |
+#> |.....................| 1.496 | 0.9871 | 0.6524 | 2.272 |
+#> | X| 470.34077 | 91.93 | 0.003973 | 0.2836 | 0.1102 |
+#> |.....................| 0.009011 | 0.5851 | 1.502 | 0.04372 |
+#> |.....................| 0.8821 | 0.05487 | 0.8354 | 0.7391 |
+#> |.....................| 1.496 | 0.9871 | 0.6524 | 2.272 |
+#> | F| Forward Diff. | 26.15 | 0.9841 | -0.2917 | -0.5557 |
+#> |.....................| 0.1743 | 0.07961 | -5.483 | -2.977 |
+#> |.....................| -1.594 | -1.883 | 1.921 | 2.622 |
+#> |.....................| -2.684 | 3.199 | -3.516 | -0.2713 |
+#> | 60| 503.34963 | 1.001 | -1.624 | -0.8890 | -0.8555 |
+#> |.....................| -1.160 | -1.269 | 1.871 | -1.579 |
+#> |.....................| -0.5570 | -0.7566 | -0.9888 | -1.205 |
+#> |.....................| -0.4219 | -1.204 | -0.3205 | 0.003684 |
+#> | U| 503.34963 | 91.54 | -5.813 | -0.8679 | -2.107 |
+#> |.....................| -4.802 | 0.2817 | 1.965 | 0.03787 |
+#> |.....................| 0.9599 | 0.06159 | 0.6484 | 0.5998 |
+#> |.....................| 1.714 | 0.6438 | 1.334 | 2.275 |
+#> | X| 503.34963 | 91.54 | 0.002989 | 0.2957 | 0.1216 |
+#> |.....................| 0.008214 | 0.5700 | 1.965 | 0.03787 |
+#> |.....................| 0.9599 | 0.06159 | 0.6484 | 0.5998 |
+#> |.....................| 1.714 | 0.6438 | 1.334 | 2.275 |
+#> | 61| 469.52776 | 1.001 | -1.377 | -0.9480 | -0.9425 |
+#> |.....................| -1.079 | -1.153 | 0.9014 | -1.405 |
+#> |.....................| -0.7213 | -0.9635 | -0.7590 | -1.066 |
+#> |.....................| -0.5863 | -0.9260 | -1.020 | 0.002305 |
+#> | U| 469.52776 | 91.55 | -5.565 | -0.9203 | -2.194 |
+#> |.....................| -4.721 | 0.3353 | 1.564 | 0.04288 |
+#> |.....................| 0.8919 | 0.05562 | 0.8161 | 0.7248 |
+#> |.....................| 1.519 | 0.9115 | 0.7335 | 2.274 |
+#> | X| 469.52776 | 91.55 | 0.003829 | 0.2849 | 0.1114 |
+#> |.....................| 0.008907 | 0.5831 | 1.564 | 0.04288 |
+#> |.....................| 0.8919 | 0.05562 | 0.8161 | 0.7248 |
+#> |.....................| 1.519 | 0.9115 | 0.7335 | 2.274 |
+#> | F| Forward Diff. | -33.46 | 0.8466 | -0.2714 | -0.3437 |
+#> |.....................| -0.005169 | 0.9674 | -4.363 | -2.175 |
+#> |.....................| -0.4723 | -1.194 | 1.668 | 1.180 |
+#> |.....................| -1.975 | -3.231 | 4.715 | 0.6860 |
+#> | 62| 468.69396 | 1.009 | -1.417 | -0.9407 | -0.9181 |
+#> |.....................| -1.088 | -1.184 | 1.029 | -1.410 |
+#> |.....................| -0.7106 | -0.9016 | -0.8502 | -1.110 |
+#> |.....................| -0.5641 | -0.8957 | -1.025 | -0.08379 |
+#> | U| 468.69396 | 92.28 | -5.606 | -0.9138 | -2.170 |
+#> |.....................| -4.730 | 0.3207 | 1.617 | 0.04273 |
+#> |.....................| 0.8963 | 0.05740 | 0.7496 | 0.6857 |
+#> |.....................| 1.546 | 0.9407 | 0.7298 | 2.169 |
+#> | X| 468.69396 | 92.28 | 0.003677 | 0.2862 | 0.1142 |
+#> |.....................| 0.008826 | 0.5795 | 1.617 | 0.04273 |
+#> |.....................| 0.8963 | 0.05740 | 0.7496 | 0.6857 |
+#> |.....................| 1.546 | 0.9407 | 0.7298 | 2.169 |
+#> | F| Forward Diff. | 44.64 | 0.7919 | 0.8591 | -0.3536 |
+#> |.....................| -0.1337 | 0.2061 | -3.251 | 1.076 |
+#> |.....................| 0.6486 | -0.6734 | -0.006662 | -4.031 |
+#> |.....................| -0.9510 | -1.369 | 2.636 | 0.2207 |
+#> | 63| 468.25975 | 1.001 | -1.457 | -0.9435 | -0.8944 |
+#> |.....................| -1.092 | -1.207 | 1.162 | -1.430 |
+#> |.....................| -0.7163 | -0.8453 | -0.9089 | -1.031 |
+#> |.....................| -0.5350 | -0.9084 | -1.055 | -0.1705 |
+#> | U| 468.25975 | 91.62 | -5.645 | -0.9163 | -2.146 |
+#> |.....................| -4.734 | 0.3104 | 1.671 | 0.04217 |
+#> |.....................| 0.8939 | 0.05903 | 0.7067 | 0.7562 |
+#> |.....................| 1.580 | 0.9284 | 0.7040 | 2.064 |
+#> | X| 468.25975 | 91.62 | 0.003534 | 0.2857 | 0.1169 |
+#> |.....................| 0.008791 | 0.5770 | 1.671 | 0.04217 |
+#> |.....................| 0.8939 | 0.05903 | 0.7067 | 0.7562 |
+#> |.....................| 1.580 | 0.9284 | 0.7040 | 2.064 |
+#> | F| Forward Diff. | -27.10 | 0.6132 | -0.09159 | -0.08800 |
+#> |.....................| -0.1078 | -0.3202 | -2.388 | 1.638 |
+#> |.....................| 1.140 | 0.1171 | 0.1600 | 3.377 |
+#> |.....................| 1.163 | -2.226 | -0.6898 | -0.6683 |
+#> | 64| 467.71969 | 1.007 | -1.501 | -0.9546 | -0.8725 |
+#> |.....................| -1.088 | -1.196 | 1.309 | -1.518 |
+#> |.....................| -0.7729 | -0.8084 | -0.9408 | -1.028 |
+#> |.....................| -0.5596 | -0.8715 | -1.022 | -0.2167 |
+#> | U| 467.71969 | 92.14 | -5.690 | -0.9262 | -2.124 |
+#> |.....................| -4.730 | 0.3152 | 1.732 | 0.03962 |
+#> |.....................| 0.8705 | 0.06009 | 0.6835 | 0.7588 |
+#> |.....................| 1.551 | 0.9640 | 0.7321 | 2.007 |
+#> | X| 467.71969 | 92.14 | 0.003381 | 0.2837 | 0.1195 |
+#> |.....................| 0.008831 | 0.5781 | 1.732 | 0.03962 |
+#> |.....................| 0.8705 | 0.06009 | 0.6835 | 0.7588 |
+#> |.....................| 1.551 | 0.9640 | 0.7321 | 2.007 |
+#> | F| Forward Diff. | 13.64 | 0.5263 | -0.09449 | -0.03300 |
+#> |.....................| -0.2497 | 0.5177 | -1.944 | 1.719 |
+#> |.....................| 0.02781 | -0.4546 | 0.1053 | 4.139 |
+#> |.....................| 0.2369 | 0.8861 | 1.752 | -0.4404 |
+#> | 65| 467.30536 | 1.004 | -1.542 | -0.9574 | -0.8551 |
+#> |.....................| -1.078 | -1.202 | 1.437 | -1.633 |
+#> |.....................| -0.8162 | -0.7674 | -0.9588 | -1.081 |
+#> |.....................| -0.5907 | -0.8860 | -1.037 | -0.2723 |
+#> | U| 467.30536 | 91.87 | -5.731 | -0.9286 | -2.107 |
+#> |.....................| -4.720 | 0.3124 | 1.785 | 0.03631 |
+#> |.....................| 0.8526 | 0.06127 | 0.6704 | 0.7116 |
+#> |.....................| 1.514 | 0.9500 | 0.7187 | 1.940 |
+#> | X| 467.30536 | 91.87 | 0.003244 | 0.2832 | 0.1216 |
+#> |.....................| 0.008917 | 0.5775 | 1.785 | 0.03631 |
+#> |.....................| 0.8526 | 0.06127 | 0.6704 | 0.7116 |
+#> |.....................| 1.514 | 0.9500 | 0.7187 | 1.940 |
+#> | F| Forward Diff. | -28.84 | 0.5077 | -0.1377 | 0.05990 |
+#> |.....................| -0.2272 | 0.7424 | -2.070 | -0.4026 |
+#> |.....................| -0.6342 | -0.6074 | -0.7367 | -1.927 |
+#> |.....................| -1.174 | -0.4282 | -0.2913 | -0.8226 |
+#> | 66| 467.70919 | 1.018 | -1.590 | -0.9528 | -0.8478 |
+#> |.....................| -1.050 | -1.273 | 1.541 | -1.746 |
+#> |.....................| -0.7981 | -0.6862 | -0.9431 | -1.082 |
+#> |.....................| -0.5846 | -0.9179 | -1.062 | -0.3171 |
+#> | U| 467.70919 | 93.14 | -5.778 | -0.9245 | -2.100 |
+#> |.....................| -4.692 | 0.2799 | 1.829 | 0.03305 |
+#> |.....................| 0.8601 | 0.06362 | 0.6818 | 0.7103 |
+#> |.....................| 1.521 | 0.9193 | 0.6977 | 1.885 |
+#> | X| 467.70919 | 93.14 | 0.003094 | 0.2840 | 0.1225 |
+#> |.....................| 0.009168 | 0.5695 | 1.829 | 0.03305 |
+#> |.....................| 0.8601 | 0.06362 | 0.6818 | 0.7103 |
+#> |.....................| 1.521 | 0.9193 | 0.6977 | 1.885 |
+#> | 67| 467.47896 | 1.015 | -1.557 | -0.9559 | -0.8529 |
+#> |.....................| -1.069 | -1.224 | 1.469 | -1.667 |
+#> |.....................| -0.8105 | -0.7423 | -0.9538 | -1.081 |
+#> |.....................| -0.5885 | -0.8957 | -1.045 | -0.2858 |
+#> | U| 467.47896 | 92.90 | -5.746 | -0.9273 | -2.105 |
+#> |.....................| -4.711 | 0.3023 | 1.799 | 0.03531 |
+#> |.....................| 0.8550 | 0.06200 | 0.6740 | 0.7117 |
+#> |.....................| 1.517 | 0.9407 | 0.7123 | 1.923 |
+#> | X| 467.47896 | 92.90 | 0.003197 | 0.2835 | 0.1219 |
+#> |.....................| 0.008994 | 0.5750 | 1.799 | 0.03531 |
+#> |.....................| 0.8550 | 0.06200 | 0.6740 | 0.7117 |
+#> |.....................| 1.517 | 0.9407 | 0.7123 | 1.923 |
+#> | 68| 467.47242 | 1.015 | -1.547 | -0.9569 | -0.8545 |
+#> |.....................| -1.075 | -1.209 | 1.447 | -1.644 |
+#> |.....................| -0.8142 | -0.7594 | -0.9570 | -1.080 |
+#> |.....................| -0.5898 | -0.8890 | -1.040 | -0.2763 |
+#> | U| 467.47242 | 92.83 | -5.736 | -0.9282 | -2.106 |
+#> |.....................| -4.717 | 0.3092 | 1.790 | 0.03600 |
+#> |.....................| 0.8534 | 0.06150 | 0.6716 | 0.7121 |
+#> |.....................| 1.515 | 0.9472 | 0.7168 | 1.935 |
+#> | X| 467.47242 | 92.83 | 0.003229 | 0.2833 | 0.1217 |
+#> |.....................| 0.008942 | 0.5767 | 1.790 | 0.03600 |
+#> |.....................| 0.8534 | 0.06150 | 0.6716 | 0.7121 |
+#> |.....................| 1.515 | 0.9472 | 0.7168 | 1.935 |
+#> | 69| 467.34503 | 1.012 | -1.542 | -0.9574 | -0.8552 |
+#> |.....................| -1.078 | -1.203 | 1.437 | -1.633 |
+#> |.....................| -0.8160 | -0.7673 | -0.9586 | -1.080 |
+#> |.....................| -0.5904 | -0.8859 | -1.037 | -0.2720 |
+#> | U| 467.34503 | 92.56 | -5.731 | -0.9286 | -2.107 |
+#> |.....................| -4.720 | 0.3123 | 1.786 | 0.03631 |
+#> |.....................| 0.8527 | 0.06128 | 0.6705 | 0.7121 |
+#> |.....................| 1.514 | 0.9501 | 0.7188 | 1.940 |
+#> | X| 467.34503 | 92.56 | 0.003244 | 0.2832 | 0.1216 |
+#> |.....................| 0.008918 | 0.5775 | 1.786 | 0.03631 |
+#> |.....................| 0.8527 | 0.06128 | 0.6705 | 0.7121 |
+#> |.....................| 1.514 | 0.9501 | 0.7188 | 1.940 |
+#> | 70| 467.25859 | 1.007 | -1.542 | -0.9574 | -0.8552 |
+#> |.....................| -1.078 | -1.202 | 1.437 | -1.633 |
+#> |.....................| -0.8161 | -0.7674 | -0.9587 | -1.080 |
+#> |.....................| -0.5906 | -0.8860 | -1.037 | -0.2722 |
+#> | U| 467.25859 | 92.16 | -5.731 | -0.9286 | -2.107 |
+#> |.....................| -4.720 | 0.3124 | 1.785 | 0.03631 |
+#> |.....................| 0.8526 | 0.06127 | 0.6704 | 0.7118 |
+#> |.....................| 1.514 | 0.9500 | 0.7187 | 1.940 |
+#> | X| 467.25859 | 92.16 | 0.003244 | 0.2832 | 0.1216 |
+#> |.....................| 0.008918 | 0.5775 | 1.785 | 0.03631 |
+#> |.....................| 0.8526 | 0.06127 | 0.6704 | 0.7118 |
+#> |.....................| 1.514 | 0.9500 | 0.7187 | 1.940 |
+#> | F| Forward Diff. | 0.4422 | 0.5213 | 0.04284 | 0.02840 |
+#> |.....................| -0.2383 | 0.7531 | -2.043 | -0.07081 |
+#> |.....................| -0.6548 | -0.6872 | -0.7073 | -1.773 |
+#> |.....................| -1.488 | -0.4400 | -0.3907 | -0.8156 |
+#> | 71| 467.25330 | 1.007 | -1.543 | -0.9574 | -0.8552 |
+#> |.....................| -1.078 | -1.203 | 1.439 | -1.633 |
+#> |.....................| -0.8155 | -0.7668 | -0.9581 | -1.079 |
+#> |.....................| -0.5893 | -0.8856 | -1.037 | -0.2714 |
+#> | U| 467.2533 | 92.12 | -5.731 | -0.9287 | -2.107 |
+#> |.....................| -4.720 | 0.3121 | 1.786 | 0.03631 |
+#> |.....................| 0.8529 | 0.06129 | 0.6709 | 0.7133 |
+#> |.....................| 1.516 | 0.9504 | 0.7190 | 1.941 |
+#> | X| 467.2533 | 92.12 | 0.003243 | 0.2832 | 0.1216 |
+#> |.....................| 0.008919 | 0.5774 | 1.786 | 0.03631 |
+#> |.....................| 0.8529 | 0.06129 | 0.6709 | 0.7133 |
+#> |.....................| 1.516 | 0.9504 | 0.7190 | 1.941 |
+#> | F| Forward Diff. | -3.065 | 0.5175 | 0.01752 | 0.03302 |
+#> |.....................| -0.2370 | 0.7457 | -1.985 | -0.01476 |
+#> |.....................| -0.5869 | -0.6438 | -0.7222 | -1.672 |
+#> |.....................| -1.086 | -0.3942 | -0.3461 | -0.8075 |
+#> | 72| 467.24583 | 1.008 | -1.544 | -0.9571 | -0.8551 |
+#> |.....................| -1.077 | -1.206 | 1.442 | -1.635 |
+#> |.....................| -0.8142 | -0.7642 | -0.9569 | -1.078 |
+#> |.....................| -0.5901 | -0.8857 | -1.037 | -0.2715 |
+#> | U| 467.24583 | 92.22 | -5.733 | -0.9284 | -2.107 |
+#> |.....................| -4.719 | 0.3108 | 1.788 | 0.03626 |
+#> |.....................| 0.8534 | 0.06137 | 0.6718 | 0.7144 |
+#> |.....................| 1.515 | 0.9503 | 0.7191 | 1.941 |
+#> | X| 467.24583 | 92.22 | 0.003238 | 0.2832 | 0.1216 |
+#> |.....................| 0.008927 | 0.5771 | 1.788 | 0.03626 |
+#> |.....................| 0.8534 | 0.06137 | 0.6718 | 0.7144 |
+#> |.....................| 1.515 | 0.9503 | 0.7191 | 1.941 |
+#> | F| Forward Diff. | 6.834 | 0.5162 | 0.08982 | 0.01752 |
+#> |.....................| -0.2436 | 0.7158 | -2.020 | -0.04939 |
+#> |.....................| -0.5459 | -0.6263 | -0.5712 | -1.499 |
+#> |.....................| -1.429 | -0.4150 | -0.4098 | -0.8001 |
+#> | 73| 467.23713 | 1.007 | -1.546 | -0.9569 | -0.8551 |
+#> |.....................| -1.076 | -1.209 | 1.446 | -1.636 |
+#> |.....................| -0.8132 | -0.7618 | -0.9559 | -1.076 |
+#> |.....................| -0.5919 | -0.8860 | -1.037 | -0.2716 |
+#> | U| 467.23713 | 92.12 | -5.734 | -0.9282 | -2.107 |
+#> |.....................| -4.718 | 0.3095 | 1.789 | 0.03621 |
+#> |.....................| 0.8538 | 0.06143 | 0.6724 | 0.7154 |
+#> |.....................| 1.513 | 0.9500 | 0.7191 | 1.941 |
+#> | X| 467.23713 | 92.12 | 0.003233 | 0.2833 | 0.1216 |
+#> |.....................| 0.008936 | 0.5768 | 1.789 | 0.03621 |
+#> |.....................| 0.8538 | 0.06143 | 0.6724 | 0.7154 |
+#> |.....................| 1.513 | 0.9500 | 0.7191 | 1.941 |
+#> | F| Forward Diff. | -3.249 | 0.5067 | 0.04417 | 0.02698 |
+#> |.....................| -0.2393 | 0.6753 | -1.942 | -0.1419 |
+#> |.....................| -0.5001 | -0.5983 | -0.6679 | -1.518 |
+#> |.....................| -1.576 | -0.4506 | -0.4091 | -0.8075 |
+#> | 74| 467.22826 | 1.008 | -1.548 | -0.9568 | -0.8550 |
+#> |.....................| -1.074 | -1.212 | 1.450 | -1.638 |
+#> |.....................| -0.8127 | -0.7593 | -0.9548 | -1.076 |
+#> |.....................| -0.5925 | -0.8862 | -1.037 | -0.2718 |
+#> | U| 467.22826 | 92.20 | -5.736 | -0.9281 | -2.107 |
+#> |.....................| -4.716 | 0.3080 | 1.791 | 0.03615 |
+#> |.....................| 0.8540 | 0.06151 | 0.6733 | 0.7160 |
+#> |.....................| 1.512 | 0.9499 | 0.7192 | 1.940 |
+#> | X| 467.22826 | 92.20 | 0.003227 | 0.2833 | 0.1216 |
+#> |.....................| 0.008947 | 0.5764 | 1.791 | 0.03615 |
+#> |.....................| 0.8540 | 0.06151 | 0.6733 | 0.7160 |
+#> |.....................| 1.512 | 0.9499 | 0.7192 | 1.940 |
+#> | F| Forward Diff. | 4.158 | 0.5052 | 0.09162 | 0.01474 |
+#> |.....................| -0.2441 | 0.6411 | -1.927 | 0.008374 |
+#> |.....................| -0.4204 | -0.5681 | -0.5325 | -1.398 |
+#> |.....................| -1.545 | -0.4616 | -0.4623 | -0.8062 |
+#> | 75| 467.21798 | 1.007 | -1.549 | -0.9567 | -0.8549 |
+#> |.....................| -1.073 | -1.215 | 1.453 | -1.641 |
+#> |.....................| -0.8130 | -0.7568 | -0.9541 | -1.075 |
+#> |.....................| -0.5920 | -0.8862 | -1.036 | -0.2722 |
+#> | U| 467.21798 | 92.13 | -5.738 | -0.9280 | -2.107 |
+#> |.....................| -4.715 | 0.3065 | 1.792 | 0.03607 |
+#> |.....................| 0.8539 | 0.06158 | 0.6738 | 0.7163 |
+#> |.....................| 1.512 | 0.9498 | 0.7195 | 1.940 |
+#> | X| 467.21798 | 92.13 | 0.003221 | 0.2833 | 0.1216 |
+#> |.....................| 0.008959 | 0.5760 | 1.792 | 0.03607 |
+#> |.....................| 0.8539 | 0.06158 | 0.6738 | 0.7163 |
+#> |.....................| 1.512 | 0.9498 | 0.7195 | 1.940 |
+#> | F| Forward Diff. | -2.820 | 0.4989 | 0.05960 | 0.01935 |
+#> |.....................| -0.2421 | 0.6061 | -1.914 | -0.2151 |
+#> |.....................| -0.5103 | -0.6093 | -0.7625 | -1.437 |
+#> |.....................| -1.510 | -0.4672 | -0.4489 | -0.8043 |
+#> | 76| 467.20848 | 1.008 | -1.551 | -0.9569 | -0.8547 |
+#> |.....................| -1.072 | -1.218 | 1.456 | -1.643 |
+#> |.....................| -0.8130 | -0.7539 | -0.9520 | -1.075 |
+#> |.....................| -0.5920 | -0.8859 | -1.036 | -0.2725 |
+#> | U| 467.20848 | 92.20 | -5.740 | -0.9282 | -2.106 |
+#> |.....................| -4.714 | 0.3053 | 1.793 | 0.03601 |
+#> |.....................| 0.8539 | 0.06166 | 0.6753 | 0.7165 |
+#> |.....................| 1.512 | 0.9501 | 0.7200 | 1.939 |
+#> | X| 467.20848 | 92.20 | 0.003215 | 0.2833 | 0.1217 |
+#> |.....................| 0.008973 | 0.5757 | 1.793 | 0.03601 |
+#> |.....................| 0.8539 | 0.06166 | 0.6753 | 0.7165 |
+#> |.....................| 1.512 | 0.9501 | 0.7200 | 1.939 |
+#> | F| Forward Diff. | 3.706 | 0.4993 | 0.1020 | 0.01046 |
+#> |.....................| -0.2448 | 0.5847 | -1.899 | -0.1702 |
+#> |.....................| -0.3837 | -0.5516 | -0.5275 | -1.370 |
+#> |.....................| -1.509 | -0.4527 | -0.4630 | -0.7991 |
+#> | 77| 467.20140 | 1.007 | -1.554 | -0.9572 | -0.8545 |
+#> |.....................| -1.070 | -1.221 | 1.459 | -1.644 |
+#> |.....................| -0.8137 | -0.7511 | -0.9495 | -1.075 |
+#> |.....................| -0.5926 | -0.8856 | -1.035 | -0.2726 |
+#> | U| 467.2014 | 92.12 | -5.742 | -0.9285 | -2.106 |
+#> |.....................| -4.712 | 0.3041 | 1.795 | 0.03600 |
+#> |.....................| 0.8536 | 0.06174 | 0.6772 | 0.7169 |
+#> |.....................| 1.512 | 0.9504 | 0.7205 | 1.939 |
+#> | X| 467.2014 | 92.12 | 0.003207 | 0.2832 | 0.1217 |
+#> |.....................| 0.008990 | 0.5754 | 1.795 | 0.03600 |
+#> |.....................| 0.8536 | 0.06174 | 0.6772 | 0.7169 |
+#> |.....................| 1.512 | 0.9504 | 0.7205 | 1.939 |
+#> | F| Forward Diff. | -4.697 | 0.4875 | 0.03394 | 0.01314 |
+#> |.....................| -0.2450 | 0.5527 | -1.903 | -0.2230 |
+#> |.....................| -0.3367 | -0.5055 | -0.4386 | -1.334 |
+#> |.....................| -1.570 | -0.4518 | -0.4312 | -0.7987 |
+#> | 78| 467.19155 | 1.008 | -1.556 | -0.9574 | -0.8545 |
+#> |.....................| -1.067 | -1.224 | 1.462 | -1.645 |
+#> |.....................| -0.8159 | -0.7492 | -0.9499 | -1.074 |
+#> |.....................| -0.5924 | -0.8858 | -1.035 | -0.2722 |
+#> | U| 467.19155 | 92.18 | -5.745 | -0.9286 | -2.106 |
+#> |.....................| -4.709 | 0.3027 | 1.796 | 0.03596 |
+#> |.....................| 0.8527 | 0.06180 | 0.6768 | 0.7173 |
+#> |.....................| 1.512 | 0.9502 | 0.7208 | 1.940 |
+#> | X| 467.19155 | 92.18 | 0.003200 | 0.2832 | 0.1217 |
+#> |.....................| 0.009010 | 0.5751 | 1.796 | 0.03596 |
+#> |.....................| 0.8527 | 0.06180 | 0.6768 | 0.7173 |
+#> |.....................| 1.512 | 0.9502 | 0.7208 | 1.940 |
+#> | F| Forward Diff. | 2.102 | 0.4867 | 0.07498 | 0.004893 |
+#> |.....................| -0.2442 | 0.5250 | -1.879 | -0.1740 |
+#> |.....................| -0.3775 | -0.5383 | -0.4109 | -1.255 |
+#> |.....................| -1.562 | -0.4584 | -0.4426 | -0.7882 |
+#> | 79| 467.18237 | 1.007 | -1.558 | -0.9574 | -0.8544 |
+#> |.....................| -1.065 | -1.226 | 1.465 | -1.647 |
+#> |.....................| -0.8177 | -0.7470 | -0.9510 | -1.074 |
+#> |.....................| -0.5912 | -0.8859 | -1.035 | -0.2717 |
+#> | U| 467.18237 | 92.12 | -5.747 | -0.9286 | -2.106 |
+#> |.....................| -4.707 | 0.3016 | 1.797 | 0.03591 |
+#> |.....................| 0.8519 | 0.06186 | 0.6761 | 0.7177 |
+#> |.....................| 1.513 | 0.9501 | 0.7212 | 1.940 |
+#> | X| 467.18237 | 92.12 | 0.003193 | 0.2832 | 0.1217 |
+#> |.....................| 0.009031 | 0.5748 | 1.797 | 0.03591 |
+#> |.....................| 0.8519 | 0.06186 | 0.6761 | 0.7177 |
+#> |.....................| 1.513 | 0.9501 | 0.7212 | 1.940 |
+#> | F| Forward Diff. | -4.940 | 0.4761 | 0.03110 | 0.006161 |
+#> |.....................| -0.2415 | 0.4988 | -1.880 | -0.2651 |
+#> |.....................| -0.3787 | -0.5263 | -0.4799 | -1.241 |
+#> |.....................| -1.481 | -0.4641 | -0.4124 | -0.7761 |
+#> | 80| 467.17113 | 1.008 | -1.561 | -0.9574 | -0.8542 |
+#> |.....................| -1.062 | -1.228 | 1.469 | -1.648 |
+#> |.....................| -0.8192 | -0.7442 | -0.9515 | -1.074 |
+#> |.....................| -0.5909 | -0.8858 | -1.034 | -0.2714 |
+#> | U| 467.17113 | 92.19 | -5.749 | -0.9286 | -2.106 |
+#> |.....................| -4.704 | 0.3008 | 1.799 | 0.03586 |
+#> |.....................| 0.8513 | 0.06194 | 0.6757 | 0.7179 |
+#> |.....................| 1.514 | 0.9502 | 0.7215 | 1.941 |
+#> | X| 467.17113 | 92.19 | 0.003185 | 0.2832 | 0.1217 |
+#> |.....................| 0.009056 | 0.5746 | 1.799 | 0.03586 |
+#> |.....................| 0.8513 | 0.06194 | 0.6757 | 0.7179 |
+#> |.....................| 1.514 | 0.9502 | 0.7215 | 1.941 |
+#> | 81| 467.15723 | 1.008 | -1.564 | -0.9575 | -0.8538 |
+#> |.....................| -1.058 | -1.230 | 1.473 | -1.651 |
+#> |.....................| -0.8215 | -0.7400 | -0.9524 | -1.074 |
+#> |.....................| -0.5906 | -0.8857 | -1.034 | -0.2712 |
+#> | U| 467.15723 | 92.19 | -5.753 | -0.9287 | -2.106 |
+#> |.....................| -4.700 | 0.2996 | 1.800 | 0.03578 |
+#> |.....................| 0.8504 | 0.06206 | 0.6750 | 0.7179 |
+#> |.....................| 1.514 | 0.9503 | 0.7219 | 1.941 |
+#> | X| 467.15723 | 92.19 | 0.003173 | 0.2832 | 0.1218 |
+#> |.....................| 0.009093 | 0.5743 | 1.800 | 0.03578 |
+#> |.....................| 0.8504 | 0.06206 | 0.6750 | 0.7179 |
+#> |.....................| 1.514 | 0.9503 | 0.7219 | 1.941 |
+#> | 82| 467.09153 | 1.008 | -1.583 | -0.9578 | -0.8521 |
+#> |.....................| -1.038 | -1.244 | 1.497 | -1.664 |
+#> |.....................| -0.8331 | -0.7187 | -0.9572 | -1.074 |
+#> |.....................| -0.5894 | -0.8854 | -1.031 | -0.2699 |
+#> | U| 467.09153 | 92.20 | -5.772 | -0.9290 | -2.104 |
+#> |.....................| -4.680 | 0.2934 | 1.810 | 0.03540 |
+#> |.....................| 0.8456 | 0.06268 | 0.6715 | 0.7181 |
+#> |.....................| 1.516 | 0.9506 | 0.7239 | 1.943 |
+#> | X| 467.09153 | 92.20 | 0.003114 | 0.2831 | 0.1220 |
+#> |.....................| 0.009282 | 0.5728 | 1.810 | 0.03540 |
+#> |.....................| 0.8456 | 0.06268 | 0.6715 | 0.7181 |
+#> |.....................| 1.516 | 0.9506 | 0.7239 | 1.943 |
+#> | 83| 466.89701 | 1.009 | -1.658 | -0.9591 | -0.8451 |
+#> |.....................| -0.9556 | -1.297 | 1.590 | -1.717 |
+#> |.....................| -0.8794 | -0.6338 | -0.9760 | -1.073 |
+#> |.....................| -0.5844 | -0.8840 | -1.022 | -0.2647 |
+#> | U| 466.89701 | 92.27 | -5.846 | -0.9301 | -2.097 |
+#> |.....................| -4.598 | 0.2688 | 1.849 | 0.03388 |
+#> |.....................| 0.8264 | 0.06513 | 0.6578 | 0.7186 |
+#> |.....................| 1.521 | 0.9519 | 0.7320 | 1.949 |
+#> | X| 466.89701 | 92.27 | 0.002890 | 0.2829 | 0.1228 |
+#> |.....................| 0.01008 | 0.5668 | 1.849 | 0.03388 |
+#> |.....................| 0.8264 | 0.06513 | 0.6578 | 0.7186 |
+#> |.....................| 1.521 | 0.9519 | 0.7320 | 1.949 |
+#> | 84| 466.81525 | 1.010 | -1.758 | -0.9608 | -0.8357 |
+#> |.....................| -0.8455 | -1.369 | 1.715 | -1.787 |
+#> |.....................| -0.9414 | -0.5201 | -1.001 | -1.072 |
+#> |.....................| -0.5775 | -0.8822 | -1.009 | -0.2576 |
+#> | U| 466.81525 | 92.41 | -5.946 | -0.9316 | -2.087 |
+#> |.....................| -4.488 | 0.2358 | 1.901 | 0.03185 |
+#> |.....................| 0.8007 | 0.06841 | 0.6394 | 0.7195 |
+#> |.....................| 1.530 | 0.9537 | 0.7428 | 1.958 |
+#> | X| 466.81525 | 92.41 | 0.002615 | 0.2826 | 0.1240 |
+#> |.....................| 0.01125 | 0.5587 | 1.901 | 0.03185 |
+#> |.....................| 0.8007 | 0.06841 | 0.6394 | 0.7195 |
+#> |.....................| 1.530 | 0.9537 | 0.7428 | 1.958 |
+#> | F| Forward Diff. | 1.005 | 0.03859 | 0.3281 | -0.1495 |
+#> |.....................| 0.1126 | -0.4190 | -0.9638 | -1.159 |
+#> |.....................| -0.4187 | -0.1084 | -1.236 | 1.865 |
+#> |.....................| -0.3960 | -0.4043 | -0.1671 | 0.1635 |
+#> | 85| 467.22945 | 1.009 | -1.931 | -1.059 | -0.7851 |
+#> |.....................| -0.6667 | -1.418 | 1.962 | -1.804 |
+#> |.....................| -1.038 | -0.3298 | -0.7816 | -1.157 |
+#> |.....................| -0.5368 | -0.8226 | -0.9633 | -0.3812 |
+#> | U| 467.22945 | 92.33 | -6.120 | -1.019 | -2.037 |
+#> |.....................| -4.309 | 0.2137 | 2.003 | 0.03136 |
+#> |.....................| 0.7606 | 0.07390 | 0.7997 | 0.6429 |
+#> |.....................| 1.578 | 1.011 | 0.7823 | 1.807 |
+#> | X| 467.22945 | 92.33 | 0.002199 | 0.2652 | 0.1304 |
+#> |.....................| 0.01345 | 0.5532 | 2.003 | 0.03136 |
+#> |.....................| 0.7606 | 0.07390 | 0.7997 | 0.6429 |
+#> |.....................| 1.578 | 1.011 | 0.7823 | 1.807 |
+#> | 86| 466.68655 | 1.009 | -1.812 | -0.9919 | -0.8198 |
+#> |.....................| -0.7896 | -1.384 | 1.793 | -1.792 |
+#> |.....................| -0.9716 | -0.4604 | -0.9317 | -1.100 |
+#> |.....................| -0.5645 | -0.8633 | -0.9948 | -0.2964 |
+#> | U| 466.68655 | 92.33 | -6.001 | -0.9592 | -2.072 |
+#> |.....................| -4.432 | 0.2290 | 1.933 | 0.03172 |
+#> |.....................| 0.7883 | 0.07013 | 0.6901 | 0.6945 |
+#> |.....................| 1.545 | 0.9719 | 0.7553 | 1.910 |
+#> | X| 466.68655 | 92.33 | 0.002477 | 0.2770 | 0.1260 |
+#> |.....................| 0.01190 | 0.5570 | 1.933 | 0.03172 |
+#> |.....................| 0.7883 | 0.07013 | 0.6901 | 0.6945 |
+#> |.....................| 1.545 | 0.9719 | 0.7553 | 1.910 |
+#> | F| Forward Diff. | -11.18 | 0.05254 | -0.8763 | -0.07569 |
+#> |.....................| 0.1998 | -0.2059 | -0.4605 | -0.7124 |
+#> |.....................| -0.3271 | 0.07217 | 0.9692 | 1.710 |
+#> |.....................| -0.7229 | 0.7265 | 0.2517 | -0.09129 |
+#> | 87| 466.82655 | 1.009 | -1.865 | -0.9192 | -0.7946 |
+#> |.....................| -0.7769 | -1.362 | 1.859 | -1.827 |
+#> |.....................| -0.9838 | -0.4392 | -0.9155 | -1.146 |
+#> |.....................| -0.4995 | -0.8511 | -1.000 | -0.3560 |
+#> | U| 466.82655 | 92.34 | -6.054 | -0.8947 | -2.046 |
+#> |.....................| -4.419 | 0.2394 | 1.960 | 0.03072 |
+#> |.....................| 0.7832 | 0.07074 | 0.7019 | 0.6527 |
+#> |.....................| 1.622 | 0.9836 | 0.7506 | 1.838 |
+#> | X| 466.82655 | 92.34 | 0.002349 | 0.2901 | 0.1292 |
+#> |.....................| 0.01205 | 0.5596 | 1.960 | 0.03072 |
+#> |.....................| 0.7832 | 0.07074 | 0.7019 | 0.6527 |
+#> |.....................| 1.622 | 0.9836 | 0.7506 | 1.838 |
+#> | 88| 466.65072 | 1.010 | -1.827 | -0.9719 | -0.8129 |
+#> |.....................| -0.7861 | -1.378 | 1.811 | -1.801 |
+#> |.....................| -0.9749 | -0.4546 | -0.9274 | -1.113 |
+#> |.....................| -0.5467 | -0.8600 | -0.9963 | -0.3127 |
+#> | U| 466.65072 | 92.43 | -6.015 | -0.9415 | -2.065 |
+#> |.....................| -4.428 | 0.2318 | 1.940 | 0.03144 |
+#> |.....................| 0.7869 | 0.07030 | 0.6933 | 0.6830 |
+#> |.....................| 1.566 | 0.9750 | 0.7540 | 1.891 |
+#> | X| 466.65072 | 92.43 | 0.002441 | 0.2806 | 0.1269 |
+#> |.....................| 0.01194 | 0.5577 | 1.940 | 0.03144 |
+#> |.....................| 0.7869 | 0.07030 | 0.6933 | 0.6830 |
+#> |.....................| 1.566 | 0.9750 | 0.7540 | 1.891 |
+#> | F| Forward Diff. | -1.340 | 0.07863 | 0.1180 | -0.03302 |
+#> |.....................| 0.1973 | -0.03638 | -0.4314 | -0.7320 |
+#> |.....................| -0.3719 | 0.04356 | 0.7597 | 1.009 |
+#> |.....................| 0.3079 | 0.4883 | -0.4019 | -0.3069 |
+#> | 89| 466.64054 | 1.012 | -1.843 | -0.9769 | -0.8069 |
+#> |.....................| -0.7968 | -1.376 | 1.833 | -1.786 |
+#> |.....................| -0.9571 | -0.4600 | -0.9463 | -1.118 |
+#> |.....................| -0.5553 | -0.8554 | -0.9954 | -0.3119 |
+#> | U| 466.64054 | 92.56 | -6.031 | -0.9459 | -2.059 |
+#> |.....................| -4.439 | 0.2329 | 1.949 | 0.03189 |
+#> |.....................| 0.7943 | 0.07014 | 0.6795 | 0.6783 |
+#> |.....................| 1.556 | 0.9795 | 0.7548 | 1.892 |
+#> | X| 466.64054 | 92.56 | 0.002403 | 0.2797 | 0.1276 |
+#> |.....................| 0.01181 | 0.5580 | 1.949 | 0.03189 |
+#> |.....................| 0.7943 | 0.07014 | 0.6795 | 0.6783 |
+#> |.....................| 1.556 | 0.9795 | 0.7548 | 1.892 |
+#> | F| Forward Diff. | 13.35 | 0.06546 | -0.02976 | 0.01632 |
+#> |.....................| 0.1680 | -0.06031 | -0.2101 | 0.2297 |
+#> |.....................| -0.01975 | 0.1913 | 0.1108 | 0.6100 |
+#> |.....................| -0.008263 | 1.320 | 0.06198 | -0.2490 |
+#> | 90| 466.63994 | 1.010 | -1.856 | -0.9836 | -0.8023 |
+#> |.....................| -0.8121 | -1.369 | 1.859 | -1.781 |
+#> |.....................| -0.9548 | -0.4699 | -0.9506 | -1.117 |
+#> |.....................| -0.5644 | -0.8726 | -1.009 | -0.3176 |
+#> | U| 466.63994 | 92.43 | -6.045 | -0.9518 | -2.054 |
+#> |.....................| -4.454 | 0.2360 | 1.960 | 0.03203 |
+#> |.....................| 0.7952 | 0.06986 | 0.6763 | 0.6795 |
+#> |.....................| 1.545 | 0.9629 | 0.7430 | 1.885 |
+#> | X| 466.63994 | 92.43 | 0.002371 | 0.2785 | 0.1282 |
+#> |.....................| 0.01163 | 0.5587 | 1.960 | 0.03203 |
+#> |.....................| 0.7952 | 0.06986 | 0.6763 | 0.6795 |
+#> |.....................| 1.545 | 0.9629 | 0.7430 | 1.885 |
+#> | F| Forward Diff. | 0.1431 | 0.02593 | -0.4247 | 0.08835 |
+#> |.....................| 0.1490 | -0.08497 | 0.03702 | 0.4153 |
+#> |.....................| -0.04754 | 0.2015 | 0.06787 | -0.3581 |
+#> |.....................| -0.4069 | 0.09362 | -0.9227 | -0.5264 |
+#> | 91| 466.65402 | 1.008 | -1.856 | -0.9767 | -0.8037 |
+#> |.....................| -0.8145 | -1.367 | 1.858 | -1.788 |
+#> |.....................| -0.9540 | -0.4731 | -0.9517 | -1.111 |
+#> |.....................| -0.5579 | -0.8741 | -0.9943 | -0.3092 |
+#> | U| 466.65402 | 92.22 | -6.045 | -0.9458 | -2.055 |
+#> |.....................| -4.457 | 0.2367 | 1.960 | 0.03184 |
+#> |.....................| 0.7955 | 0.06976 | 0.6755 | 0.6846 |
+#> |.....................| 1.553 | 0.9615 | 0.7557 | 1.895 |
+#> | X| 466.65402 | 92.22 | 0.002370 | 0.2797 | 0.1280 |
+#> |.....................| 0.01160 | 0.5589 | 1.960 | 0.03184 |
+#> |.....................| 0.7955 | 0.06976 | 0.6755 | 0.6846 |
+#> |.....................| 1.553 | 0.9615 | 0.7557 | 1.895 |
+#> | 92| 466.63541 | 1.010 | -1.856 | -0.9812 | -0.8028 |
+#> |.....................| -0.8129 | -1.368 | 1.858 | -1.783 |
+#> |.....................| -0.9545 | -0.4710 | -0.9509 | -1.115 |
+#> |.....................| -0.5622 | -0.8731 | -1.004 | -0.3147 |
+#> | U| 466.63541 | 92.36 | -6.045 | -0.9498 | -2.055 |
+#> |.....................| -4.455 | 0.2363 | 1.960 | 0.03197 |
+#> |.....................| 0.7953 | 0.06982 | 0.6761 | 0.6812 |
+#> |.....................| 1.548 | 0.9624 | 0.7474 | 1.888 |
+#> | X| 466.63541 | 92.36 | 0.002371 | 0.2789 | 0.1281 |
+#> |.....................| 0.01162 | 0.5588 | 1.960 | 0.03197 |
+#> |.....................| 0.7953 | 0.06982 | 0.6761 | 0.6812 |
+#> |.....................| 1.548 | 0.9624 | 0.7474 | 1.888 |
+#> | F| Forward Diff. | -7.597 | 0.01585 | -0.3721 | 0.09081 |
+#> |.....................| 0.1473 | -0.05128 | 0.01723 | 0.2650 |
+#> |.....................| -0.04930 | 0.2121 | 0.3911 | -0.1952 |
+#> |.....................| -0.2951 | 0.01195 | -0.4116 | -0.4404 |
+#> | 93| 466.62967 | 1.010 | -1.857 | -0.9822 | -0.8038 |
+#> |.....................| -0.8179 | -1.367 | 1.859 | -1.785 |
+#> |.....................| -0.9524 | -0.4748 | -0.9515 | -1.114 |
+#> |.....................| -0.5617 | -0.8740 | -1.004 | -0.3130 |
+#> | U| 466.62967 | 92.43 | -6.045 | -0.9507 | -2.056 |
+#> |.....................| -4.460 | 0.2370 | 1.960 | 0.03192 |
+#> |.....................| 0.7962 | 0.06971 | 0.6756 | 0.6815 |
+#> |.....................| 1.548 | 0.9616 | 0.7476 | 1.890 |
+#> | X| 466.62967 | 92.43 | 0.002369 | 0.2787 | 0.1280 |
+#> |.....................| 0.01156 | 0.5590 | 1.960 | 0.03192 |
+#> |.....................| 0.7962 | 0.06971 | 0.6756 | 0.6815 |
+#> |.....................| 1.548 | 0.9616 | 0.7476 | 1.890 |
+#> | F| Forward Diff. | 0.1737 | 0.01712 | -0.3712 | 0.07555 |
+#> |.....................| 0.1320 | -0.03330 | -0.1756 | 0.3015 |
+#> |.....................| -0.06297 | 0.1717 | 0.09645 | -0.1674 |
+#> |.....................| -0.2756 | -0.01624 | -0.3459 | -0.4307 |
+#> | 94| 466.62779 | 1.010 | -1.856 | -0.9797 | -0.8047 |
+#> |.....................| -0.8221 | -1.366 | 1.862 | -1.786 |
+#> |.....................| -0.9500 | -0.4779 | -0.9517 | -1.113 |
+#> |.....................| -0.5623 | -0.8742 | -1.003 | -0.3111 |
+#> | U| 466.62779 | 92.40 | -6.045 | -0.9484 | -2.056 |
+#> |.....................| -4.464 | 0.2375 | 1.961 | 0.03188 |
+#> |.....................| 0.7972 | 0.06963 | 0.6755 | 0.6823 |
+#> |.....................| 1.548 | 0.9614 | 0.7480 | 1.893 |
+#> | X| 466.62779 | 92.40 | 0.002370 | 0.2792 | 0.1279 |
+#> |.....................| 0.01152 | 0.5591 | 1.961 | 0.03188 |
+#> |.....................| 0.7972 | 0.06963 | 0.6755 | 0.6823 |
+#> |.....................| 1.548 | 0.9614 | 0.7480 | 1.893 |
+#> | F| Forward Diff. | -2.926 | 0.01199 | -0.2808 | 0.07297 |
+#> |.....................| 0.1250 | -0.02504 | 0.02207 | 0.2419 |
+#> |.....................| -0.03068 | 0.1983 | 0.3271 | -0.08125 |
+#> |.....................| -0.2841 | -0.05347 | -0.2873 | -0.3919 |
+#> | 95| 466.62386 | 1.010 | -1.856 | -0.9811 | -0.8057 |
+#> |.....................| -0.8267 | -1.365 | 1.862 | -1.788 |
+#> |.....................| -0.9479 | -0.4822 | -0.9526 | -1.114 |
+#> |.....................| -0.5610 | -0.8741 | -1.003 | -0.3093 |
+#> | U| 466.62386 | 92.43 | -6.045 | -0.9497 | -2.057 |
+#> |.....................| -4.469 | 0.2377 | 1.961 | 0.03183 |
+#> |.....................| 0.7980 | 0.06950 | 0.6749 | 0.6820 |
+#> |.....................| 1.549 | 0.9614 | 0.7483 | 1.895 |
+#> | X| 466.62386 | 92.43 | 0.002370 | 0.2789 | 0.1278 |
+#> |.....................| 0.01146 | 0.5592 | 1.961 | 0.03183 |
+#> |.....................| 0.7980 | 0.06950 | 0.6749 | 0.6820 |
+#> |.....................| 1.549 | 0.9614 | 0.7483 | 1.895 |
+#> | F| Forward Diff. | 0.1137 | 0.01564 | -0.3265 | 0.06191 |
+#> |.....................| 0.1094 | -0.02529 | 0.01125 | 0.2123 |
+#> |.....................| -0.07598 | 0.1365 | 0.2003 | -0.1363 |
+#> |.....................| -0.2276 | -0.05501 | -0.2526 | -0.4116 |
+#> | 96| 466.62386 | 1.010 | -1.856 | -0.9811 | -0.8057 |
+#> |.....................| -0.8267 | -1.365 | 1.862 | -1.788 |
+#> |.....................| -0.9479 | -0.4822 | -0.9526 | -1.114 |
+#> |.....................| -0.5610 | -0.8741 | -1.003 | -0.3093 |
+#> | U| 466.62386 | 92.43 | -6.045 | -0.9497 | -2.057 |
+#> |.....................| -4.469 | 0.2377 | 1.961 | 0.03183 |
+#> |.....................| 0.7980 | 0.06950 | 0.6749 | 0.6820 |
+#> |.....................| 1.549 | 0.9614 | 0.7483 | 1.895 |
+#> | X| 466.62386 | 92.43 | 0.002370 | 0.2789 | 0.1278 |
+#> |.....................| 0.01146 | 0.5592 | 1.961 | 0.03183 |
+#> |.....................| 0.7980 | 0.06950 | 0.6749 | 0.6820 |
+#> |.....................| 1.549 | 0.9614 | 0.7483 | 1.895 |
+#> calculating covariance matrix
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Error in AIC(f_nlmixr_sfo_sfo_focei_const$nm, f_nlmixr_fomc_sfo_focei_const$nm, f_nlmixr_dfop_sfo_focei_const$nm, f_nlmixr_fomc_sfo_saem_obs$nm, f_nlmixr_fomc_sfo_focei_obs$nm, f_nlmixr_dfop_sfo_saem_obs$nm, f_nlmixr_dfop_sfo_focei_obs$nm, f_nlmixr_fomc_sfo_focei_tc$nm, f_nlmixr_dfop_sfo_focei_tc$nm, f_nlmixr_fomc_sfo_saem_obs_tc$nm, f_nlmixr_fomc_sfo_focei_obs_tc$nm, f_nlmixr_dfop_sfo_saem_obs_tc$nm, f_nlmixr_dfop_sfo_focei_obs_tc$nm): object 'f_nlmixr_sfo_sfo_focei_const' not found
# Currently, FOMC-SFO with two-component error by variable fitted by focei gives the
+
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> df AIC
+#> f_nlmixr_sfo_sfo_focei_const$nm 9 1082.4868
+#> f_nlmixr_fomc_sfo_focei_const$nm 11 814.4317
+#> f_nlmixr_dfop_sfo_focei_const$nm 13 866.0485
+#> f_nlmixr_fomc_sfo_saem_obs$nm 12 791.7256
+#> f_nlmixr_fomc_sfo_focei_obs$nm 12 794.5998
+#> f_nlmixr_dfop_sfo_saem_obs$nm 14 812.0463
+#> f_nlmixr_dfop_sfo_focei_obs$nm 14 846.9228
+#> f_nlmixr_fomc_sfo_focei_tc$nm 12 812.3585
+#> f_nlmixr_dfop_sfo_focei_tc$nm 14 842.3479
+#> f_nlmixr_fomc_sfo_saem_obs_tc$nm 14 817.1261
+#> f_nlmixr_fomc_sfo_focei_obs_tc$nm 14 787.4863
+#> f_nlmixr_dfop_sfo_saem_obs_tc$nm 16 858.3213
+#> f_nlmixr_dfop_sfo_focei_obs_tc$nm 16 811.0630
#> Error in plot(f_nlmixr_fomc_sfo_focei_obs_tc): object 'f_nlmixr_fomc_sfo_focei_obs_tc' not found
#> Error in summary(f_nlmixr_fomc_sfo_focei_obs_tc): object 'f_nlmixr_fomc_sfo_focei_obs_tc' not found
# }
+
![](nlmixr.mmkin-2.png)
#> nlmixr version used for fitting: 2.0.5
+#> mkin version used for pre-fitting: 1.1.0
+#> R version used for fitting: 4.1.1
+#> Date of fit: Tue Oct 5 17:25:02 2021
+#> Date of summary: Tue Oct 5 17:26:23 2021
+#>
+#> Equations:
+#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
+#> d_A1/dt = + f_parent_to_A1 * (alpha/beta) * 1/((time/beta) + 1) *
+#> parent - k_A1 * A1
+#>
+#> Data:
+#> 170 observations of 2 variable(s) grouped in 5 datasets
+#>
+#> Degradation model predictions using RxODE
+#>
+#> Fitted in 24.31 s
+#>
+#> Variance model: Two-component variance unique to each observed variable
+#>
+#> Mean of starting values for individual parameters:
+#> parent_0 log_k_A1 f_parent_qlogis log_alpha log_beta
+#> 93.1168 -5.3034 -0.9442 -0.1065 2.2909
+#>
+#> Mean of starting values for error model parameters:
+#> sigma_low_parent rsd_high_parent sigma_low_A1 rsd_high_A1
+#> 1.15958 0.03005 1.15958 0.03005
+#>
+#> Fixed degradation parameter values:
+#> None
+#>
+#> Results:
+#>
+#> Likelihood calculated by focei
+#> AIC BIC logLik
+#> 787.5 831.4 -379.7
+#>
+#> Optimised parameters:
+#> est. lower upper
+#> parent_0 93.6898 91.2681 96.1114
+#> log_k_A1 -6.2923 -8.3662 -4.2185
+#> f_parent_qlogis -1.0019 -1.3760 -0.6278
+#> log_alpha -0.1639 -0.6641 0.3363
+#> log_beta 2.2031 1.6723 2.7340
+#>
+#> Correlation:
+#> prnt_0 lg__A1 f_prn_ lg_lph
+#> log_k_A1 0.368
+#> f_parent_qlogis -0.788 -0.401
+#> log_alpha 0.338 0.942 -0.307
+#> log_beta -0.401 -0.761 0.253 -0.555
+#>
+#> Random effects (omega):
+#> eta.parent_0 eta.log_k_A1 eta.f_parent_qlogis eta.log_alpha
+#> eta.parent_0 4.74 0.00 0.0000 0.0000
+#> eta.log_k_A1 0.00 5.57 0.0000 0.0000
+#> eta.f_parent_qlogis 0.00 0.00 0.1646 0.0000
+#> eta.log_alpha 0.00 0.00 0.0000 0.3312
+#> eta.log_beta 0.00 0.00 0.0000 0.0000
+#> eta.log_beta
+#> eta.parent_0 0.0000
+#> eta.log_k_A1 0.0000
+#> eta.f_parent_qlogis 0.0000
+#> eta.log_alpha 0.0000
+#> eta.log_beta 0.3438
+#>
+#> Variance model:
+#> sigma_low_parent rsd_high_parent sigma_low_A1 rsd_high_A1
+#> 2.35467 0.00261 0.64525 0.08456
+#>
+#> Backtransformed parameters:
+#> est. lower upper
+#> parent_0 93.68976 9.127e+01 96.11140
+#> k_A1 0.00185 2.326e-04 0.01472
+#> f_parent_to_A1 0.26857 2.017e-01 0.34801
+#> alpha 0.84879 5.147e-01 1.39971
+#> beta 9.05342 5.325e+00 15.39359
+#>
+#> Resulting formation fractions:
+#> ff
+#> parent_A1 0.2686
+#> parent_sink 0.7314
+#>
+#> Estimated disappearance times:
+#> DT50 DT90 DT50back
+#> parent 11.43 127.4 38.35
+#> A1 374.59 1244.4 NA
# }
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> RxODE 1.1.1 using 8 threads (see ?getRxThreads)
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> RxODE 1.1.2 using 8 threads (see ?getRxThreads)
#> no cache: create with `rxCreateCache()`
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> calculating covariance matrix
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using S matrix to calculate covariance, can check sandwich or R matrix with $covRS and $covR
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Calculating residuals/tables
#> done
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> df AIC
-#> f_nlmixr_sfo_saem$nm 5 627.9197
-#> f_nlmixr_sfo_focei$nm 5 625.0512
-#> f_nlmixr_fomc_saem$nm 7 463.7245
-#> f_nlmixr_fomc_focei$nm 7 468.0822
-#> f_nlmixr_dfop_saem$nm 9 518.5794
-#> f_nlmixr_dfop_focei$nm 9 537.6309
-#> f_nlmixr_hs_saem$nm 9 535.9011
-#> f_nlmixr_hs_focei$nm 9 544.7590
-#> f_nlmixr_fomc_saem_tc$nm 8 463.5871
-#> f_nlmixr_fomc_focei_tc$nm 8 470.0733
+#> f_nlmixr_sfo_saem$nm 5 624.9492
+#> f_nlmixr_sfo_focei$nm 5 625.0695
+#> f_nlmixr_fomc_saem$nm 7 463.7577
+#> f_nlmixr_fomc_focei$nm 7 468.0861
+#> f_nlmixr_dfop_saem$nm 9 495.1980
+#> f_nlmixr_dfop_focei$nm 9 495.1072
+#> f_nlmixr_hs_saem$nm 9 531.0689
+#> f_nlmixr_hs_focei$nm 9 545.6728
+#> f_nlmixr_fomc_saem_tc$nm 8 462.1411
+#> f_nlmixr_fomc_focei_tc$nm 8 470.0745
#> [1] 468.0781
#> [1] 535.609
#> function ()
#> {
#> ini({
-#> parent_0 = 86.5344031312703
-#> eta.parent_0 ~ 4.15825368312402
-#> log_k_parent = -3.20701116105339
-#> eta.log_k_parent ~ 1.51881531595261
-#> log_k_A1 = -4.56730447776105
-#> eta.log_k_A1 ~ 0.560590264281928
-#> f_parent_qlogis = -0.334081143921924
-#> eta.f_parent_qlogis ~ 1.14983591785967
-#> sigma_parent = 4.31472323222676
-#> sigma_A1 = 4.31472323222676
+#> parent_0 = 87
+#> eta.parent_0 ~ 4.2
+#> log_k_parent = -3.2
+#> eta.log_k_parent ~ 1.5
+#> log_k_A1 = -4.6
+#> eta.log_k_A1 ~ 0.56
+#> f_parent_qlogis = -0.33
+#> eta.f_parent_qlogis ~ 1.1
+#> sigma_parent = 4.3
+#> sigma_A1 = 4.3
#> })
#> model({
#> parent_0_model = parent_0 + eta.parent_0
@@ -396,7 +396,7 @@ obtained by fitting the same model to a list of datasets using
+#> <environment: 0x55556675b428>#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.6104 -5.6552 -0.1308 2.1755 -1.1174 2.9315 1.6064 0.6616 0.5897 0.4753 9.7765 10.2253
-#> 2: 93.8838 -5.6936 -0.1062 2.2361 -1.0529 2.7849 1.5260 0.6285 0.5602 0.4515 7.9206 5.2721
-#> 3: 93.9304 -5.7260 -0.0940 2.2480 -1.0317 2.6457 1.4889 0.5971 0.5322 0.4290 7.5051 3.6573
-#> 4: 93.6107 -5.7914 -0.0929 2.2382 -1.0171 2.5134 2.0027 0.5676 0.5056 0.4075 7.3763 3.1438
-#> 5: 93.7262 -5.7517 -0.0926 2.2365 -1.0306 2.3877 1.9026 0.5679 0.4803 0.3871 7.2914 3.0275
-#> 6: 93.7261 -5.7719 -0.0823 2.2625 -1.0391 2.2683 2.1168 0.5638 0.4563 0.3678 7.0857 2.8196
-#> 7: 93.5991 -5.8553 -0.0917 2.2659 -1.0146 2.1549 2.3708 0.5618 0.4335 0.3494 6.9413 2.7447
-#> 8: 93.4288 -5.8969 -0.0885 2.2757 -1.0253 2.1183 2.4324 0.5615 0.4118 0.3319 7.2269 2.6781
-#> 9: 93.4049 -6.1188 -0.0863 2.2841 -1.0154 2.0124 3.0090 0.5633 0.3912 0.3153 7.2084 2.7464
-#> 10: 93.4773 -6.1940 -0.0816 2.2893 -1.0174 1.9958 3.6308 0.5540 0.3716 0.2996 7.2414 2.8980
-#> 11: 93.5334 -6.1739 -0.0772 2.2901 -1.0479 2.2841 3.4492 0.5567 0.3531 0.2846 7.0567 2.8159
-#> 12: 93.5824 -6.3716 -0.0875 2.2706 -1.0452 2.1699 4.3087 0.5505 0.3354 0.2704 7.2970 2.3790
-#> 13: 93.8528 -6.3302 -0.0846 2.2564 -1.0302 2.0614 4.6014 0.5475 0.3186 0.2568 7.3901 2.1942
-#> 14: 94.0343 -6.1408 -0.0887 2.2666 -1.0280 1.9995 4.3714 0.5202 0.3027 0.2440 7.1696 2.0730
-#> 15: 94.1712 -6.3900 -0.0759 2.2825 -1.0112 1.8995 5.0913 0.5358 0.2876 0.2318 7.2155 2.0259
-#> 16: 93.9481 -6.1284 -0.0798 2.2707 -1.0264 1.8046 4.8368 0.5501 0.2732 0.2202 7.2731 2.0912
-#> 17: 93.7828 -6.2736 -0.0852 2.2870 -1.0249 1.7143 4.5949 0.5408 0.2595 0.2092 7.0213 2.0417
-#> 18: 93.8758 -6.3616 -0.0851 2.2713 -1.0157 1.8699 4.9132 0.5349 0.2465 0.1987 7.0613 1.8601
-#> 19: 93.7565 -6.5413 -0.0866 2.2695 -1.0166 2.5251 5.9754 0.5312 0.2547 0.1888 7.2555 1.7947
-#> 20: 93.7233 -6.3942 -0.0970 2.2620 -1.0195 2.3989 5.6766 0.5484 0.2576 0.1794 7.0292 1.8687
-#> 21: 93.8298 -6.2619 -0.0974 2.2570 -1.0118 2.2789 5.3928 0.5497 0.2545 0.1704 6.7138 1.8157
-#> 22: 93.9520 -6.1633 -0.0874 2.2777 -1.0274 2.1650 5.1232 0.5437 0.2641 0.1622 6.8254 1.8443
-#> 23: 93.8442 -6.3255 -0.0855 2.2568 -1.0151 2.1243 4.9615 0.5334 0.2885 0.1556 6.8049 1.8073
-#> 24: 93.9659 -6.5470 -0.0855 2.2572 -1.0178 2.0788 6.2156 0.5425 0.2834 0.1583 6.9598 1.8686
-#> 25: 94.3004 -6.4881 -0.0920 2.2371 -1.0187 3.2507 5.9048 0.5367 0.2872 0.1609 6.8709 1.8839
-#> 26: 94.1750 -6.4437 -0.0964 2.2337 -1.0301 3.1136 5.6096 0.5307 0.2820 0.1611 6.5948 1.8742
-#> 27: 94.6007 -6.3072 -0.0750 2.2936 -1.0343 3.9844 5.3291 0.5042 0.2679 0.1695 6.7524 1.8335
-#> 28: 94.4915 -6.1389 -0.0826 2.2730 -1.0223 3.7852 5.0626 0.4998 0.2590 0.1812 6.4646 1.8937
-#> 29: 94.1900 -6.1516 -0.0836 2.2680 -1.0287 3.7861 4.8095 0.4976 0.2612 0.1875 6.4674 1.8998
-#> 30: 94.6632 -6.0574 -0.0773 2.2637 -1.0280 3.5968 4.5690 0.4948 0.2525 0.2040 6.5945 1.9022
-#> 31: 94.3460 -6.1684 -0.0761 2.2677 -1.0276 3.4170 4.3406 0.4901 0.2690 0.2038 6.9918 1.8446
-#> 32: 94.4385 -5.9347 -0.0751 2.2893 -1.0146 3.3283 4.1235 0.4882 0.2576 0.2002 6.7622 1.7754
-#> 33: 94.7021 -5.9329 -0.0787 2.2987 -1.0108 3.3485 3.9174 0.4859 0.2640 0.1941 6.9648 1.8014
-#> 34: 94.4058 -6.0311 -0.0692 2.2980 -1.0125 3.1811 3.7215 0.4994 0.2676 0.1936 6.9791 1.7561
-#> 35: 94.4503 -6.0470 -0.0692 2.2950 -1.0100 3.5600 3.7611 0.4994 0.2637 0.1928 6.8010 1.7890
-#> 36: 94.3400 -6.0339 -0.0792 2.2960 -1.0204 3.3820 3.5731 0.4822 0.2638 0.1887 6.6462 1.6763
-#> 37: 94.1497 -6.0221 -0.0879 2.2653 -1.0073 3.2129 3.3944 0.4979 0.2506 0.1793 6.4853 1.7911
-#> 38: 94.1574 -5.8638 -0.0884 2.2752 -1.0156 3.0523 3.2247 0.4992 0.2435 0.1772 6.4329 1.7707
-#> 39: 94.1680 -5.9558 -0.0948 2.2535 -1.0205 2.8997 3.0635 0.5065 0.2448 0.1819 6.4462 1.8100
-#> 40: 94.0516 -6.0814 -0.0881 2.2531 -1.0356 2.7547 3.4976 0.4949 0.2515 0.1827 6.4734 1.8133
-#> 41: 94.1522 -6.1880 -0.0849 2.2618 -1.0230 2.6170 4.1610 0.5129 0.2389 0.1797 6.4165 1.7782
-#> 42: 94.2178 -6.1829 -0.0854 2.2791 -1.0325 2.8092 4.1174 0.5052 0.2288 0.1853 6.4332 1.7883
-#> 43: 93.9083 -6.1600 -0.0831 2.2860 -1.0350 2.9631 3.9116 0.4914 0.2310 0.1826 6.4865 1.8449
-#> 44: 93.9636 -6.1494 -0.0824 2.2903 -1.0150 2.8149 3.7221 0.4921 0.2214 0.1805 6.4818 1.9385
-#> 45: 93.9937 -6.2329 -0.0895 2.2832 -1.0157 4.2815 4.5622 0.5075 0.2250 0.1796 6.4098 1.8355
-#> 46: 93.8001 -6.1784 -0.0944 2.2664 -1.0212 4.0674 4.3341 0.5023 0.2274 0.1795 6.5539 1.7875
-#> 47: 93.8997 -6.3400 -0.0945 2.2627 -1.0183 3.8641 4.9860 0.5017 0.2312 0.1834 6.5497 1.7838
-#> 48: 93.7861 -6.3496 -0.0944 2.2713 -1.0255 3.6709 5.3403 0.5025 0.2197 0.1839 6.1766 1.9080
-#> 49: 93.7128 -6.3914 -0.0944 2.2752 -1.0137 3.4873 5.6007 0.5051 0.2198 0.1788 6.3050 1.8320
-#> 50: 94.1645 -6.3056 -0.0945 2.2755 -1.0062 3.3130 5.3207 0.4998 0.2176 0.1781 6.4998 1.8516
-#> 51: 93.9897 -6.1556 -0.1026 2.2633 -1.0097 3.1473 5.0547 0.4853 0.2439 0.1796 6.3184 1.7981
-#> 52: 93.7604 -6.2264 -0.1068 2.2485 -0.9936 2.9899 4.8209 0.4887 0.2542 0.1793 6.5076 1.7916
-#> 53: 93.8821 -6.5447 -0.1049 2.2546 -1.0020 2.8404 6.5603 0.4701 0.2556 0.1789 6.5735 1.7763
-#> 54: 93.8865 -6.4028 -0.1081 2.2507 -1.0162 2.6984 6.2323 0.4724 0.2576 0.1846 6.3607 1.8295
-#> 55: 94.0120 -6.5455 -0.0986 2.2728 -1.0119 2.5635 6.3983 0.4550 0.2686 0.1773 6.6815 1.7869
-#> 56: 94.1921 -6.6581 -0.0953 2.2713 -1.0151 2.4353 8.2169 0.4478 0.2675 0.1763 6.6257 1.7873
-#> 57: 93.8812 -6.4499 -0.1081 2.2447 -1.0182 2.3136 7.8060 0.4683 0.2562 0.1804 6.2421 1.8455
-#> 58: 93.9830 -6.5112 -0.1092 2.2436 -1.0136 2.1979 7.4157 0.4695 0.2569 0.1762 6.3196 1.8224
-#> 59: 93.8537 -6.6528 -0.1105 2.2390 -1.0089 2.0880 9.0039 0.4689 0.2534 0.1692 6.3735 1.8049
-#> 60: 93.7399 -6.4780 -0.1212 2.2263 -0.9979 1.9836 8.5537 0.4565 0.2445 0.1696 6.4748 1.8439
-#> 61: 93.8180 -6.4608 -0.1243 2.2275 -1.0039 1.8844 8.1260 0.4630 0.2414 0.1693 6.3936 1.7653
-#> 62: 93.5774 -6.3127 -0.1298 2.2250 -1.0022 1.7902 7.7197 0.4711 0.2452 0.1708 6.5708 1.8014
-#> 63: 93.5731 -6.2060 -0.1327 2.2213 -1.0031 1.7007 7.3337 0.4685 0.2426 0.1712 6.4933 1.8318
-#> 64: 93.3587 -6.2299 -0.1316 2.2290 -1.0004 1.6302 6.9671 0.4694 0.2460 0.1710 6.2584 1.8361
-#> 65: 93.2982 -6.1900 -0.1354 2.2341 -0.9963 1.5487 6.6187 0.4685 0.2482 0.1750 6.0950 1.8341
-#> 66: 93.4532 -6.2107 -0.1251 2.2254 -0.9786 1.4713 6.2878 0.4822 0.2489 0.1701 6.3732 1.7951
-#> 67: 93.5878 -6.1823 -0.1208 2.2455 -0.9766 1.3977 5.9734 0.4860 0.2407 0.1668 6.4456 1.8371
-#> 68: 93.5819 -5.9209 -0.1200 2.2599 -0.9792 1.3278 5.6747 0.4793 0.2412 0.1686 6.5728 1.8144
-#> 69: 93.4002 -6.1142 -0.1242 2.2542 -0.9878 1.4433 5.3910 0.4730 0.2511 0.1830 6.3888 1.7900
-#> 70: 93.2631 -6.1875 -0.1271 2.2639 -0.9844 1.5244 5.1214 0.4711 0.2444 0.1770 6.5093 1.7117
-#> 71: 93.2629 -6.2944 -0.1275 2.2418 -0.9805 1.4481 4.8654 0.4612 0.2522 0.1748 6.4659 1.8500
-#> 72: 93.0324 -6.2727 -0.1332 2.2421 -0.9766 1.3757 5.1467 0.4519 0.2524 0.1673 6.3452 1.8054
-#> 73: 93.0174 -6.4402 -0.1391 2.2320 -0.9795 1.3069 6.1963 0.4480 0.2563 0.1637 6.3915 1.8506
-#> 74: 93.0073 -6.4286 -0.1450 2.2241 -0.9962 1.2416 6.0011 0.4510 0.2461 0.1682 6.6924 1.8302
-#> 75: 93.2607 -6.5056 -0.1379 2.2233 -0.9926 1.1795 6.0508 0.4573 0.2540 0.1669 6.4813 1.7896
-#> 76: 93.2937 -6.1637 -0.1404 2.2228 -0.9970 1.1205 5.7483 0.4588 0.2529 0.1656 6.3781 1.7976
-#> 77: 93.2223 -6.1702 -0.1381 2.2200 -0.9858 1.4369 5.4609 0.4633 0.2585 0.1697 6.3510 1.8749
-#> 78: 93.3189 -6.1924 -0.1355 2.2238 -0.9944 1.3651 5.1878 0.4608 0.2631 0.1612 6.1888 1.7669
-#> 79: 93.2417 -6.6345 -0.1335 2.2340 -0.9865 1.2968 7.3486 0.4570 0.2564 0.1532 6.0902 1.7505
-#> 80: 93.3476 -6.3069 -0.1305 2.2319 -0.9880 1.6281 6.9812 0.4649 0.2525 0.1514 6.0659 1.7582
-#> 81: 93.4798 -6.3145 -0.1253 2.2468 -0.9989 1.9108 6.6321 0.4447 0.2583 0.1579 6.0843 1.7959
-#> 82: 93.2745 -6.2461 -0.1184 2.2529 -0.9937 1.8153 6.3005 0.4439 0.2602 0.1691 6.2826 1.7896
-#> 83: 93.4628 -6.3953 -0.1189 2.2640 -0.9880 1.7245 6.1094 0.4430 0.2612 0.1709 6.4474 1.6820
-#> 84: 93.3664 -6.2885 -0.1105 2.2675 -0.9875 1.6383 6.1170 0.4498 0.2689 0.1719 6.4847 1.6731
-#> 85: 93.5090 -6.3029 -0.1095 2.2709 -0.9898 1.6666 6.1406 0.4365 0.2693 0.1710 6.2452 1.6594
-#> 86: 93.5097 -6.2256 -0.1106 2.2701 -0.9928 1.5833 6.2468 0.4365 0.2749 0.1632 6.2007 1.7178
-#> 87: 93.5165 -6.3038 -0.1046 2.2731 -0.9877 1.5041 5.9345 0.4398 0.2667 0.1603 6.3928 1.7003
-#> 88: 93.3766 -6.2723 -0.1071 2.2771 -0.9881 1.4289 5.6378 0.4241 0.2538 0.1598 6.1043 1.6772
-#> 89: 93.4448 -6.0430 -0.1102 2.2781 -0.9725 1.3575 5.3559 0.4187 0.2915 0.1518 6.0153 1.7593
-#> 90: 93.2843 -6.1065 -0.1089 2.2866 -0.9705 1.5362 5.0881 0.4203 0.2844 0.1656 5.9235 1.6631
-#> 91: 93.4159 -6.0210 -0.1095 2.2879 -0.9798 2.1371 4.8337 0.4245 0.2857 0.1573 5.9182 1.7482
-#> 92: 93.3198 -6.2526 -0.1075 2.2919 -0.9791 2.0303 4.7352 0.4159 0.2918 0.1590 6.0853 1.6755
-#> 93: 93.3269 -6.1838 -0.1173 2.2809 -0.9999 1.9287 4.4985 0.4211 0.2893 0.1684 6.1189 1.6734
-#> 94: 93.2077 -6.1086 -0.1148 2.2890 -0.9918 2.1061 4.2736 0.4230 0.2802 0.1662 5.9328 1.7116
-#> 95: 93.0207 -6.1510 -0.1170 2.2665 -0.9791 2.1360 4.0630 0.4199 0.2937 0.1734 6.1415 1.6737
-#> 96: 93.2134 -6.1614 -0.1152 2.2861 -0.9711 2.5372 4.1579 0.4211 0.2790 0.1647 6.1575 1.6338
-#> 97: 93.1425 -6.2333 -0.1140 2.2912 -0.9665 2.4103 4.4551 0.4136 0.2835 0.1645 6.0790 1.6652
-#> 98: 92.9412 -6.2651 -0.1167 2.2847 -0.9738 2.2898 4.7233 0.4095 0.2882 0.1836 5.9305 1.6158
-#> 99: 92.9087 -6.1870 -0.1177 2.2833 -0.9744 2.1753 4.4872 0.4142 0.2913 0.1876 5.9838 1.7003
-#> 100: 92.7788 -6.2113 -0.1146 2.2928 -0.9939 2.0665 4.4195 0.4109 0.2945 0.1866 6.0195 1.7275
-#> 101: 92.8783 -6.0718 -0.1080 2.2959 -0.9968 1.9632 4.1985 0.4142 0.2966 0.1778 6.2542 1.6844
-#> 102: 93.0451 -6.3706 -0.1086 2.2894 -0.9974 1.8650 5.2121 0.4135 0.3030 0.1769 6.2204 1.6281
-#> 103: 93.2901 -6.4069 -0.1066 2.2943 -0.9896 1.7718 5.7453 0.4152 0.2879 0.1818 6.0239 1.7299
-#> 104: 93.3437 -6.3694 -0.1063 2.2769 -0.9914 1.6832 5.8903 0.4210 0.2884 0.1855 6.1116 1.7415
-#> 105: 93.4609 -6.2767 -0.1060 2.2751 -1.0157 1.5990 5.5958 0.4214 0.2865 0.1841 6.1287 1.7322
-#> 106: 93.5833 -6.2340 -0.1006 2.2879 -1.0084 1.8669 5.3160 0.4272 0.2982 0.1829 6.0211 1.6726
-#> 107: 93.7800 -6.1505 -0.0948 2.2685 -1.0219 1.7735 5.0502 0.4325 0.2841 0.1753 5.8556 1.7636
-#> 108: 93.8532 -6.3744 -0.0938 2.2650 -1.0210 2.0297 5.7080 0.4307 0.2836 0.1701 6.0669 1.6804
-#> 109: 93.8994 -6.3544 -0.0829 2.2862 -1.0287 1.9282 5.4226 0.4184 0.3113 0.1789 6.2343 1.6667
-#> 110: 94.0150 -6.5609 -0.0905 2.2821 -1.0088 2.1118 6.8121 0.4276 0.3275 0.1845 6.1640 1.6706
-#> 111: 93.7887 -6.0185 -0.0925 2.2831 -1.0097 2.0062 6.4715 0.4209 0.3255 0.1852 6.2823 1.6301
-#> 112: 93.9709 -6.0918 -0.0934 2.2857 -1.0067 2.2032 6.1479 0.4207 0.3285 0.1817 6.1718 1.6494
-#> 113: 93.8761 -6.3434 -0.0955 2.2919 -1.0223 2.5209 5.8405 0.4259 0.3293 0.1842 6.0377 1.6431
-#> 114: 93.6959 -6.2312 -0.0934 2.2782 -1.0154 2.3949 5.5485 0.4237 0.3460 0.1814 6.2225 1.6229
-#> 115: 93.5487 -6.0915 -0.0971 2.2836 -1.0083 2.2751 5.2711 0.4199 0.3557 0.1783 6.5929 1.6479
-#> 116: 93.5953 -6.1479 -0.1013 2.2760 -1.0018 2.1614 5.0075 0.4163 0.3399 0.1794 6.1822 1.6222
-#> 117: 93.3508 -6.1730 -0.1076 2.2632 -0.9953 2.0533 4.7571 0.4057 0.3303 0.1803 6.3444 1.7106
-#> 118: 93.4462 -5.9724 -0.1177 2.2557 -0.9963 2.0318 4.5193 0.3956 0.3349 0.1920 6.0439 1.7146
-#> 119: 93.5841 -6.0400 -0.1151 2.2480 -1.0035 1.9956 4.2933 0.3968 0.3448 0.1929 6.0754 1.6750
-#> 120: 93.4891 -6.0937 -0.1175 2.2499 -1.0006 1.8958 4.0786 0.3927 0.3392 0.1927 6.1654 1.6495
-#> 121: 93.4611 -6.1371 -0.1217 2.2538 -1.0067 1.8011 3.8747 0.3864 0.3549 0.1851 5.9558 1.6940
-#> 122: 93.4636 -6.1015 -0.1243 2.2564 -1.0002 1.7414 3.6810 0.3840 0.3557 0.1860 6.0583 1.6629
-#> 123: 93.2988 -5.9318 -0.1243 2.2601 -0.9989 2.2063 3.4969 0.3840 0.3543 0.1833 5.9686 1.5966
-#> 124: 93.4200 -5.9847 -0.1231 2.2594 -0.9991 2.0959 3.3221 0.3846 0.3544 0.1787 6.1292 1.5957
-#> 125: 93.3727 -6.1217 -0.1239 2.2584 -1.0082 1.9911 3.6395 0.3838 0.3577 0.1782 6.2794 1.6262
-#> 126: 93.4956 -6.0529 -0.1244 2.2482 -1.0096 1.8916 3.4576 0.3847 0.3505 0.1753 6.1181 1.6347
-#> 127: 93.6265 -5.9360 -0.1298 2.2342 -1.0075 1.7970 3.2847 0.3887 0.3367 0.1691 6.2315 1.7051
-#> 128: 93.4446 -6.0523 -0.1337 2.2453 -1.0079 1.7072 3.1205 0.3840 0.3302 0.1759 6.2082 1.6705
-#> 129: 93.4470 -6.0065 -0.1321 2.2321 -1.0015 1.6636 2.9644 0.3853 0.3303 0.1671 6.1479 1.6733
-#> 130: 93.3205 -5.9628 -0.1290 2.2252 -0.9954 2.0336 2.9210 0.3879 0.3284 0.1634 6.0582 1.6372
-#> 131: 93.3836 -5.8919 -0.1358 2.2375 -0.9930 2.1392 2.7749 0.3801 0.3202 0.1644 5.9972 1.6837
-#> 132: 93.1041 -5.9265 -0.1203 2.2552 -0.9929 2.0323 2.8741 0.3831 0.3353 0.1755 6.0648 1.5934
-#> 133: 93.1617 -6.0668 -0.1175 2.2538 -0.9963 1.9306 3.6825 0.3846 0.3187 0.1790 6.0732 1.5684
-#> 134: 93.1503 -6.1208 -0.1232 2.2644 -0.9851 2.3429 3.8026 0.3788 0.3296 0.1737 5.8807 1.5722
-#> 135: 92.8629 -5.9726 -0.1197 2.2650 -0.9761 2.2257 3.6124 0.3802 0.3407 0.1765 5.8408 1.5446
-#> 136: 93.1460 -6.0654 -0.1227 2.2661 -0.9736 2.1144 3.4583 0.3770 0.3434 0.1700 5.7690 1.5561
-#> 137: 93.1243 -6.2350 -0.1274 2.2472 -0.9811 2.0087 4.3526 0.3733 0.3670 0.1615 5.9377 1.5224
-#> 138: 93.1203 -6.1704 -0.1283 2.2472 -0.9891 1.9083 4.1557 0.3788 0.3671 0.1641 5.8765 1.5525
-#> 139: 93.2841 -6.0586 -0.1366 2.2404 -0.9894 1.8129 4.3184 0.3718 0.3693 0.1630 6.1854 1.6388
-#> 140: 93.4239 -6.2398 -0.1382 2.2459 -0.9713 1.7241 4.5903 0.3713 0.3627 0.1548 6.0737 1.5826
-#> 141: 93.4149 -6.1972 -0.1388 2.2605 -0.9686 2.2179 4.5557 0.3701 0.3675 0.1486 6.0793 1.5603
-#> 142: 93.4404 -5.8955 -0.1203 2.2682 -0.9706 2.1070 4.3279 0.3830 0.3719 0.1581 5.9534 1.6189
-#> 143: 93.3108 -5.8069 -0.1142 2.2835 -0.9672 2.0194 4.1115 0.3787 0.3924 0.1592 5.9410 1.5521
-#> 144: 93.3953 -5.7456 -0.1154 2.2891 -0.9553 2.2741 3.9059 0.3787 0.3849 0.1633 6.0163 1.5640
-#> 145: 93.3322 -5.8301 -0.1100 2.2926 -0.9595 2.1604 3.7106 0.3687 0.3754 0.1657 5.8968 1.5844
-#> 146: 93.0844 -5.8926 -0.1084 2.2870 -0.9605 2.0524 3.5251 0.3649 0.3713 0.1646 6.1960 1.5691
-#> 147: 93.2106 -6.0084 -0.1074 2.2931 -0.9654 1.9498 3.5341 0.3646 0.3669 0.1641 6.0548 1.5230
-#> 148: 93.2005 -6.1989 -0.1065 2.2924 -0.9740 1.8523 4.4855 0.3631 0.3660 0.1759 5.9600 1.5194
-#> 149: 93.0788 -6.2470 -0.1108 2.2861 -0.9836 2.1348 4.7630 0.3597 0.3815 0.1815 5.9584 1.5227
-#> 150: 93.2241 -6.2660 -0.1126 2.2847 -0.9912 2.1149 5.0574 0.3656 0.3788 0.1781 5.7213 1.5379
-#> 151: 93.0046 -6.5379 -0.1164 2.2757 -0.9845 2.0092 6.8660 0.3719 0.3827 0.1807 5.7612 1.5697
-#> 152: 93.2222 -6.4637 -0.1154 2.2737 -0.9950 1.6744 6.2289 0.3670 0.3881 0.1638 5.8514 1.5920
-#> 153: 93.1619 -6.3230 -0.1224 2.2638 -0.9924 1.7907 5.5429 0.3842 0.3946 0.1720 5.7562 1.5493
-#> 154: 93.0402 -6.4004 -0.1205 2.2633 -0.9868 1.7620 6.2494 0.3860 0.3891 0.1737 5.7577 1.5109
-#> 155: 93.1692 -6.4353 -0.1203 2.2696 -0.9761 1.8710 6.4519 0.3949 0.3962 0.1721 5.8348 1.4949
-#> 156: 93.2709 -6.2672 -0.1203 2.2663 -0.9708 2.1172 5.1692 0.3949 0.4187 0.1637 6.1251 1.5012
-#> 157: 93.1264 -6.1931 -0.1208 2.2728 -0.9669 1.9985 4.7739 0.3938 0.4031 0.1696 6.1014 1.5627
-#> 158: 93.1263 -6.1951 -0.1237 2.2826 -0.9729 1.7675 4.6131 0.3928 0.3904 0.1659 6.1582 1.5647
-#> 159: 92.9780 -6.2831 -0.1242 2.2726 -0.9770 1.8348 5.4674 0.3938 0.3887 0.1631 6.0622 1.5787
-#> 160: 93.1289 -6.4397 -0.1263 2.2651 -0.9675 2.4637 6.0560 0.3919 0.4017 0.1626 5.9486 1.5859
-#> 161: 93.2629 -6.3336 -0.1294 2.2670 -0.9666 2.9602 5.4966 0.3872 0.3988 0.1667 5.9034 1.5421
-#> 162: 93.1652 -6.3800 -0.1342 2.2518 -0.9754 2.8800 5.6206 0.3908 0.4158 0.1627 5.9332 1.5306
-#> 163: 93.2886 -6.4115 -0.1437 2.2330 -0.9685 1.9997 6.2760 0.4015 0.4076 0.1623 5.7905 1.5398
-#> 164: 93.4631 -6.7246 -0.1396 2.2358 -0.9854 1.8885 7.8014 0.3952 0.4028 0.1573 5.7052 1.5695
-#> 165: 93.4757 -6.8408 -0.1404 2.2346 -0.9825 2.4877 9.3632 0.3948 0.4019 0.1615 5.8406 1.5902
-#> 166: 93.9075 -6.7707 -0.1428 2.2331 -0.9848 1.9761 8.9292 0.3939 0.3909 0.1610 5.7600 1.5966
-#> 167: 93.8895 -7.1938 -0.1363 2.2449 -0.9870 2.0894 11.4058 0.3850 0.3899 0.1627 5.8501 1.5748
-#> 168: 93.5849 -6.8478 -0.1294 2.2466 -0.9888 2.3573 9.4037 0.3935 0.3808 0.1645 6.0206 1.6591
-#> 169: 93.4931 -6.4550 -0.1173 2.2727 -0.9990 2.1948 6.5738 0.3844 0.4029 0.1699 6.0990 1.6123
-#> 170: 93.7188 -6.4015 -0.1173 2.2715 -0.9981 1.8800 6.1745 0.3844 0.4001 0.1635 6.1990 1.5745
-#> 171: 93.5938 -6.4389 -0.1119 2.2663 -0.9893 2.5731 6.5397 0.3858 0.4044 0.1554 6.1636 1.5631
-#> 172: 93.4515 -6.2049 -0.1050 2.2937 -0.9701 2.6134 4.6813 0.3687 0.4017 0.1715 6.3875 1.5006
-#> 173: 93.2254 -6.2074 -0.1041 2.3111 -0.9661 2.5799 4.6939 0.3669 0.4016 0.1738 6.5633 1.5229
-#> 174: 93.4116 -6.1198 -0.1050 2.3075 -0.9711 3.0196 4.3080 0.3720 0.3988 0.1778 6.4856 1.5214
-#> 175: 93.4952 -6.0439 -0.1050 2.3008 -0.9714 3.1172 3.7728 0.3720 0.3979 0.1749 6.1918 1.4985
-#> 176: 93.6186 -6.0891 -0.1061 2.3033 -0.9794 2.1081 3.8909 0.3705 0.4029 0.1796 6.1064 1.4657
-#> 177: 93.6432 -5.9977 -0.1031 2.2953 -0.9950 1.9411 3.4156 0.3694 0.3970 0.1843 6.0473 1.4918
-#> 178: 93.5736 -6.0079 -0.0996 2.2986 -0.9809 1.7778 3.5107 0.3696 0.3909 0.1840 6.1243 1.4937
-#> 179: 93.6407 -6.0246 -0.0977 2.3042 -0.9770 2.0631 3.8144 0.3718 0.3885 0.1798 6.1851 1.5212
-#> 180: 93.6336 -5.8865 -0.0969 2.3217 -0.9871 2.2566 3.1377 0.3721 0.3715 0.1784 6.0747 1.5546
-#> 181: 93.5075 -5.8632 -0.0965 2.3140 -0.9764 2.5812 2.9771 0.3715 0.3728 0.1876 5.9833 1.5356
-#> 182: 93.4464 -5.8627 -0.0930 2.3211 -0.9713 2.5956 2.8054 0.3836 0.3759 0.1861 6.1293 1.6259
-#> 183: 93.2737 -5.8238 -0.0977 2.3127 -0.9642 2.8739 2.6277 0.3846 0.3743 0.1868 6.0451 1.6493
-#> 184: 93.2191 -5.9175 -0.0993 2.3107 -0.9592 2.3088 3.0689 0.3829 0.3515 0.1711 6.1487 1.6666
-#> 185: 93.3626 -5.8872 -0.1070 2.3112 -0.9413 2.2812 3.2719 0.3712 0.3555 0.1783 6.1295 1.6288
-#> 186: 93.1585 -5.8532 -0.1053 2.3140 -0.9665 2.7906 2.8415 0.3734 0.3531 0.1680 6.0294 1.6104
-#> 187: 93.3041 -5.6798 -0.0957 2.3158 -0.9608 3.1056 2.0850 0.3813 0.3484 0.1728 6.1191 1.5813
-#> 188: 93.2466 -5.6791 -0.0954 2.3172 -0.9446 3.8296 2.1956 0.3816 0.3439 0.1757 5.9670 1.5445
-#> 189: 93.3532 -5.6883 -0.0859 2.3335 -0.9594 2.8968 2.3125 0.3691 0.3512 0.1812 5.9467 1.6101
-#> 190: 93.5064 -5.6288 -0.0726 2.3548 -0.9562 2.8233 2.1930 0.3334 0.3700 0.1759 6.4036 1.5877
-#> 191: 93.4145 -5.6906 -0.0726 2.3467 -0.9624 2.8818 2.3581 0.3334 0.3771 0.1712 6.2046 1.4952
-#> 192: 93.2060 -5.7479 -0.0716 2.3433 -0.9618 2.5221 2.6613 0.3324 0.3909 0.1552 6.1651 1.4971
-#> 193: 93.2904 -5.7634 -0.0811 2.3327 -0.9585 2.6968 2.6324 0.3339 0.3856 0.1632 6.5621 1.5258
-#> 194: 93.5271 -5.7859 -0.0874 2.3419 -0.9580 2.8361 2.8424 0.3286 0.3784 0.1636 6.3714 1.5386
-#> 195: 93.3944 -5.9358 -0.0838 2.3407 -0.9718 3.4161 3.2427 0.3315 0.3787 0.1678 6.3722 1.5181
-#> 196: 93.2341 -5.9078 -0.0701 2.3492 -0.9816 3.1580 3.0586 0.3285 0.3666 0.1681 6.4633 1.5382
-#> 197: 93.2967 -6.0131 -0.0745 2.3426 -0.9991 3.7978 3.6459 0.3353 0.3491 0.1796 6.2264 1.5310
-#> 198: 93.2628 -5.7991 -0.0730 2.3434 -0.9819 2.3896 2.6695 0.3371 0.3431 0.1762 6.3141 1.5254
-#> 199: 93.2765 -5.9078 -0.0782 2.3553 -0.9864 2.2760 3.3883 0.3420 0.3459 0.1866 6.0192 1.4982
-#> 200: 93.0447 -5.9148 -0.0769 2.3543 -0.9759 2.1516 2.9675 0.3455 0.3476 0.1870 5.9079 1.4688
-#> 201: 93.1655 -5.8951 -0.0763 2.3493 -0.9707 1.8254 2.9481 0.3448 0.3526 0.1831 6.0676 1.5097
-#> 202: 93.1082 -5.8916 -0.0768 2.3499 -0.9673 1.8503 2.9562 0.3447 0.3574 0.1821 6.1282 1.5026
-#> 203: 93.0728 -5.9316 -0.0774 2.3506 -0.9650 2.0210 3.2306 0.3441 0.3563 0.1827 6.1253 1.4974
-#> 204: 93.0846 -5.9347 -0.0773 2.3494 -0.9648 2.1463 3.2567 0.3453 0.3563 0.1824 6.1301 1.4911
-#> 205: 93.0929 -5.9439 -0.0781 2.3491 -0.9659 2.2204 3.3165 0.3453 0.3572 0.1823 6.1098 1.4941
-#> 206: 93.1795 -5.9401 -0.0795 2.3481 -0.9681 2.2588 3.2940 0.3470 0.3568 0.1829 6.1132 1.4996
-#> 207: 93.2303 -5.9158 -0.0805 2.3467 -0.9703 2.3439 3.1823 0.3484 0.3571 0.1845 6.1021 1.5059
-#> 208: 93.2161 -5.8969 -0.0825 2.3440 -0.9700 2.3306 3.0999 0.3496 0.3563 0.1848 6.0998 1.5177
-#> 209: 93.2077 -5.8842 -0.0848 2.3413 -0.9681 2.3580 3.0406 0.3499 0.3553 0.1841 6.0829 1.5199
-#> 210: 93.1951 -5.8661 -0.0867 2.3383 -0.9656 2.4170 2.9578 0.3501 0.3543 0.1833 6.0562 1.5261
-#> 211: 93.1870 -5.8543 -0.0892 2.3347 -0.9645 2.4650 2.9307 0.3502 0.3548 0.1831 6.0286 1.5289
-#> 212: 93.2077 -5.8506 -0.0915 2.3316 -0.9626 2.4909 2.9544 0.3504 0.3555 0.1835 6.0079 1.5300
-#> 213: 93.2104 -5.8492 -0.0938 2.3283 -0.9612 2.4695 2.9635 0.3503 0.3548 0.1841 5.9859 1.5341
-#> 214: 93.2059 -5.8537 -0.0959 2.3255 -0.9615 2.4264 3.0084 0.3499 0.3540 0.1835 5.9698 1.5370
-#> 215: 93.2051 -5.8569 -0.0977 2.3227 -0.9608 2.4277 3.0541 0.3495 0.3534 0.1830 5.9586 1.5374
-#> 216: 93.1879 -5.8596 -0.0993 2.3199 -0.9600 2.4347 3.0802 0.3493 0.3534 0.1828 5.9465 1.5380
-#> 217: 93.1834 -5.8621 -0.1008 2.3173 -0.9594 2.4479 3.0998 0.3491 0.3535 0.1827 5.9369 1.5402
-#> 218: 93.1796 -5.8657 -0.1021 2.3152 -0.9593 2.4234 3.1238 0.3492 0.3534 0.1835 5.9184 1.5441
-#> 219: 93.1680 -5.8721 -0.1032 2.3132 -0.9588 2.4640 3.1464 0.3494 0.3531 0.1839 5.8929 1.5493
-#> 220: 93.1579 -5.8839 -0.1044 2.3118 -0.9586 2.5707 3.1909 0.3495 0.3531 0.1847 5.8754 1.5496
-#> 221: 93.1557 -5.8882 -0.1058 2.3100 -0.9583 2.6662 3.2052 0.3492 0.3533 0.1854 5.8662 1.5518
-#> 222: 93.1624 -5.8832 -0.1074 2.3075 -0.9578 2.7993 3.1736 0.3490 0.3542 0.1861 5.8489 1.5546
-#> 223: 93.1699 -5.8771 -0.1086 2.3052 -0.9583 2.9085 3.1456 0.3488 0.3558 0.1871 5.8436 1.5610
-#> 224: 93.1870 -5.8751 -0.1097 2.3037 -0.9583 2.9988 3.1279 0.3487 0.3570 0.1878 5.8390 1.5628
-#> 225: 93.2094 -5.8719 -0.1110 2.3012 -0.9583 3.0581 3.1018 0.3485 0.3574 0.1885 5.8214 1.5656
-#> 226: 93.2352 -5.8683 -0.1122 2.2988 -0.9587 3.1297 3.0761 0.3482 0.3584 0.1895 5.8105 1.5680
-#> 227: 93.2611 -5.8653 -0.1132 2.2964 -0.9589 3.1563 3.0610 0.3476 0.3594 0.1904 5.8038 1.5701
-#> 228: 93.2741 -5.8593 -0.1140 2.2943 -0.9591 3.1641 3.0356 0.3470 0.3603 0.1911 5.7984 1.5730
-#> 229: 93.2899 -5.8593 -0.1151 2.2919 -0.9595 3.1626 3.0313 0.3466 0.3613 0.1918 5.7999 1.5745
-#> 230: 93.3048 -5.8650 -0.1164 2.2899 -0.9593 3.1743 3.0542 0.3460 0.3624 0.1921 5.7990 1.5753
-#> 231: 93.3159 -5.8638 -0.1177 2.2875 -0.9592 3.1930 3.0524 0.3454 0.3631 0.1924 5.7956 1.5748
-#> 232: 93.3209 -5.8611 -0.1189 2.2852 -0.9590 3.1872 3.0420 0.3450 0.3639 0.1926 5.7921 1.5755
-#> 233: 93.3196 -5.8556 -0.1200 2.2833 -0.9589 3.1861 3.0209 0.3445 0.3644 0.1926 5.7852 1.5779
-#> 234: 93.3245 -5.8530 -0.1210 2.2813 -0.9591 3.1890 3.0115 0.3441 0.3651 0.1922 5.7781 1.5786
-#> 235: 93.3219 -5.8522 -0.1218 2.2800 -0.9593 3.1573 3.0042 0.3437 0.3659 0.1917 5.7813 1.5797
-#> 236: 93.3155 -5.8524 -0.1227 2.2789 -0.9595 3.1542 3.0035 0.3433 0.3669 0.1913 5.7834 1.5800
-#> 237: 93.3060 -5.8556 -0.1235 2.2779 -0.9599 3.1308 3.0158 0.3430 0.3678 0.1910 5.7833 1.5809
-#> 238: 93.3111 -5.8563 -0.1242 2.2772 -0.9602 3.1194 3.0099 0.3427 0.3683 0.1907 5.7842 1.5809
-#> 239: 93.3177 -5.8580 -0.1248 2.2764 -0.9605 3.0944 3.0130 0.3423 0.3686 0.1904 5.7840 1.5815
-#> 240: 93.3222 -5.8606 -0.1255 2.2754 -0.9608 3.0739 3.0140 0.3420 0.3686 0.1902 5.7843 1.5825
-#> 241: 93.3289 -5.8627 -0.1262 2.2740 -0.9611 3.0848 3.0167 0.3417 0.3688 0.1900 5.7836 1.5840
-#> 242: 93.3366 -5.8627 -0.1270 2.2727 -0.9612 3.1273 3.0103 0.3415 0.3691 0.1898 5.7855 1.5850
-#> 243: 93.3441 -5.8646 -0.1277 2.2714 -0.9614 3.1530 3.0218 0.3414 0.3692 0.1896 5.7829 1.5856
-#> 244: 93.3499 -5.8645 -0.1285 2.2700 -0.9618 3.1705 3.0265 0.3412 0.3694 0.1894 5.7778 1.5874
-#> 245: 93.3619 -5.8673 -0.1294 2.2686 -0.9622 3.1863 3.0397 0.3412 0.3694 0.1892 5.7752 1.5889
-#> 246: 93.3745 -5.8698 -0.1301 2.2671 -0.9627 3.2105 3.0484 0.3412 0.3693 0.1890 5.7716 1.5905
-#> 247: 93.3838 -5.8757 -0.1307 2.2659 -0.9632 3.2158 3.0715 0.3412 0.3693 0.1889 5.7688 1.5922
-#> 248: 93.3914 -5.8799 -0.1314 2.2650 -0.9640 3.2268 3.0851 0.3413 0.3690 0.1889 5.7648 1.5934
-#> 249: 93.3983 -5.8844 -0.1319 2.2640 -0.9648 3.2471 3.0990 0.3415 0.3691 0.1889 5.7641 1.5944
-#> 250: 93.4032 -5.8898 -0.1324 2.2629 -0.9655 3.2828 3.1197 0.3414 0.3694 0.1887 5.7623 1.5965
-#> 251: 93.4053 -5.8939 -0.1329 2.2621 -0.9657 3.3074 3.1303 0.3414 0.3698 0.1887 5.7611 1.5978
-#> 252: 93.4095 -5.8950 -0.1334 2.2613 -0.9658 3.3479 3.1281 0.3414 0.3701 0.1887 5.7578 1.5986
-#> 253: 93.4132 -5.8956 -0.1340 2.2606 -0.9660 3.3486 3.1283 0.3413 0.3703 0.1887 5.7559 1.5999
-#> 254: 93.4201 -5.8966 -0.1345 2.2597 -0.9660 3.3502 3.1298 0.3413 0.3706 0.1888 5.7593 1.5997
-#> 255: 93.4235 -5.8953 -0.1349 2.2590 -0.9656 3.3332 3.1220 0.3412 0.3706 0.1887 5.7571 1.6012
-#> 256: 93.4231 -5.8926 -0.1353 2.2585 -0.9651 3.3255 3.1104 0.3411 0.3706 0.1886 5.7569 1.6018
-#> 257: 93.4247 -5.8874 -0.1356 2.2582 -0.9646 3.3164 3.0917 0.3410 0.3705 0.1885 5.7585 1.6030
-#> 258: 93.4198 -5.8857 -0.1359 2.2580 -0.9641 3.3086 3.0828 0.3409 0.3702 0.1885 5.7608 1.6026
-#> 259: 93.4125 -5.8833 -0.1362 2.2576 -0.9638 3.2926 3.0726 0.3408 0.3701 0.1885 5.7651 1.6023
-#> 260: 93.4073 -5.8847 -0.1365 2.2572 -0.9640 3.2737 3.0759 0.3406 0.3703 0.1885 5.7687 1.6030
-#> 261: 93.4049 -5.8885 -0.1368 2.2571 -0.9642 3.2510 3.0904 0.3402 0.3702 0.1882 5.7742 1.6028
-#> 262: 93.4036 -5.8931 -0.1371 2.2566 -0.9645 3.2279 3.1104 0.3397 0.3699 0.1880 5.7766 1.6033
-#> 263: 93.4026 -5.8964 -0.1375 2.2562 -0.9647 3.2024 3.1313 0.3395 0.3696 0.1877 5.7786 1.6029
-#> 264: 93.3990 -5.9003 -0.1377 2.2559 -0.9649 3.1808 3.1545 0.3393 0.3694 0.1874 5.7778 1.6022
-#> 265: 93.4005 -5.9013 -0.1380 2.2555 -0.9650 3.1664 3.1680 0.3390 0.3693 0.1871 5.7765 1.6021
-#> 266: 93.4005 -5.9011 -0.1382 2.2552 -0.9653 3.1530 3.1708 0.3387 0.3692 0.1869 5.7763 1.6020
-#> 267: 93.4006 -5.9035 -0.1384 2.2549 -0.9654 3.1384 3.1902 0.3384 0.3690 0.1866 5.7768 1.6014
-#> 268: 93.3972 -5.9086 -0.1385 2.2547 -0.9653 3.1224 3.2331 0.3380 0.3688 0.1863 5.7778 1.6008
-#> 269: 93.3936 -5.9113 -0.1386 2.2547 -0.9654 3.0959 3.2552 0.3377 0.3688 0.1861 5.7782 1.6001
-#> 270: 93.3867 -5.9139 -0.1387 2.2547 -0.9653 3.0853 3.2756 0.3372 0.3687 0.1859 5.7787 1.5989
-#> 271: 93.3836 -5.9154 -0.1389 2.2545 -0.9654 3.0824 3.2889 0.3367 0.3686 0.1858 5.7761 1.5980
-#> 272: 93.3812 -5.9160 -0.1390 2.2543 -0.9653 3.0741 3.2919 0.3362 0.3686 0.1857 5.7729 1.5977
-#> 273: 93.3767 -5.9174 -0.1390 2.2542 -0.9652 3.0663 3.2992 0.3358 0.3687 0.1856 5.7699 1.5970
-#> 274: 93.3696 -5.9171 -0.1391 2.2543 -0.9652 3.0604 3.2940 0.3355 0.3687 0.1855 5.7688 1.5958
-#> 275: 93.3658 -5.9177 -0.1393 2.2544 -0.9651 3.0605 3.2961 0.3353 0.3687 0.1853 5.7675 1.5952
-#> 276: 93.3621 -5.9185 -0.1395 2.2543 -0.9649 3.0508 3.2992 0.3351 0.3686 0.1852 5.7672 1.5940
-#> 277: 93.3602 -5.9206 -0.1397 2.2542 -0.9649 3.0453 3.3087 0.3349 0.3685 0.1851 5.7679 1.5935
-#> 278: 93.3565 -5.9213 -0.1400 2.2539 -0.9648 3.0366 3.3117 0.3347 0.3683 0.1852 5.7695 1.5931
-#> 279: 93.3548 -5.9222 -0.1403 2.2535 -0.9647 3.0284 3.3179 0.3345 0.3682 0.1854 5.7703 1.5928
-#> 280: 93.3544 -5.9215 -0.1407 2.2528 -0.9647 3.0193 3.3141 0.3344 0.3683 0.1854 5.7714 1.5927
-#> 281: 93.3533 -5.9205 -0.1410 2.2522 -0.9647 3.0130 3.3090 0.3341 0.3685 0.1855 5.7706 1.5927
-#> 282: 93.3564 -5.9189 -0.1414 2.2514 -0.9648 3.0025 3.3019 0.3339 0.3686 0.1856 5.7682 1.5930
-#> 283: 93.3571 -5.9164 -0.1417 2.2508 -0.9646 2.9990 3.2926 0.3337 0.3686 0.1858 5.7642 1.5943
-#> 284: 93.3576 -5.9154 -0.1421 2.2501 -0.9644 2.9976 3.2895 0.3336 0.3686 0.1860 5.7625 1.5942
-#> 285: 93.3584 -5.9142 -0.1425 2.2496 -0.9644 2.9906 3.2835 0.3334 0.3684 0.1861 5.7591 1.5939
-#> 286: 93.3609 -5.9137 -0.1429 2.2491 -0.9642 2.9852 3.2817 0.3332 0.3682 0.1863 5.7572 1.5939
-#> 287: 93.3641 -5.9131 -0.1433 2.2485 -0.9641 2.9732 3.2785 0.3331 0.3680 0.1863 5.7547 1.5944
-#> 288: 93.3671 -5.9128 -0.1436 2.2480 -0.9641 2.9673 3.2767 0.3330 0.3679 0.1864 5.7540 1.5939
-#> 289: 93.3676 -5.9125 -0.1440 2.2474 -0.9639 2.9663 3.2765 0.3329 0.3678 0.1865 5.7536 1.5939
-#> 290: 93.3659 -5.9126 -0.1443 2.2469 -0.9637 2.9570 3.2776 0.3328 0.3678 0.1866 5.7523 1.5941
-#> 291: 93.3620 -5.9109 -0.1447 2.2466 -0.9634 2.9472 3.2713 0.3327 0.3676 0.1866 5.7527 1.5943
-#> 292: 93.3601 -5.9096 -0.1450 2.2462 -0.9632 2.9359 3.2664 0.3326 0.3675 0.1866 5.7517 1.5944
-#> 293: 93.3582 -5.9077 -0.1453 2.2457 -0.9629 2.9295 3.2586 0.3326 0.3675 0.1866 5.7514 1.5945
-#> 294: 93.3583 -5.9054 -0.1456 2.2454 -0.9626 2.9203 3.2478 0.3326 0.3676 0.1867 5.7508 1.5942
-#> 295: 93.3577 -5.9037 -0.1459 2.2449 -0.9624 2.9216 3.2406 0.3325 0.3678 0.1867 5.7493 1.5934
-#> 296: 93.3570 -5.9016 -0.1462 2.2445 -0.9623 2.9304 3.2334 0.3323 0.3680 0.1868 5.7502 1.5933
-#> 297: 93.3538 -5.8988 -0.1462 2.2441 -0.9621 2.9429 3.2217 0.3321 0.3681 0.1870 5.7539 1.5939
-#> 298: 93.3525 -5.8966 -0.1463 2.2438 -0.9620 2.9662 3.2118 0.3319 0.3683 0.1870 5.7555 1.5942
-#> 299: 93.3526 -5.8957 -0.1465 2.2437 -0.9619 2.9812 3.2056 0.3318 0.3685 0.1870 5.7582 1.5938
-#> 300: 93.3504 -5.8953 -0.1467 2.2436 -0.9616 2.9982 3.2029 0.3316 0.3688 0.1873 5.7609 1.5937
-#> 301: 93.3469 -5.8941 -0.1469 2.2434 -0.9612 3.0124 3.1993 0.3315 0.3690 0.1875 5.7641 1.5933
-#> 302: 93.3442 -5.8944 -0.1472 2.2434 -0.9609 3.0353 3.2015 0.3313 0.3692 0.1876 5.7660 1.5937
-#> 303: 93.3428 -5.8970 -0.1474 2.2432 -0.9607 3.0454 3.2160 0.3312 0.3692 0.1876 5.7654 1.5938
-#> 304: 93.3407 -5.9012 -0.1475 2.2430 -0.9607 3.0626 3.2409 0.3310 0.3693 0.1877 5.7649 1.5932
-#> 305: 93.3395 -5.9051 -0.1476 2.2429 -0.9607 3.0756 3.2632 0.3308 0.3693 0.1879 5.7650 1.5924
-#> 306: 93.3398 -5.9099 -0.1478 2.2429 -0.9607 3.0881 3.2952 0.3306 0.3694 0.1880 5.7655 1.5920
-#> 307: 93.3406 -5.9128 -0.1479 2.2427 -0.9608 3.0995 3.3163 0.3305 0.3695 0.1880 5.7666 1.5921
-#> 308: 93.3418 -5.9165 -0.1480 2.2426 -0.9610 3.1060 3.3420 0.3303 0.3696 0.1881 5.7674 1.5914
-#> 309: 93.3437 -5.9205 -0.1481 2.2424 -0.9610 3.1185 3.3703 0.3301 0.3697 0.1882 5.7665 1.5908
-#> 310: 93.3442 -5.9236 -0.1482 2.2422 -0.9612 3.1270 3.3902 0.3299 0.3698 0.1882 5.7650 1.5904
-#> 311: 93.3482 -5.9268 -0.1482 2.2421 -0.9614 3.1333 3.4086 0.3296 0.3698 0.1882 5.7636 1.5900
-#> 312: 93.3529 -5.9286 -0.1482 2.2420 -0.9615 3.1348 3.4186 0.3294 0.3699 0.1882 5.7622 1.5895
-#> 313: 93.3573 -5.9290 -0.1481 2.2419 -0.9617 3.1332 3.4199 0.3291 0.3699 0.1882 5.7621 1.5891
-#> 314: 93.3630 -5.9293 -0.1482 2.2418 -0.9619 3.1398 3.4211 0.3289 0.3700 0.1883 5.7594 1.5888
-#> 315: 93.3669 -5.9284 -0.1483 2.2416 -0.9622 3.1464 3.4155 0.3286 0.3702 0.1885 5.7586 1.5889
-#> 316: 93.3724 -5.9279 -0.1485 2.2412 -0.9624 3.1426 3.4124 0.3283 0.3704 0.1887 5.7581 1.5887
-#> 317: 93.3763 -5.9281 -0.1487 2.2409 -0.9626 3.1335 3.4108 0.3281 0.3706 0.1888 5.7573 1.5880
-#> 318: 93.3786 -5.9275 -0.1488 2.2405 -0.9627 3.1262 3.4057 0.3279 0.3709 0.1888 5.7579 1.5876
-#> 319: 93.3821 -5.9275 -0.1490 2.2402 -0.9628 3.1273 3.4032 0.3276 0.3711 0.1889 5.7570 1.5870
-#> 320: 93.3856 -5.9272 -0.1491 2.2401 -0.9629 3.1337 3.3989 0.3273 0.3715 0.1888 5.7563 1.5861
-#> 321: 93.3902 -5.9263 -0.1492 2.2399 -0.9631 3.1388 3.3931 0.3269 0.3718 0.1887 5.7555 1.5852
-#> 322: 93.3951 -5.9251 -0.1493 2.2397 -0.9631 3.1415 3.3856 0.3266 0.3721 0.1886 5.7552 1.5846
-#> 323: 93.3988 -5.9251 -0.1493 2.2395 -0.9632 3.1377 3.3824 0.3262 0.3724 0.1885 5.7556 1.5841
-#> 324: 93.4030 -5.9236 -0.1494 2.2394 -0.9633 3.1355 3.3738 0.3259 0.3727 0.1885 5.7562 1.5837
-#> 325: 93.4047 -5.9219 -0.1495 2.2393 -0.9633 3.1415 3.3647 0.3256 0.3731 0.1884 5.7553 1.5831
-#> 326: 93.4077 -5.9204 -0.1495 2.2391 -0.9634 3.1489 3.3564 0.3254 0.3735 0.1884 5.7562 1.5829
-#> 327: 93.4121 -5.9185 -0.1496 2.2390 -0.9635 3.1503 3.3472 0.3250 0.3739 0.1884 5.7562 1.5825
-#> 328: 93.4157 -5.9182 -0.1496 2.2389 -0.9636 3.1564 3.3432 0.3246 0.3743 0.1884 5.7559 1.5823
-#> 329: 93.4181 -5.9169 -0.1496 2.2388 -0.9638 3.1666 3.3361 0.3243 0.3746 0.1884 5.7544 1.5822
-#> 330: 93.4206 -5.9171 -0.1497 2.2386 -0.9640 3.1726 3.3349 0.3239 0.3748 0.1885 5.7538 1.5824
-#> 331: 93.4214 -5.9172 -0.1497 2.2385 -0.9642 3.1764 3.3332 0.3236 0.3750 0.1886 5.7540 1.5824
-#> 332: 93.4226 -5.9171 -0.1497 2.2385 -0.9645 3.1787 3.3303 0.3232 0.3752 0.1887 5.7539 1.5826
-#> 333: 93.4242 -5.9168 -0.1497 2.2384 -0.9645 3.1757 3.3287 0.3229 0.3755 0.1886 5.7545 1.5823
-#> 334: 93.4273 -5.9167 -0.1497 2.2383 -0.9645 3.1832 3.3290 0.3226 0.3758 0.1887 5.7540 1.5818
-#> 335: 93.4306 -5.9170 -0.1498 2.2384 -0.9644 3.1910 3.3318 0.3223 0.3760 0.1887 5.7548 1.5814
-#> 336: 93.4315 -5.9177 -0.1498 2.2384 -0.9644 3.1999 3.3355 0.3219 0.3762 0.1887 5.7558 1.5811
-#> 337: 93.4332 -5.9181 -0.1499 2.2384 -0.9643 3.2145 3.3360 0.3216 0.3764 0.1887 5.7581 1.5805
-#> 338: 93.4352 -5.9169 -0.1498 2.2384 -0.9643 3.2221 3.3307 0.3213 0.3767 0.1887 5.7592 1.5802
-#> 339: 93.4385 -5.9152 -0.1498 2.2384 -0.9643 3.2356 3.3242 0.3210 0.3770 0.1887 5.7605 1.5797
-#> 340: 93.4417 -5.9130 -0.1498 2.2384 -0.9643 3.2506 3.3167 0.3207 0.3773 0.1888 5.7599 1.5794
-#> 341: 93.4452 -5.9102 -0.1497 2.2382 -0.9641 3.2568 3.3064 0.3205 0.3772 0.1888 5.7590 1.5799
-#> 342: 93.4487 -5.9077 -0.1497 2.2381 -0.9641 3.2628 3.2970 0.3203 0.3772 0.1889 5.7587 1.5802
-#> 343: 93.4519 -5.9055 -0.1497 2.2380 -0.9642 3.2685 3.2892 0.3201 0.3772 0.1889 5.7585 1.5810
-#> 344: 93.4556 -5.9048 -0.1497 2.2379 -0.9643 3.2690 3.2847 0.3200 0.3771 0.1891 5.7573 1.5812
-#> 345: 93.4588 -5.9041 -0.1498 2.2377 -0.9645 3.2704 3.2807 0.3199 0.3771 0.1893 5.7567 1.5811
-#> 346: 93.4605 -5.9033 -0.1498 2.2376 -0.9647 3.2655 3.2747 0.3198 0.3770 0.1893 5.7557 1.5808
-#> 347: 93.4638 -5.9027 -0.1498 2.2375 -0.9648 3.2725 3.2701 0.3198 0.3768 0.1894 5.7532 1.5808
-#> 348: 93.4643 -5.9028 -0.1498 2.2373 -0.9649 3.2764 3.2676 0.3197 0.3768 0.1893 5.7523 1.5807
-#> 349: 93.4664 -5.9023 -0.1497 2.2372 -0.9650 3.2806 3.2638 0.3197 0.3767 0.1893 5.7527 1.5815
-#> 350: 93.4700 -5.9014 -0.1497 2.2370 -0.9651 3.2817 3.2585 0.3196 0.3767 0.1892 5.7534 1.5817
-#> 351: 93.4724 -5.9001 -0.1497 2.2369 -0.9652 3.2825 3.2522 0.3196 0.3768 0.1892 5.7541 1.5818
-#> 352: 93.4744 -5.8986 -0.1497 2.2369 -0.9653 3.2875 3.2460 0.3195 0.3768 0.1891 5.7546 1.5819
-#> 353: 93.4738 -5.8975 -0.1496 2.2369 -0.9653 3.2891 3.2407 0.3195 0.3769 0.1889 5.7560 1.5822
-#> 354: 93.4733 -5.8960 -0.1496 2.2369 -0.9652 3.2856 3.2333 0.3194 0.3768 0.1889 5.7579 1.5824
-#> 355: 93.4731 -5.8944 -0.1496 2.2370 -0.9652 3.2893 3.2259 0.3194 0.3767 0.1888 5.7599 1.5826
-#> 356: 93.4724 -5.8933 -0.1495 2.2373 -0.9652 3.2924 3.2197 0.3194 0.3767 0.1888 5.7608 1.5832
-#> 357: 93.4723 -5.8929 -0.1493 2.2376 -0.9654 3.2907 3.2164 0.3194 0.3767 0.1887 5.7605 1.5833
-#> 358: 93.4723 -5.8923 -0.1491 2.2378 -0.9654 3.2875 3.2120 0.3194 0.3766 0.1886 5.7608 1.5837
-#> 359: 93.4705 -5.8931 -0.1490 2.2379 -0.9656 3.2875 3.2121 0.3194 0.3764 0.1886 5.7606 1.5843
-#> 360: 93.4699 -5.8938 -0.1488 2.2382 -0.9658 3.2837 3.2133 0.3195 0.3763 0.1886 5.7606 1.5848
-#> 361: 93.4693 -5.8951 -0.1487 2.2383 -0.9659 3.2822 3.2164 0.3195 0.3763 0.1886 5.7600 1.5852
-#> 362: 93.4691 -5.8963 -0.1486 2.2385 -0.9660 3.2770 3.2196 0.3195 0.3763 0.1884 5.7618 1.5856
-#> 363: 93.4681 -5.8970 -0.1485 2.2387 -0.9660 3.2706 3.2208 0.3195 0.3762 0.1883 5.7639 1.5857
-#> 364: 93.4674 -5.8970 -0.1484 2.2389 -0.9660 3.2593 3.2189 0.3195 0.3760 0.1881 5.7659 1.5855
-#> 365: 93.4680 -5.8968 -0.1482 2.2391 -0.9659 3.2513 3.2174 0.3196 0.3758 0.1881 5.7686 1.5857
-#> 366: 93.4672 -5.8962 -0.1480 2.2393 -0.9658 3.2493 3.2161 0.3196 0.3755 0.1880 5.7714 1.5861
-#> 367: 93.4656 -5.8953 -0.1479 2.2396 -0.9657 3.2462 3.2121 0.3195 0.3753 0.1881 5.7721 1.5862
-#> 368: 93.4645 -5.8946 -0.1478 2.2398 -0.9657 3.2469 3.2083 0.3194 0.3750 0.1882 5.7724 1.5860
-#> 369: 93.4638 -5.8946 -0.1476 2.2401 -0.9657 3.2544 3.2068 0.3194 0.3749 0.1882 5.7713 1.5856
-#> 370: 93.4639 -5.8946 -0.1475 2.2404 -0.9657 3.2547 3.2066 0.3194 0.3748 0.1882 5.7719 1.5853
-#> 371: 93.4646 -5.8959 -0.1474 2.2407 -0.9657 3.2584 3.2129 0.3194 0.3746 0.1883 5.7725 1.5847
-#> 372: 93.4648 -5.8964 -0.1473 2.2409 -0.9658 3.2649 3.2172 0.3193 0.3745 0.1883 5.7730 1.5843
-#> 373: 93.4658 -5.8958 -0.1471 2.2411 -0.9659 3.2744 3.2135 0.3193 0.3743 0.1884 5.7730 1.5843
-#> 374: 93.4678 -5.8953 -0.1470 2.2412 -0.9662 3.2855 3.2100 0.3192 0.3742 0.1885 5.7727 1.5847
-#> 375: 93.4697 -5.8955 -0.1470 2.2413 -0.9663 3.2917 3.2087 0.3190 0.3742 0.1885 5.7733 1.5845
-#> 376: 93.4707 -5.8960 -0.1469 2.2414 -0.9664 3.2997 3.2095 0.3189 0.3741 0.1885 5.7726 1.5841
-#> 377: 93.4712 -5.8965 -0.1468 2.2415 -0.9665 3.3016 3.2100 0.3188 0.3741 0.1885 5.7724 1.5836
-#> 378: 93.4706 -5.8971 -0.1468 2.2416 -0.9665 3.2958 3.2113 0.3187 0.3741 0.1884 5.7733 1.5829
-#> 379: 93.4699 -5.8983 -0.1467 2.2418 -0.9666 3.2940 3.2174 0.3186 0.3741 0.1883 5.7732 1.5827
-#> 380: 93.4709 -5.8993 -0.1467 2.2418 -0.9667 3.2907 3.2225 0.3185 0.3739 0.1882 5.7726 1.5826
-#> 381: 93.4730 -5.9009 -0.1467 2.2418 -0.9667 3.2861 3.2325 0.3185 0.3737 0.1881 5.7709 1.5825
-#> 382: 93.4746 -5.9018 -0.1467 2.2418 -0.9667 3.2841 3.2407 0.3184 0.3734 0.1880 5.7692 1.5822
-#> 383: 93.4744 -5.9033 -0.1468 2.2418 -0.9667 3.2847 3.2537 0.3184 0.3732 0.1878 5.7672 1.5819
-#> 384: 93.4747 -5.9049 -0.1468 2.2418 -0.9667 3.2854 3.2640 0.3184 0.3729 0.1878 5.7657 1.5816
-#> 385: 93.4751 -5.9062 -0.1468 2.2418 -0.9666 3.2917 3.2702 0.3184 0.3727 0.1877 5.7642 1.5813
-#> 386: 93.4756 -5.9074 -0.1468 2.2418 -0.9666 3.2971 3.2753 0.3185 0.3725 0.1876 5.7625 1.5810
-#> 387: 93.4761 -5.9084 -0.1469 2.2417 -0.9666 3.2988 3.2789 0.3185 0.3723 0.1875 5.7613 1.5804
-#> 388: 93.4777 -5.9092 -0.1469 2.2417 -0.9666 3.3055 3.2811 0.3185 0.3721 0.1875 5.7599 1.5803
-#> 389: 93.4805 -5.9092 -0.1468 2.2417 -0.9667 3.3138 3.2802 0.3185 0.3719 0.1874 5.7588 1.5803
-#> 390: 93.4828 -5.9089 -0.1468 2.2417 -0.9667 3.3164 3.2782 0.3186 0.3718 0.1873 5.7576 1.5806
-#> 391: 93.4854 -5.9094 -0.1467 2.2416 -0.9668 3.3265 3.2800 0.3186 0.3716 0.1873 5.7556 1.5804
-#> 392: 93.4877 -5.9103 -0.1467 2.2416 -0.9669 3.3327 3.2836 0.3187 0.3715 0.1873 5.7535 1.5803
-#> 393: 93.4899 -5.9110 -0.1467 2.2416 -0.9669 3.3419 3.2876 0.3187 0.3715 0.1873 5.7517 1.5803
-#> 394: 93.4925 -5.9117 -0.1467 2.2416 -0.9669 3.3494 3.2903 0.3187 0.3714 0.1873 5.7508 1.5801
-#> 395: 93.4945 -5.9121 -0.1467 2.2416 -0.9670 3.3536 3.2912 0.3187 0.3714 0.1873 5.7497 1.5796
-#> 396: 93.4951 -5.9124 -0.1467 2.2416 -0.9670 3.3590 3.2918 0.3187 0.3715 0.1873 5.7476 1.5793
-#> 397: 93.4955 -5.9123 -0.1467 2.2416 -0.9669 3.3626 3.2904 0.3186 0.3715 0.1873 5.7456 1.5788
-#> 398: 93.4971 -5.9120 -0.1467 2.2416 -0.9669 3.3735 3.2887 0.3186 0.3716 0.1873 5.7433 1.5786
-#> 399: 93.4995 -5.9116 -0.1467 2.2415 -0.9669 3.3854 3.2866 0.3186 0.3716 0.1873 5.7422 1.5785
-#> 400: 93.5007 -5.9116 -0.1466 2.2415 -0.9669 3.3923 3.2856 0.3186 0.3717 0.1873 5.7416 1.5786
-#> 401: 93.5028 -5.9109 -0.1467 2.2415 -0.9669 3.4020 3.2820 0.3186 0.3718 0.1873 5.7412 1.5787
-#> 402: 93.5042 -5.9099 -0.1467 2.2414 -0.9669 3.4114 3.2781 0.3186 0.3719 0.1874 5.7406 1.5788
-#> 403: 93.5054 -5.9090 -0.1467 2.2413 -0.9670 3.4179 3.2735 0.3186 0.3720 0.1874 5.7401 1.5785
-#> 404: 93.5071 -5.9093 -0.1468 2.2412 -0.9670 3.4190 3.2726 0.3186 0.3720 0.1875 5.7392 1.5779
-#> 405: 93.5087 -5.9087 -0.1468 2.2411 -0.9671 3.4186 3.2689 0.3186 0.3721 0.1876 5.7386 1.5776
-#> 406: 93.5091 -5.9087 -0.1469 2.2411 -0.9671 3.4228 3.2688 0.3186 0.3721 0.1876 5.7377 1.5774
-#> 407: 93.5094 -5.9091 -0.1470 2.2411 -0.9672 3.4285 3.2698 0.3186 0.3720 0.1877 5.7368 1.5770
-#> 408: 93.5108 -5.9081 -0.1470 2.2410 -0.9672 3.4378 3.2648 0.3187 0.3719 0.1877 5.7358 1.5766
-#> 409: 93.5113 -5.9082 -0.1470 2.2410 -0.9672 3.4444 3.2643 0.3187 0.3719 0.1878 5.7357 1.5763
-#> 410: 93.5102 -5.9099 -0.1470 2.2410 -0.9672 3.4502 3.2731 0.3188 0.3719 0.1878 5.7359 1.5756
-#> 411: 93.5097 -5.9109 -0.1469 2.2410 -0.9673 3.4534 3.2793 0.3188 0.3718 0.1878 5.7348 1.5753
-#> 412: 93.5102 -5.9114 -0.1469 2.2410 -0.9673 3.4522 3.2836 0.3189 0.3717 0.1878 5.7330 1.5753
-#> 413: 93.5110 -5.9120 -0.1469 2.2410 -0.9675 3.4534 3.2885 0.3189 0.3716 0.1878 5.7320 1.5756
-#> 414: 93.5126 -5.9130 -0.1469 2.2410 -0.9675 3.4550 3.2943 0.3190 0.3716 0.1878 5.7314 1.5753
-#> 415: 93.5144 -5.9140 -0.1469 2.2409 -0.9676 3.4574 3.3003 0.3190 0.3715 0.1878 5.7304 1.5751
-#> 416: 93.5147 -5.9149 -0.1469 2.2409 -0.9676 3.4632 3.3059 0.3191 0.3714 0.1878 5.7292 1.5750
-#> 417: 93.5132 -5.9156 -0.1468 2.2410 -0.9677 3.4675 3.3090 0.3192 0.3713 0.1878 5.7292 1.5747
-#> 418: 93.5131 -5.9165 -0.1468 2.2410 -0.9678 3.4680 3.3130 0.3192 0.3712 0.1878 5.7296 1.5747
-#> 419: 93.5142 -5.9166 -0.1467 2.2411 -0.9678 3.4663 3.3143 0.3193 0.3712 0.1879 5.7302 1.5744
-#> 420: 93.5150 -5.9164 -0.1466 2.2412 -0.9679 3.4626 3.3130 0.3193 0.3712 0.1879 5.7303 1.5744
-#> 421: 93.5162 -5.9169 -0.1465 2.2413 -0.9681 3.4596 3.3158 0.3194 0.3713 0.1880 5.7315 1.5743
-#> 422: 93.5173 -5.9172 -0.1465 2.2414 -0.9682 3.4567 3.3165 0.3194 0.3714 0.1881 5.7332 1.5740
-#> 423: 93.5174 -5.9178 -0.1464 2.2415 -0.9684 3.4550 3.3185 0.3194 0.3715 0.1882 5.7348 1.5741
-#> 424: 93.5174 -5.9189 -0.1464 2.2417 -0.9685 3.4531 3.3225 0.3193 0.3716 0.1882 5.7360 1.5737
-#> 425: 93.5171 -5.9184 -0.1463 2.2418 -0.9685 3.4508 3.3186 0.3192 0.3718 0.1882 5.7372 1.5738
-#> 426: 93.5167 -5.9177 -0.1462 2.2419 -0.9686 3.4566 3.3143 0.3192 0.3720 0.1882 5.7385 1.5735
-#> 427: 93.5185 -5.9174 -0.1462 2.2420 -0.9687 3.4561 3.3114 0.3191 0.3721 0.1881 5.7389 1.5734
-#> 428: 93.5192 -5.9177 -0.1461 2.2421 -0.9688 3.4574 3.3112 0.3191 0.3722 0.1880 5.7398 1.5731
-#> 429: 93.5184 -5.9179 -0.1460 2.2421 -0.9689 3.4558 3.3102 0.3190 0.3723 0.1879 5.7405 1.5729
-#> 430: 93.5170 -5.9187 -0.1460 2.2421 -0.9690 3.4575 3.3132 0.3190 0.3724 0.1879 5.7404 1.5727
-#> 431: 93.5156 -5.9192 -0.1460 2.2422 -0.9691 3.4556 3.3150 0.3190 0.3724 0.1879 5.7405 1.5726
-#> 432: 93.5148 -5.9203 -0.1459 2.2422 -0.9692 3.4557 3.3201 0.3190 0.3725 0.1878 5.7409 1.5727
-#> 433: 93.5134 -5.9215 -0.1459 2.2422 -0.9692 3.4569 3.3263 0.3190 0.3726 0.1878 5.7415 1.5731
-#> 434: 93.5128 -5.9222 -0.1459 2.2423 -0.9691 3.4623 3.3304 0.3190 0.3726 0.1877 5.7422 1.5728
-#> 435: 93.5116 -5.9231 -0.1459 2.2424 -0.9691 3.4672 3.3376 0.3191 0.3727 0.1877 5.7424 1.5726
-#> 436: 93.5111 -5.9228 -0.1459 2.2425 -0.9692 3.4658 3.3352 0.3190 0.3727 0.1876 5.7429 1.5725
-#> 437: 93.5100 -5.9227 -0.1459 2.2425 -0.9692 3.4651 3.3328 0.3190 0.3727 0.1876 5.7430 1.5725
-#> 438: 93.5071 -5.9230 -0.1459 2.2425 -0.9692 3.4614 3.3329 0.3190 0.3728 0.1876 5.7437 1.5725
-#> 439: 93.5035 -5.9225 -0.1459 2.2426 -0.9691 3.4555 3.3298 0.3190 0.3728 0.1875 5.7449 1.5725
-#> 440: 93.5006 -5.9222 -0.1459 2.2426 -0.9690 3.4503 3.3286 0.3190 0.3728 0.1874 5.7461 1.5723
-#> 441: 93.4988 -5.9220 -0.1459 2.2427 -0.9689 3.4445 3.3272 0.3190 0.3728 0.1874 5.7466 1.5721
-#> 442: 93.4971 -5.9216 -0.1459 2.2428 -0.9688 3.4392 3.3265 0.3190 0.3728 0.1874 5.7475 1.5721
-#> 443: 93.4957 -5.9214 -0.1458 2.2429 -0.9688 3.4338 3.3256 0.3190 0.3729 0.1874 5.7487 1.5723
-#> 444: 93.4949 -5.9210 -0.1458 2.2430 -0.9688 3.4288 3.3236 0.3189 0.3729 0.1874 5.7502 1.5721
-#> 445: 93.4932 -5.9210 -0.1458 2.2430 -0.9687 3.4283 3.3237 0.3189 0.3731 0.1874 5.7516 1.5719
-#> 446: 93.4922 -5.9205 -0.1458 2.2430 -0.9687 3.4253 3.3215 0.3188 0.3733 0.1873 5.7524 1.5717
-#> 447: 93.4917 -5.9205 -0.1458 2.2430 -0.9686 3.4257 3.3213 0.3187 0.3736 0.1873 5.7528 1.5715
-#> 448: 93.4924 -5.9205 -0.1458 2.2430 -0.9685 3.4296 3.3209 0.3186 0.3737 0.1872 5.7532 1.5717
-#> 449: 93.4920 -5.9203 -0.1459 2.2430 -0.9684 3.4302 3.3194 0.3185 0.3739 0.1872 5.7542 1.5717
-#> 450: 93.4915 -5.9207 -0.1459 2.2430 -0.9684 3.4314 3.3217 0.3184 0.3741 0.1871 5.7551 1.5715
-#> 451: 93.4915 -5.9214 -0.1459 2.2430 -0.9684 3.4371 3.3253 0.3183 0.3743 0.1871 5.7562 1.5717
-#> 452: 93.4926 -5.9212 -0.1458 2.2430 -0.9683 3.4417 3.3242 0.3182 0.3745 0.1870 5.7567 1.5717
-#> 453: 93.4935 -5.9211 -0.1459 2.2430 -0.9683 3.4413 3.3232 0.3182 0.3746 0.1870 5.7574 1.5714
-#> 454: 93.4941 -5.9209 -0.1459 2.2429 -0.9683 3.4406 3.3222 0.3182 0.3748 0.1870 5.7580 1.5713
-#> 455: 93.4947 -5.9212 -0.1459 2.2429 -0.9684 3.4450 3.3232 0.3181 0.3750 0.1870 5.7580 1.5710
-#> 456: 93.4950 -5.9214 -0.1459 2.2429 -0.9684 3.4481 3.3236 0.3181 0.3751 0.1870 5.7585 1.5708
-#> 457: 93.4961 -5.9220 -0.1459 2.2429 -0.9685 3.4516 3.3266 0.3180 0.3752 0.1869 5.7590 1.5707
-#> 458: 93.4965 -5.9218 -0.1459 2.2428 -0.9685 3.4553 3.3257 0.3179 0.3753 0.1869 5.7589 1.5707
-#> 459: 93.4959 -5.9212 -0.1459 2.2428 -0.9685 3.4572 3.3229 0.3178 0.3754 0.1868 5.7596 1.5705
-#> 460: 93.4960 -5.9209 -0.1459 2.2428 -0.9685 3.4573 3.3209 0.3178 0.3755 0.1868 5.7598 1.5704
-#> 461: 93.4944 -5.9211 -0.1459 2.2428 -0.9685 3.4592 3.3202 0.3177 0.3757 0.1868 5.7609 1.5701
-#> 462: 93.4941 -5.9214 -0.1459 2.2428 -0.9686 3.4630 3.3206 0.3176 0.3759 0.1868 5.7617 1.5700
-#> 463: 93.4932 -5.9215 -0.1459 2.2429 -0.9686 3.4708 3.3197 0.3175 0.3761 0.1868 5.7622 1.5699
-#> 464: 93.4933 -5.9209 -0.1459 2.2429 -0.9685 3.4759 3.3162 0.3175 0.3762 0.1869 5.7628 1.5696
-#> 465: 93.4928 -5.9204 -0.1459 2.2428 -0.9685 3.4794 3.3133 0.3174 0.3764 0.1870 5.7642 1.5693
-#> 466: 93.4934 -5.9197 -0.1460 2.2428 -0.9685 3.4838 3.3105 0.3173 0.3766 0.1870 5.7659 1.5693
-#> 467: 93.4931 -5.9197 -0.1460 2.2428 -0.9685 3.4866 3.3094 0.3172 0.3768 0.1871 5.7667 1.5691
-#> 468: 93.4933 -5.9198 -0.1460 2.2428 -0.9685 3.4916 3.3099 0.3172 0.3769 0.1871 5.7672 1.5690
-#> 469: 93.4936 -5.9200 -0.1461 2.2427 -0.9685 3.4929 3.3119 0.3171 0.3771 0.1871 5.7681 1.5689
-#> 470: 93.4938 -5.9200 -0.1461 2.2427 -0.9685 3.4931 3.3111 0.3171 0.3773 0.1871 5.7685 1.5687
-#> 471: 93.4943 -5.9198 -0.1461 2.2427 -0.9685 3.4932 3.3097 0.3170 0.3776 0.1871 5.7681 1.5686
-#> 472: 93.4931 -5.9197 -0.1461 2.2427 -0.9684 3.4923 3.3092 0.3170 0.3778 0.1870 5.7683 1.5686
-#> 473: 93.4928 -5.9193 -0.1461 2.2426 -0.9684 3.4918 3.3068 0.3169 0.3781 0.1870 5.7690 1.5685
-#> 474: 93.4920 -5.9193 -0.1462 2.2426 -0.9683 3.4878 3.3075 0.3169 0.3781 0.1870 5.7687 1.5688
-#> 475: 93.4909 -5.9191 -0.1463 2.2425 -0.9683 3.4868 3.3069 0.3169 0.3782 0.1869 5.7681 1.5692
-#> 476: 93.4887 -5.9190 -0.1464 2.2424 -0.9682 3.4881 3.3072 0.3169 0.3783 0.1869 5.7673 1.5694
-#> 477: 93.4875 -5.9185 -0.1465 2.2423 -0.9681 3.4847 3.3059 0.3169 0.3784 0.1868 5.7667 1.5696
-#> 478: 93.4867 -5.9182 -0.1466 2.2421 -0.9681 3.4804 3.3056 0.3170 0.3784 0.1867 5.7661 1.5700
-#> 479: 93.4865 -5.9178 -0.1468 2.2419 -0.9681 3.4768 3.3043 0.3171 0.3784 0.1867 5.7657 1.5702
-#> 480: 93.4863 -5.9181 -0.1469 2.2417 -0.9680 3.4733 3.3057 0.3172 0.3784 0.1866 5.7656 1.5702
-#> 481: 93.4865 -5.9182 -0.1470 2.2415 -0.9680 3.4694 3.3069 0.3173 0.3784 0.1866 5.7648 1.5705
-#> 482: 93.4871 -5.9187 -0.1472 2.2412 -0.9681 3.4667 3.3089 0.3173 0.3784 0.1865 5.7631 1.5709
-#> 483: 93.4860 -5.9192 -0.1473 2.2410 -0.9681 3.4668 3.3107 0.3174 0.3785 0.1865 5.7624 1.5709
-#> 484: 93.4858 -5.9193 -0.1474 2.2408 -0.9681 3.4681 3.3111 0.3174 0.3786 0.1864 5.7615 1.5713
-#> 485: 93.4858 -5.9195 -0.1476 2.2406 -0.9681 3.4643 3.3110 0.3174 0.3787 0.1864 5.7612 1.5717
-#> 486: 93.4853 -5.9198 -0.1477 2.2404 -0.9682 3.4665 3.3115 0.3174 0.3788 0.1864 5.7612 1.5717
-#> 487: 93.4856 -5.9201 -0.1478 2.2402 -0.9682 3.4687 3.3143 0.3173 0.3790 0.1864 5.7612 1.5719
-#> 488: 93.4858 -5.9209 -0.1479 2.2401 -0.9683 3.4688 3.3186 0.3173 0.3792 0.1864 5.7626 1.5722
-#> 489: 93.4870 -5.9211 -0.1480 2.2399 -0.9684 3.4681 3.3198 0.3174 0.3794 0.1863 5.7640 1.5725
-#> 490: 93.4881 -5.9213 -0.1481 2.2398 -0.9684 3.4694 3.3211 0.3174 0.3797 0.1864 5.7650 1.5728
-#> 491: 93.4892 -5.9210 -0.1482 2.2395 -0.9685 3.4716 3.3193 0.3173 0.3799 0.1864 5.7650 1.5732
-#> 492: 93.4907 -5.9211 -0.1483 2.2393 -0.9686 3.4754 3.3179 0.3173 0.3801 0.1865 5.7648 1.5736
-#> 493: 93.4928 -5.9215 -0.1484 2.2390 -0.9686 3.4858 3.3185 0.3173 0.3803 0.1865 5.7640 1.5738
-#> 494: 93.4937 -5.9217 -0.1485 2.2388 -0.9687 3.4940 3.3182 0.3172 0.3805 0.1865 5.7639 1.5740
-#> 495: 93.4945 -5.9213 -0.1485 2.2386 -0.9688 3.4998 3.3151 0.3172 0.3808 0.1866 5.7638 1.5742
-#> 496: 93.4953 -5.9208 -0.1486 2.2384 -0.9688 3.5036 3.3123 0.3172 0.3810 0.1867 5.7635 1.5745
-#> 497: 93.4969 -5.9205 -0.1487 2.2382 -0.9689 3.5064 3.3109 0.3172 0.3813 0.1868 5.7637 1.5747
-#> 498: 93.4980 -5.9205 -0.1488 2.2379 -0.9690 3.5057 3.3104 0.3171 0.3815 0.1868 5.7639 1.5752
-#> 499: 93.4999 -5.9205 -0.1488 2.2377 -0.9691 3.5095 3.3102 0.3171 0.3817 0.1869 5.7639 1.5756
-#> 500: 93.5013 -5.9210 -0.1489 2.2376 -0.9691 3.5093 3.3135 0.3171 0.3818 0.1869 5.7644 1.5758
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.4067 -5.7935 -0.0604 2.2993 -1.1624 2.9450 1.7342 0.6650 0.5890 0.4750 14.5215 9.1023
+#> 2: 93.8811 -5.7873 -0.0289 2.3640 -1.0762 2.7977 2.0710 0.6317 0.5595 0.4512 11.1033 4.6425
+#> 3: 94.0397 -5.9934 0.0119 2.4035 -1.0703 3.0693 2.4524 0.6124 0.5316 0.4287 10.0698 3.4243
+#> 4: 93.8834 -6.0401 0.0041 2.3944 -1.0097 2.9159 3.1645 0.6120 0.5050 0.4073 9.2013 3.2162
+#> 5: 94.0163 -5.8381 -0.0267 2.3580 -1.0239 2.7701 3.0063 0.5814 0.4797 0.3869 9.0330 3.0330
+#> 6: 93.9753 -5.8371 -0.0315 2.3598 -1.0052 2.6316 2.8559 0.5708 0.4558 0.3675 8.6051 2.6518
+#> 7: 93.6109 -5.8741 -0.0401 2.3570 -1.0025 2.5000 2.7131 0.5691 0.4330 0.3492 8.4407 2.4701
+#> 8: 93.2480 -6.0361 -0.0523 2.3504 -1.0028 2.3750 3.1584 0.5407 0.4113 0.3317 8.6121 2.2437
+#> 9: 93.2245 -6.0431 -0.0503 2.3552 -0.9828 2.2562 3.9790 0.5395 0.3908 0.3151 8.6609 2.1129
+#> 10: 93.3040 -6.1080 -0.0503 2.3613 -0.9784 2.1434 4.8606 0.5401 0.3712 0.2994 8.6497 2.0865
+#> 11: 93.4509 -5.9532 -0.0503 2.3444 -0.9823 3.0948 4.6176 0.5679 0.3527 0.2844 8.1651 2.0310
+#> 12: 93.5099 -6.1699 -0.0503 2.3408 -0.9746 3.2814 4.3867 0.5679 0.3350 0.2702 8.1716 1.9862
+#> 13: 93.8052 -6.1984 -0.0474 2.3233 -0.9922 3.1173 4.6967 0.5644 0.3183 0.2567 8.2982 2.0040
+#> 14: 93.6510 -6.0090 -0.0429 2.3601 -0.9885 2.9615 4.4618 0.5526 0.3024 0.2438 8.3254 2.0605
+#> 15: 93.8952 -6.3354 -0.0394 2.3580 -0.9792 2.8134 5.2117 0.5657 0.2872 0.2316 8.1329 2.0520
+#> 16: 93.4703 -6.0722 -0.0434 2.3386 -1.0026 2.6727 4.9512 0.5781 0.2729 0.2201 8.0866 2.0994
+#> 17: 93.4238 -6.2132 -0.0755 2.3120 -1.0119 2.5391 4.7036 0.5495 0.2592 0.2091 7.5958 2.2864
+#> 18: 93.5288 -6.2747 -0.0616 2.3223 -1.0105 2.4121 4.4684 0.5467 0.2463 0.1986 7.1910 1.9828
+#> 19: 93.2607 -6.3635 -0.0631 2.3206 -1.0045 3.6271 4.8142 0.5405 0.2340 0.1928 7.3672 1.8187
+#> 20: 93.3918 -6.3241 -0.0742 2.2941 -1.0140 3.4457 4.9242 0.5596 0.2223 0.1950 7.1427 1.8754
+#> 21: 93.6794 -6.1336 -0.0758 2.3000 -1.0048 3.2734 4.6780 0.5565 0.2111 0.1852 7.0989 1.9232
+#> 22: 94.0006 -6.1882 -0.0800 2.3099 -1.0252 3.1098 4.4441 0.5354 0.2006 0.1870 7.0038 1.9920
+#> 23: 93.6433 -6.2626 -0.0841 2.2791 -1.0183 4.8893 4.4476 0.5276 0.1906 0.1798 6.3698 1.8787
+#> 24: 93.9545 -6.3772 -0.0816 2.2887 -1.0019 4.6448 5.1698 0.5293 0.1810 0.1779 6.5903 1.9474
+#> 25: 94.2280 -6.3235 -0.0839 2.2600 -0.9932 5.2801 4.9113 0.5262 0.1720 0.1806 6.5267 1.9807
+#> 26: 94.2022 -6.2830 -0.0883 2.2643 -1.0012 5.9595 4.6658 0.5225 0.1634 0.1795 6.3678 1.9659
+#> 27: 94.4398 -6.1769 -0.0894 2.2564 -1.0177 9.0771 4.4325 0.5207 0.1552 0.1880 6.4522 1.8590
+#> 28: 94.2586 -6.1652 -0.0882 2.2574 -1.0226 8.6233 4.2108 0.5158 0.1475 0.1881 6.3701 1.7882
+#> 29: 94.3490 -6.1505 -0.0854 2.2615 -1.0081 9.6333 4.0003 0.5109 0.1423 0.1833 6.3601 1.8485
+#> 30: 94.6929 -6.0285 -0.0909 2.2610 -1.0082 9.1517 3.8003 0.5117 0.1401 0.2097 6.2461 1.8606
+#> 31: 94.2553 -6.0390 -0.0896 2.2625 -1.0078 8.6941 3.6103 0.5072 0.1378 0.2088 6.3337 1.8220
+#> 32: 94.3096 -5.7252 -0.0886 2.2677 -0.9967 9.0244 3.4298 0.5051 0.1325 0.2015 6.4601 1.8880
+#> 33: 94.8327 -5.8775 -0.0865 2.2684 -0.9976 8.6305 3.2583 0.4920 0.1333 0.1993 6.4804 1.8203
+#> 34: 94.3527 -5.9488 -0.0826 2.2879 -0.9989 8.1989 3.1538 0.4969 0.1388 0.1984 6.4201 1.7696
+#> 35: 94.4411 -6.1171 -0.0826 2.2913 -0.9964 8.4377 3.7937 0.4969 0.1387 0.1972 6.3878 1.7612
+#> 36: 94.2058 -6.1151 -0.0844 2.2920 -1.0069 8.0158 3.7963 0.4962 0.1395 0.1938 6.2469 1.6680
+#> 37: 93.7449 -6.1251 -0.0925 2.2736 -1.0019 7.6150 3.8477 0.5101 0.1325 0.1841 6.1375 1.7472
+#> 38: 93.6861 -6.0575 -0.0934 2.2803 -1.0097 7.2343 3.6553 0.5119 0.1259 0.1862 6.0729 1.7608
+#> 39: 93.9767 -6.0314 -0.0999 2.2548 -1.0231 6.8726 3.4725 0.5195 0.1234 0.1951 6.1947 1.8276
+#> 40: 94.0297 -6.1559 -0.0989 2.2440 -1.0374 6.5290 3.8559 0.5199 0.1279 0.1891 6.0195 1.8906
+#> 41: 94.2069 -6.3055 -0.0820 2.2710 -1.0275 6.2025 4.7866 0.5304 0.1215 0.1858 6.1777 1.8541
+#> 42: 94.2400 -6.3179 -0.0790 2.2783 -1.0379 5.8924 4.6915 0.5253 0.1154 0.1794 6.0530 1.8960
+#> 43: 93.9851 -6.4096 -0.0784 2.2832 -1.0341 5.5978 5.0608 0.5163 0.1097 0.1773 6.0057 1.8136
+#> 44: 94.1440 -6.2214 -0.0746 2.2969 -1.0262 5.3179 4.8077 0.5130 0.1079 0.1851 6.1182 1.8390
+#> 45: 93.8847 -6.3883 -0.0745 2.3059 -1.0132 6.8202 5.1378 0.5130 0.1174 0.1769 6.1000 1.8391
+#> 46: 93.7228 -6.3305 -0.0794 2.3033 -1.0107 6.4792 4.8809 0.5095 0.1196 0.1783 6.2794 1.7304
+#> 47: 93.7031 -6.4232 -0.0796 2.3006 -1.0028 6.1552 5.5756 0.5092 0.1243 0.1887 6.1716 1.7279
+#> 48: 93.5210 -6.2770 -0.0794 2.2948 -1.0122 5.8475 5.2968 0.5098 0.1247 0.1863 5.9847 1.7994
+#> 49: 93.3676 -6.4486 -0.0754 2.3079 -1.0061 5.5551 5.4356 0.5018 0.1198 0.1858 6.1108 1.7598
+#> 50: 93.8573 -6.3944 -0.0755 2.3057 -1.0038 5.2773 5.2487 0.5063 0.1193 0.1843 6.0935 1.7725
+#> 51: 93.7004 -6.2783 -0.0854 2.2836 -1.0074 5.0135 4.9863 0.4932 0.1269 0.1858 6.1630 1.8063
+#> 52: 93.4843 -6.3763 -0.0962 2.2731 -1.0073 4.7628 5.0969 0.4815 0.1345 0.1924 6.0823 1.8013
+#> 53: 93.6971 -6.5002 -0.0887 2.2774 -1.0111 4.5246 5.7428 0.4726 0.1346 0.1982 6.1744 1.7695
+#> 54: 93.6176 -6.4928 -0.0917 2.2648 -1.0220 4.2984 5.4557 0.4765 0.1419 0.2017 6.3732 1.8195
+#> 55: 93.7072 -6.5760 -0.0833 2.2865 -1.0282 4.0835 5.9775 0.4732 0.1434 0.1963 6.3653 1.7028
+#> 56: 94.1360 -6.6854 -0.0901 2.2941 -1.0244 3.8793 7.2562 0.4637 0.1393 0.1935 6.3001 1.7878
+#> 57: 93.4627 -6.6255 -0.1049 2.2502 -1.0233 3.6854 6.8934 0.4847 0.1323 0.1878 6.2357 1.8480
+#> 58: 93.8066 -6.6603 -0.1049 2.2362 -1.0280 3.5011 6.9334 0.4847 0.1397 0.1872 6.3582 1.7787
+#> 59: 93.8599 -6.7837 -0.1046 2.2450 -1.0274 3.3260 8.4672 0.4853 0.1332 0.1833 6.1248 1.8066
+#> 60: 93.6190 -6.5618 -0.1055 2.2381 -1.0244 3.1597 8.0438 0.4742 0.1390 0.1858 6.2589 1.7881
+#> 61: 93.7045 -6.6482 -0.1159 2.2413 -1.0272 3.2942 7.8485 0.4655 0.1406 0.1827 5.8425 1.7744
+#> 62: 93.5232 -6.5027 -0.1168 2.2418 -1.0187 3.3810 7.4560 0.4766 0.1414 0.1790 5.9349 1.7717
+#> 63: 93.4884 -6.4221 -0.1164 2.2505 -1.0062 3.2119 7.0832 0.4768 0.1422 0.1752 6.0193 1.7434
+#> 64: 93.2305 -6.4456 -0.1153 2.2573 -1.0062 4.1468 6.7291 0.4776 0.1395 0.1753 5.8355 1.7529
+#> 65: 93.3743 -6.3237 -0.1227 2.2484 -1.0102 3.9395 6.3926 0.4864 0.1374 0.1800 5.6731 1.7808
+#> 66: 93.7132 -6.3178 -0.1186 2.2389 -0.9894 4.0557 6.0730 0.4909 0.1426 0.1807 5.7099 1.7283
+#> 67: 93.7490 -6.3514 -0.1155 2.2445 -0.9946 3.8529 5.7693 0.4938 0.1379 0.1830 5.7366 1.7847
+#> 68: 93.7617 -6.1181 -0.1251 2.2487 -0.9841 3.7650 5.4809 0.4816 0.1549 0.1769 5.6569 1.7415
+#> 69: 93.4342 -6.3588 -0.1301 2.2350 -0.9813 4.5688 5.2068 0.4745 0.1624 0.1736 5.5771 1.7091
+#> 70: 93.5303 -6.3266 -0.1330 2.2384 -0.9753 4.3404 4.9465 0.4734 0.1563 0.1699 5.5332 1.7256
+#> 71: 93.4733 -6.2859 -0.1364 2.2170 -0.9781 4.1234 4.6992 0.4701 0.1604 0.1649 5.6661 1.7335
+#> 72: 93.3055 -6.2502 -0.1462 2.2156 -0.9724 3.9172 4.7693 0.4519 0.1607 0.1582 5.4776 1.7679
+#> 73: 93.3010 -6.6844 -0.1490 2.2262 -0.9777 3.7213 6.9975 0.4426 0.1848 0.1640 5.7066 1.7588
+#> 74: 93.1104 -6.6720 -0.1484 2.2079 -0.9982 3.5353 6.7811 0.4436 0.1807 0.1732 5.7700 1.7343
+#> 75: 93.4534 -6.9644 -0.1480 2.2078 -0.9930 3.3585 8.7027 0.4497 0.1717 0.1708 5.5371 1.7098
+#> 76: 93.5886 -6.3503 -0.1491 2.1958 -0.9884 3.7136 8.2676 0.4509 0.1731 0.1706 5.3943 1.7340
+#> 77: 93.4345 -6.4976 -0.1531 2.1831 -0.9928 4.5945 7.8542 0.4592 0.1741 0.1703 5.5564 1.7164
+#> 78: 93.6007 -6.4885 -0.1538 2.1850 -0.9919 4.3647 7.4615 0.4607 0.1803 0.1692 5.4698 1.7354
+#> 79: 93.2897 -7.0329 -0.1518 2.1935 -0.9863 4.6922 10.9870 0.4569 0.1790 0.1608 5.3799 1.7484
+#> 80: 93.4130 -6.6634 -0.1531 2.1865 -0.9839 5.4720 10.4377 0.4585 0.1852 0.1543 5.4298 1.7237
+#> 81: 93.5828 -6.7204 -0.1563 2.1914 -0.9882 5.1984 9.9158 0.4548 0.1973 0.1600 5.4425 1.7741
+#> 82: 93.4450 -6.7357 -0.1537 2.1964 -0.9958 4.9384 10.1331 0.4577 0.1874 0.1632 5.6874 1.7789
+#> 83: 93.6109 -6.9249 -0.1493 2.2061 -0.9945 4.6915 11.1537 0.4474 0.1781 0.1686 5.4249 1.7317
+#> 84: 93.7133 -6.8029 -0.1493 2.2016 -0.9886 4.4569 10.9568 0.4474 0.1715 0.1689 5.5426 1.7227
+#> 85: 93.8040 -6.6434 -0.1483 2.2032 -0.9861 5.4991 10.4090 0.4330 0.1749 0.1726 5.4570 1.7332
+#> 86: 93.9029 -6.7750 -0.1472 2.2066 -0.9892 5.2241 11.7325 0.4352 0.1819 0.1644 5.5652 1.6802
+#> 87: 93.8127 -6.7015 -0.1499 2.2019 -0.9891 4.9629 11.1459 0.4292 0.1977 0.1661 5.7122 1.6713
+#> 88: 93.6777 -6.7044 -0.1440 2.2074 -1.0050 4.7148 10.5886 0.4379 0.1878 0.1750 5.6084 1.7096
+#> 89: 94.0481 -6.2990 -0.1443 2.2085 -0.9869 4.4790 10.0591 0.4355 0.1951 0.1688 5.4280 1.8093
+#> 90: 93.6399 -6.3965 -0.1429 2.2138 -0.9737 5.1306 9.5562 0.4367 0.1917 0.1604 5.5652 1.7458
+#> 91: 93.8670 -6.3075 -0.1426 2.2128 -0.9856 5.1368 9.0784 0.4427 0.1993 0.1546 5.3927 1.8246
+#> 92: 93.7332 -6.4793 -0.1426 2.2091 -0.9835 5.0102 8.6245 0.4427 0.1986 0.1585 5.4463 1.7343
+#> 93: 93.8211 -6.3270 -0.1416 2.2123 -0.9941 4.7597 8.1932 0.4431 0.1908 0.1689 5.5213 1.7093
+#> 94: 93.7499 -6.0880 -0.1390 2.2158 -0.9960 5.1992 7.7836 0.4444 0.1958 0.1733 5.5329 1.7880
+#> 95: 93.6253 -6.2196 -0.1436 2.2126 -1.0053 4.9392 7.3944 0.4383 0.2011 0.1717 5.6042 1.7460
+#> 96: 93.8862 -6.1475 -0.1408 2.2211 -0.9922 4.6923 7.0247 0.4347 0.2077 0.1669 5.6807 1.6943
+#> 97: 93.7610 -6.2409 -0.1368 2.2281 -0.9864 4.4576 6.6734 0.4313 0.2084 0.1723 5.5387 1.7075
+#> 98: 93.5362 -6.3378 -0.1368 2.2294 -0.9813 4.2348 6.3398 0.4313 0.2127 0.1877 5.5850 1.6627
+#> 99: 93.5044 -6.2557 -0.1311 2.2282 -0.9993 4.0230 6.0228 0.4461 0.2167 0.1879 5.6437 1.7076
+#> 100: 93.3102 -6.3602 -0.1311 2.2368 -1.0040 3.8219 5.7216 0.4461 0.2139 0.1875 5.8029 1.7592
+#> 101: 93.4687 -6.0385 -0.1241 2.2347 -1.0031 3.6308 5.4356 0.4483 0.2035 0.1816 6.0097 1.7002
+#> 102: 93.6536 -6.2867 -0.1299 2.2421 -1.0002 3.4492 5.1743 0.4434 0.1993 0.1872 5.8540 1.7162
+#> 103: 93.9532 -6.2261 -0.1277 2.2361 -0.9931 3.2768 5.0546 0.4450 0.2069 0.1884 5.6688 1.7324
+#> 104: 93.9839 -6.1980 -0.1287 2.2286 -1.0081 3.1129 5.0671 0.4475 0.1997 0.1985 5.7690 1.7636
+#> 105: 94.1682 -6.1671 -0.1283 2.2217 -1.0154 2.9573 4.8137 0.4481 0.1976 0.1965 5.9277 1.7386
+#> 106: 94.2778 -6.1839 -0.1243 2.2323 -1.0022 3.5381 4.5730 0.4707 0.1980 0.1932 5.7059 1.7184
+#> 107: 94.3667 -5.9941 -0.1182 2.2283 -1.0191 3.3612 4.3444 0.4753 0.1984 0.1986 5.7813 1.7446
+#> 108: 94.2722 -6.1869 -0.1171 2.2293 -1.0027 3.6659 4.6329 0.4742 0.1986 0.2011 5.7827 1.7074
+#> 109: 94.1997 -6.2385 -0.1172 2.2241 -1.0083 3.4826 4.7954 0.4721 0.2027 0.2020 5.8339 1.7650
+#> 110: 94.3017 -6.3774 -0.1291 2.2229 -0.9857 3.7634 5.8516 0.4810 0.2126 0.1984 5.7961 1.6706
+#> 111: 93.9803 -6.0240 -0.1258 2.2273 -0.9879 3.5752 5.5590 0.4749 0.2060 0.1976 5.6243 1.7082
+#> 112: 94.1307 -6.0036 -0.1253 2.2365 -0.9886 4.0368 5.2810 0.4760 0.2060 0.1975 5.5732 1.7063
+#> 113: 93.8676 -6.2496 -0.1118 2.2600 -1.0080 3.8350 5.0170 0.4855 0.2109 0.2006 5.6406 1.7357
+#> 114: 93.5949 -6.3200 -0.1044 2.2449 -1.0172 3.6472 4.7661 0.4868 0.2095 0.2131 5.7690 1.7428
+#> 115: 93.6997 -6.3282 -0.1046 2.2567 -1.0135 3.4648 4.8622 0.4876 0.2264 0.2134 5.8853 1.7823
+#> 116: 93.8191 -6.0802 -0.1087 2.2535 -1.0011 3.4347 4.6191 0.4786 0.2176 0.2108 5.6553 1.7802
+#> 117: 93.8575 -6.0930 -0.1022 2.2498 -0.9898 3.3071 4.3881 0.4822 0.2163 0.2075 5.7806 1.8150
+#> 118: 93.9164 -5.9787 -0.1133 2.2535 -0.9861 4.2578 4.1687 0.4687 0.2198 0.2088 5.4441 1.8411
+#> 119: 93.8748 -6.0108 -0.1165 2.2488 -0.9775 4.0449 3.9603 0.4653 0.2271 0.2032 5.6119 1.7501
+#> 120: 93.6001 -6.0447 -0.1144 2.2477 -0.9821 3.8426 3.7623 0.4641 0.2223 0.2055 5.6454 1.7244
+#> 121: 93.6712 -5.9851 -0.1195 2.2484 -0.9917 3.6505 3.5742 0.4600 0.2143 0.2010 5.4083 1.7965
+#> 122: 93.6859 -6.0390 -0.1145 2.2497 -0.9888 3.4680 3.5595 0.4618 0.2136 0.1986 5.4111 1.7519
+#> 123: 93.6014 -5.8383 -0.1145 2.2584 -0.9893 3.6047 3.3815 0.4618 0.2155 0.2045 5.3624 1.7023
+#> 124: 93.6333 -5.7861 -0.1131 2.2556 -0.9872 3.4245 3.2125 0.4621 0.2153 0.2025 5.3930 1.7036
+#> 125: 93.4504 -5.9483 -0.1154 2.2531 -0.9924 3.2533 3.0518 0.4640 0.2175 0.2030 5.5097 1.6830
+#> 126: 93.5693 -5.8818 -0.1120 2.2506 -0.9960 3.0906 2.8992 0.4606 0.2267 0.2016 5.4583 1.6650
+#> 127: 93.7074 -5.8191 -0.1178 2.2412 -0.9891 2.9361 2.7543 0.4688 0.2234 0.2039 5.4861 1.8125
+#> 128: 93.5959 -5.8842 -0.1179 2.2544 -0.9985 3.0224 2.6166 0.4700 0.2237 0.2019 5.6417 1.8454
+#> 129: 93.5600 -5.8683 -0.1161 2.2365 -0.9987 3.4186 2.4857 0.4721 0.2182 0.1918 5.4391 1.8145
+#> 130: 93.4104 -5.8226 -0.1126 2.2355 -0.9892 3.3648 2.4231 0.4763 0.2212 0.1873 5.3999 1.7457
+#> 131: 93.5045 -5.7255 -0.1118 2.2486 -0.9918 4.1951 2.3020 0.4776 0.2121 0.1927 5.4342 1.7744
+#> 132: 93.2626 -5.8379 -0.1097 2.2510 -0.9933 3.9853 2.5572 0.4763 0.2114 0.1966 5.2979 1.7239
+#> 133: 93.4370 -5.9097 -0.1049 2.2578 -0.9939 4.2190 2.8246 0.4738 0.2036 0.2020 5.2853 1.6765
+#> 134: 93.8665 -5.9439 -0.1035 2.2654 -0.9832 4.0081 3.1228 0.4756 0.2102 0.1961 5.3467 1.7177
+#> 135: 93.6301 -5.8062 -0.1031 2.2702 -0.9737 3.9024 2.9667 0.4748 0.2101 0.2003 5.3053 1.6977
+#> 136: 93.7744 -5.9328 -0.1055 2.2685 -0.9764 3.7072 2.9952 0.4721 0.2096 0.1949 5.4319 1.6864
+#> 137: 93.6734 -5.9886 -0.1107 2.2517 -0.9732 3.8811 3.4962 0.4642 0.2204 0.1924 5.4294 1.6684
+#> 138: 93.7128 -5.9927 -0.1119 2.2517 -0.9775 3.6870 3.4543 0.4667 0.2204 0.1953 5.3912 1.7060
+#> 139: 93.6530 -6.1296 -0.1210 2.2456 -0.9929 3.5027 4.6472 0.4527 0.2296 0.1855 5.4953 1.7242
+#> 140: 93.9344 -6.2519 -0.1384 2.2304 -0.9970 3.6814 4.4707 0.4337 0.2182 0.1762 5.5643 1.7596
+#> 141: 93.7356 -6.2804 -0.1296 2.2549 -0.9921 3.9811 4.4876 0.4218 0.2361 0.1674 5.3531 1.7175
+#> 142: 93.7399 -6.0023 -0.1098 2.2611 -0.9815 3.7821 4.2632 0.4395 0.2421 0.1807 5.3139 1.7191
+#> 143: 93.4732 -6.0376 -0.1108 2.2689 -0.9734 3.5930 4.0500 0.4396 0.2541 0.1718 5.2930 1.6229
+#> 144: 93.4900 -5.9517 -0.1093 2.2876 -0.9675 3.4133 3.8475 0.4337 0.2542 0.1711 5.4258 1.5660
+#> 145: 93.4090 -5.9596 -0.1000 2.2942 -0.9756 3.2426 3.6551 0.4274 0.2422 0.1671 5.3539 1.6971
+#> 146: 93.4142 -5.9549 -0.0982 2.2846 -0.9704 3.0805 3.6092 0.4226 0.2339 0.1745 5.5092 1.6696
+#> 147: 93.4409 -6.0720 -0.0971 2.2942 -0.9891 2.9265 3.9922 0.4224 0.2373 0.1781 5.5599 1.6080
+#> 148: 93.4504 -6.2201 -0.0980 2.2855 -0.9832 2.7802 4.6985 0.4104 0.2464 0.1856 5.5016 1.5877
+#> 149: 93.4240 -6.2122 -0.1005 2.2728 -0.9881 3.7659 4.7755 0.4082 0.2642 0.1885 5.4942 1.5534
+#> 150: 93.5094 -6.1295 -0.1087 2.2717 -0.9941 3.5776 4.5367 0.4109 0.2611 0.1928 5.3468 1.5585
+#> 151: 93.4038 -6.2751 -0.1130 2.2643 -0.9892 3.3987 4.9866 0.4172 0.2638 0.1905 5.4955 1.6256
+#> 152: 93.5072 -6.3361 -0.1147 2.2627 -0.9988 2.3580 5.3824 0.4175 0.2656 0.1819 5.7685 1.6126
+#> 153: 93.3582 -6.2019 -0.1227 2.2526 -0.9929 2.5874 4.7052 0.4348 0.2621 0.1810 5.5149 1.6181
+#> 154: 93.1890 -6.3537 -0.1263 2.2446 -0.9871 2.4073 5.7070 0.4351 0.2586 0.1829 5.3136 1.6272
+#> 155: 93.1706 -6.4117 -0.1260 2.2484 -0.9845 2.3035 6.0004 0.4463 0.2586 0.1781 5.4260 1.6494
+#> 156: 93.3240 -6.3931 -0.1259 2.2469 -0.9824 2.5659 5.7375 0.4466 0.2781 0.1754 5.6202 1.6591
+#> 157: 93.3239 -6.1812 -0.1242 2.2541 -0.9743 1.6054 4.5906 0.4478 0.2657 0.1758 5.6806 1.6367
+#> 158: 93.3756 -6.2562 -0.1264 2.2706 -0.9888 1.5329 4.6790 0.4458 0.2532 0.1728 5.7756 1.6248
+#> 159: 93.3034 -6.3291 -0.1217 2.2524 -0.9954 1.7774 5.7204 0.4532 0.2642 0.1715 5.8189 1.6830
+#> 160: 93.4387 -6.5115 -0.1196 2.2488 -0.9846 2.2219 6.4960 0.4555 0.2728 0.1689 5.5273 1.6332
+#> 161: 93.7646 -6.3820 -0.1231 2.2520 -0.9837 2.8322 5.7269 0.4498 0.2712 0.1730 5.3659 1.5787
+#> 162: 93.6252 -6.4563 -0.1243 2.2472 -0.9867 2.8322 5.9119 0.4502 0.2671 0.1726 5.4519 1.5819
+#> 163: 93.6787 -6.6444 -0.1292 2.2366 -0.9899 2.0520 7.4835 0.4556 0.2705 0.1689 5.4095 1.5883
+#> 164: 93.7458 -6.9330 -0.1257 2.2430 -0.9872 1.7825 9.4340 0.4495 0.2701 0.1593 5.4517 1.6116
+#> 165: 93.7370 -6.9118 -0.1250 2.2421 -0.9832 1.9949 10.6549 0.4499 0.2685 0.1622 5.6272 1.6075
+#> 166: 94.0889 -6.8704 -0.1276 2.2409 -0.9872 1.5618 10.4435 0.4482 0.2608 0.1648 5.5891 1.6208
+#> 167: 94.1319 -7.2779 -0.1206 2.2505 -0.9894 1.5063 13.4312 0.4393 0.2549 0.1661 5.6013 1.6043
+#> 168: 93.8341 -6.9310 -0.1140 2.2495 -0.9844 1.7329 11.3224 0.4463 0.2540 0.1629 5.8366 1.6765
+#> 169: 93.8923 -6.6547 -0.1173 2.2620 -0.9872 1.4531 8.4608 0.4419 0.2414 0.1666 5.8784 1.6268
+#> 170: 94.0072 -6.3970 -0.1173 2.2606 -0.9861 1.4164 6.9237 0.4419 0.2468 0.1656 5.8793 1.6387
+#> 171: 93.8690 -6.5151 -0.1079 2.2482 -0.9880 1.9225 7.7681 0.4547 0.2404 0.1523 6.0158 1.6281
+#> 172: 93.6847 -6.3416 -0.1095 2.2438 -0.9849 2.0143 5.5739 0.4498 0.2450 0.1534 6.1355 1.6422
+#> 173: 93.4817 -6.3165 -0.1115 2.2573 -0.9885 1.6855 5.5626 0.4440 0.2471 0.1542 6.1343 1.6337
+#> 174: 93.6781 -6.2722 -0.1113 2.2521 -0.9958 1.9186 5.3383 0.4471 0.2427 0.1565 6.1081 1.6358
+#> 175: 93.7764 -6.1664 -0.1113 2.2468 -0.9864 1.6286 4.6233 0.4471 0.2426 0.1596 5.8892 1.6375
+#> 176: 93.9246 -6.2164 -0.1160 2.2529 -0.9853 1.0357 4.8013 0.4422 0.2471 0.1756 5.7340 1.6016
+#> 177: 93.9711 -6.1274 -0.1112 2.2540 -0.9883 1.2079 4.1536 0.4415 0.2492 0.1783 5.8399 1.6291
+#> 178: 93.9212 -6.0532 -0.1116 2.2593 -0.9742 1.2409 3.6443 0.4489 0.2458 0.1683 5.8422 1.6290
+#> 179: 94.0137 -6.0739 -0.1095 2.2664 -0.9778 1.5060 3.9878 0.4506 0.2370 0.1746 6.0349 1.6326
+#> 180: 93.9247 -6.0681 -0.1130 2.2660 -0.9934 1.9619 3.9582 0.4474 0.2328 0.1773 5.8082 1.6740
+#> 181: 93.7150 -6.0191 -0.1153 2.2558 -0.9915 2.6849 3.7075 0.4491 0.2283 0.1759 5.7187 1.6842
+#> 182: 93.5908 -6.1098 -0.1111 2.2769 -0.9942 3.0096 3.9325 0.4643 0.2275 0.1736 5.9243 1.6466
+#> 183: 93.3386 -6.0987 -0.1131 2.2630 -0.9962 3.5457 4.1285 0.4693 0.2373 0.1751 5.6948 1.7222
+#> 184: 93.4889 -6.3097 -0.1134 2.2660 -0.9720 3.0855 5.2642 0.4648 0.2255 0.1585 5.6827 1.7444
+#> 185: 93.6387 -6.1883 -0.1188 2.2622 -0.9603 3.3568 4.8291 0.4554 0.2223 0.1681 5.7089 1.8164
+#> 186: 93.3420 -6.2909 -0.1195 2.2656 -0.9835 3.2124 4.8317 0.4541 0.2286 0.1531 5.7574 1.7708
+#> 187: 93.4395 -6.0358 -0.1165 2.2528 -0.9917 3.8299 3.3301 0.4518 0.2370 0.1593 5.8508 1.6988
+#> 188: 93.5358 -6.0105 -0.1161 2.2540 -0.9813 5.1249 3.3448 0.4522 0.2361 0.1660 5.8700 1.6525
+#> 189: 93.4932 -6.1199 -0.1129 2.2636 -0.9812 4.5430 4.3213 0.4428 0.2359 0.1907 5.6970 1.7268
+#> 190: 93.4754 -5.9088 -0.1171 2.2564 -0.9614 4.6253 3.2590 0.4410 0.2399 0.1864 5.7116 1.8140
+#> 191: 93.4709 -5.9676 -0.1171 2.2568 -0.9748 4.8326 3.6704 0.4410 0.2428 0.1812 5.5925 1.7267
+#> 192: 93.3895 -5.9940 -0.1191 2.2523 -0.9691 4.3019 3.5174 0.4360 0.2484 0.1591 5.4631 1.7057
+#> 193: 93.4904 -6.0400 -0.1173 2.2519 -0.9697 4.6476 3.6255 0.4389 0.2388 0.1694 5.5362 1.7174
+#> 194: 93.4591 -5.9642 -0.1245 2.2626 -0.9559 5.3125 3.8133 0.4297 0.2550 0.1660 5.7591 1.7344
+#> 195: 93.6610 -6.2211 -0.1226 2.2580 -0.9669 5.2051 4.9271 0.4318 0.2414 0.1811 5.7010 1.7710
+#> 196: 93.4249 -5.9570 -0.1068 2.2735 -0.9727 5.1049 3.4872 0.4442 0.2429 0.1815 5.7753 1.7379
+#> 197: 93.4082 -6.0568 -0.1054 2.2754 -0.9865 5.2827 3.9305 0.4554 0.2408 0.1925 5.7514 1.7163
+#> 198: 93.3856 -5.8616 -0.1087 2.2708 -0.9686 4.1369 3.0197 0.4530 0.2473 0.1878 5.6920 1.7043
+#> 199: 93.5488 -6.0494 -0.1167 2.2682 -0.9719 3.8010 3.8897 0.4600 0.2445 0.1860 5.7126 1.6605
+#> 200: 93.3779 -5.9779 -0.1110 2.2761 -0.9780 3.5955 3.4721 0.4595 0.2468 0.1941 5.7539 1.6736
+#> 201: 93.4946 -6.0259 -0.1102 2.2676 -0.9755 3.0583 3.7305 0.4592 0.2554 0.1921 5.8877 1.6730
+#> 202: 93.4698 -6.0522 -0.1110 2.2685 -0.9703 2.9421 3.8718 0.4579 0.2595 0.1906 5.8527 1.6701
+#> 203: 93.4625 -6.0744 -0.1132 2.2642 -0.9696 3.1854 4.0983 0.4589 0.2596 0.1886 5.7532 1.6655
+#> 204: 93.4984 -6.0853 -0.1138 2.2589 -0.9718 3.2826 4.1667 0.4581 0.2588 0.1851 5.7274 1.6694
+#> 205: 93.5279 -6.1054 -0.1151 2.2562 -0.9742 3.3257 4.2680 0.4569 0.2584 0.1832 5.6976 1.6777
+#> 206: 93.6025 -6.1087 -0.1174 2.2518 -0.9767 3.2399 4.2443 0.4582 0.2589 0.1822 5.6809 1.6775
+#> 207: 93.6382 -6.0990 -0.1204 2.2481 -0.9801 3.2768 4.1473 0.4579 0.2591 0.1823 5.6460 1.6819
+#> 208: 93.6250 -6.0878 -0.1224 2.2438 -0.9812 3.1815 4.0872 0.4579 0.2577 0.1818 5.6256 1.6887
+#> 209: 93.6102 -6.0740 -0.1255 2.2394 -0.9803 3.1716 3.9968 0.4561 0.2573 0.1812 5.6063 1.6886
+#> 210: 93.6005 -6.0571 -0.1277 2.2348 -0.9799 3.2408 3.8923 0.4548 0.2572 0.1798 5.5849 1.6912
+#> 211: 93.6270 -6.0425 -0.1306 2.2292 -0.9807 3.3500 3.8267 0.4538 0.2586 0.1792 5.5578 1.6992
+#> 212: 93.6641 -6.0403 -0.1331 2.2253 -0.9806 3.4487 3.8366 0.4529 0.2596 0.1786 5.5422 1.7022
+#> 213: 93.6743 -6.0344 -0.1354 2.2214 -0.9800 3.5484 3.8260 0.4518 0.2606 0.1781 5.5250 1.7069
+#> 214: 93.6719 -6.0405 -0.1377 2.2179 -0.9804 3.5538 3.8785 0.4506 0.2612 0.1769 5.5148 1.7087
+#> 215: 93.6743 -6.0403 -0.1396 2.2146 -0.9801 3.5578 3.9180 0.4496 0.2615 0.1761 5.5118 1.7094
+#> 216: 93.6666 -6.0436 -0.1413 2.2115 -0.9796 3.5848 3.9484 0.4488 0.2624 0.1755 5.5015 1.7116
+#> 217: 93.6715 -6.0438 -0.1430 2.2086 -0.9794 3.6188 3.9603 0.4478 0.2631 0.1748 5.4884 1.7132
+#> 218: 93.6765 -6.0488 -0.1441 2.2060 -0.9796 3.6126 3.9885 0.4471 0.2632 0.1746 5.4714 1.7156
+#> 219: 93.6714 -6.0557 -0.1453 2.2038 -0.9798 3.6603 4.0118 0.4463 0.2632 0.1735 5.4593 1.7235
+#> 220: 93.6728 -6.0711 -0.1462 2.2027 -0.9794 3.7244 4.0910 0.4457 0.2639 0.1730 5.4531 1.7241
+#> 221: 93.6723 -6.0822 -0.1470 2.2015 -0.9788 3.7754 4.1554 0.4450 0.2647 0.1724 5.4511 1.7247
+#> 222: 93.6789 -6.0745 -0.1480 2.1998 -0.9780 3.8735 4.1186 0.4442 0.2662 0.1718 5.4419 1.7258
+#> 223: 93.6891 -6.0700 -0.1488 2.1984 -0.9778 3.9353 4.0998 0.4434 0.2681 0.1715 5.4375 1.7251
+#> 224: 93.7125 -6.0705 -0.1496 2.1976 -0.9774 4.0220 4.0861 0.4427 0.2697 0.1711 5.4378 1.7230
+#> 225: 93.7332 -6.0695 -0.1502 2.1966 -0.9775 4.0553 4.0669 0.4422 0.2712 0.1711 5.4355 1.7205
+#> 226: 93.7631 -6.0712 -0.1508 2.1951 -0.9779 4.0755 4.0572 0.4417 0.2728 0.1712 5.4347 1.7190
+#> 227: 93.7912 -6.0687 -0.1512 2.1938 -0.9785 4.0621 4.0439 0.4409 0.2742 0.1716 5.4325 1.7189
+#> 228: 93.8077 -6.0644 -0.1517 2.1927 -0.9791 4.0246 4.0190 0.4400 0.2755 0.1722 5.4269 1.7193
+#> 229: 93.8255 -6.0661 -0.1521 2.1909 -0.9796 3.9958 4.0166 0.4392 0.2769 0.1725 5.4214 1.7214
+#> 230: 93.8403 -6.0766 -0.1530 2.1895 -0.9802 4.0152 4.0548 0.4380 0.2788 0.1730 5.4214 1.7232
+#> 231: 93.8549 -6.0768 -0.1541 2.1877 -0.9810 4.0690 4.0542 0.4368 0.2803 0.1734 5.4157 1.7236
+#> 232: 93.8666 -6.0728 -0.1550 2.1858 -0.9816 4.0852 4.0337 0.4356 0.2818 0.1736 5.4136 1.7224
+#> 233: 93.8728 -6.0672 -0.1557 2.1844 -0.9820 4.1001 4.0000 0.4346 0.2828 0.1738 5.4028 1.7243
+#> 234: 93.8862 -6.0646 -0.1563 2.1830 -0.9825 4.1303 3.9850 0.4337 0.2838 0.1737 5.3924 1.7222
+#> 235: 93.8862 -6.0632 -0.1570 2.1819 -0.9827 4.1149 3.9735 0.4329 0.2847 0.1737 5.3846 1.7225
+#> 236: 93.8827 -6.0639 -0.1577 2.1814 -0.9834 4.1004 3.9711 0.4322 0.2852 0.1739 5.3838 1.7220
+#> 237: 93.8729 -6.0680 -0.1582 2.1808 -0.9840 4.0606 3.9866 0.4316 0.2857 0.1741 5.3806 1.7213
+#> 238: 93.8739 -6.0733 -0.1587 2.1806 -0.9845 4.0331 4.0011 0.4311 0.2859 0.1742 5.3775 1.7199
+#> 239: 93.8732 -6.0729 -0.1591 2.1802 -0.9853 3.9850 3.9892 0.4307 0.2859 0.1744 5.3782 1.7216
+#> 240: 93.8760 -6.0754 -0.1595 2.1796 -0.9854 3.9349 3.9867 0.4303 0.2858 0.1747 5.3781 1.7232
+#> 241: 93.8779 -6.0749 -0.1599 2.1791 -0.9853 3.9241 3.9801 0.4299 0.2858 0.1748 5.3757 1.7228
+#> 242: 93.8842 -6.0716 -0.1602 2.1786 -0.9852 3.9394 3.9651 0.4297 0.2859 0.1749 5.3726 1.7224
+#> 243: 93.8884 -6.0719 -0.1606 2.1778 -0.9851 3.9310 3.9741 0.4295 0.2857 0.1750 5.3705 1.7224
+#> 244: 93.8910 -6.0712 -0.1610 2.1771 -0.9850 3.9173 3.9819 0.4294 0.2856 0.1749 5.3700 1.7222
+#> 245: 93.9054 -6.0736 -0.1614 2.1764 -0.9854 3.9106 3.9984 0.4293 0.2856 0.1748 5.3711 1.7217
+#> 246: 93.9209 -6.0753 -0.1617 2.1757 -0.9859 3.9080 4.0071 0.4291 0.2852 0.1746 5.3711 1.7215
+#> 247: 93.9273 -6.0846 -0.1621 2.1752 -0.9861 3.8790 4.0580 0.4286 0.2851 0.1745 5.3755 1.7206
+#> 248: 93.9265 -6.0884 -0.1625 2.1749 -0.9865 3.8613 4.0784 0.4286 0.2848 0.1744 5.3760 1.7198
+#> 249: 93.9286 -6.0926 -0.1627 2.1746 -0.9872 3.8663 4.1008 0.4287 0.2845 0.1745 5.3755 1.7195
+#> 250: 93.9287 -6.0968 -0.1629 2.1744 -0.9878 3.8822 4.1269 0.4289 0.2844 0.1743 5.3755 1.7201
+#> 251: 93.9314 -6.1017 -0.1630 2.1739 -0.9882 3.8878 4.1495 0.4291 0.2843 0.1744 5.3729 1.7200
+#> 252: 93.9351 -6.1036 -0.1632 2.1734 -0.9885 3.8908 4.1545 0.4293 0.2843 0.1746 5.3684 1.7191
+#> 253: 93.9415 -6.1053 -0.1634 2.1729 -0.9889 3.8727 4.1602 0.4294 0.2842 0.1747 5.3650 1.7196
+#> 254: 93.9473 -6.1088 -0.1636 2.1723 -0.9891 3.8657 4.1769 0.4296 0.2843 0.1749 5.3666 1.7190
+#> 255: 93.9505 -6.1087 -0.1639 2.1717 -0.9888 3.8457 4.1720 0.4298 0.2841 0.1749 5.3617 1.7191
+#> 256: 93.9497 -6.1054 -0.1642 2.1715 -0.9885 3.8395 4.1559 0.4299 0.2839 0.1749 5.3598 1.7192
+#> 257: 93.9477 -6.1008 -0.1643 2.1713 -0.9882 3.8383 4.1360 0.4299 0.2836 0.1749 5.3567 1.7196
+#> 258: 93.9402 -6.0998 -0.1645 2.1713 -0.9880 3.8516 4.1288 0.4300 0.2832 0.1749 5.3565 1.7190
+#> 259: 93.9318 -6.0979 -0.1646 2.1711 -0.9879 3.8396 4.1182 0.4301 0.2829 0.1750 5.3583 1.7188
+#> 260: 93.9277 -6.1002 -0.1646 2.1713 -0.9879 3.8173 4.1273 0.4304 0.2826 0.1751 5.3611 1.7186
+#> 261: 93.9251 -6.0973 -0.1646 2.1714 -0.9879 3.8140 4.1105 0.4306 0.2822 0.1750 5.3588 1.7192
+#> 262: 93.9186 -6.1009 -0.1647 2.1715 -0.9880 3.8177 4.1303 0.4308 0.2822 0.1750 5.3604 1.7194
+#> 263: 93.9130 -6.1033 -0.1646 2.1715 -0.9880 3.8029 4.1529 0.4309 0.2822 0.1748 5.3647 1.7188
+#> 264: 93.9040 -6.1077 -0.1645 2.1717 -0.9879 3.7950 4.1820 0.4310 0.2822 0.1747 5.3699 1.7184
+#> 265: 93.9012 -6.1071 -0.1645 2.1714 -0.9879 3.7834 4.1895 0.4310 0.2822 0.1746 5.3755 1.7191
+#> 266: 93.8988 -6.1051 -0.1644 2.1714 -0.9879 3.7788 4.1822 0.4311 0.2822 0.1745 5.3765 1.7203
+#> 267: 93.8964 -6.1059 -0.1643 2.1714 -0.9877 3.7774 4.1896 0.4311 0.2822 0.1744 5.3792 1.7197
+#> 268: 93.8901 -6.1092 -0.1643 2.1715 -0.9876 3.7790 4.2198 0.4310 0.2822 0.1742 5.3811 1.7200
+#> 269: 93.8842 -6.1105 -0.1643 2.1717 -0.9875 3.7620 4.2336 0.4310 0.2823 0.1742 5.3838 1.7193
+#> 270: 93.8760 -6.1125 -0.1643 2.1721 -0.9874 3.7668 4.2483 0.4308 0.2823 0.1741 5.3852 1.7181
+#> 271: 93.8705 -6.1149 -0.1643 2.1722 -0.9873 3.7785 4.2625 0.4306 0.2823 0.1742 5.3853 1.7172
+#> 272: 93.8674 -6.1149 -0.1643 2.1723 -0.9871 3.7829 4.2581 0.4304 0.2823 0.1743 5.3836 1.7162
+#> 273: 93.8644 -6.1159 -0.1642 2.1725 -0.9870 3.7910 4.2631 0.4303 0.2825 0.1743 5.3818 1.7154
+#> 274: 93.8585 -6.1158 -0.1640 2.1728 -0.9869 3.7926 4.2612 0.4302 0.2825 0.1743 5.3816 1.7147
+#> 275: 93.8564 -6.1151 -0.1639 2.1732 -0.9867 3.8053 4.2581 0.4301 0.2826 0.1743 5.3804 1.7143
+#> 276: 93.8564 -6.1132 -0.1638 2.1736 -0.9866 3.7958 4.2486 0.4300 0.2827 0.1745 5.3810 1.7144
+#> 277: 93.8564 -6.1120 -0.1637 2.1741 -0.9867 3.7952 4.2426 0.4298 0.2829 0.1747 5.3808 1.7148
+#> 278: 93.8528 -6.1113 -0.1636 2.1743 -0.9867 3.7922 4.2352 0.4297 0.2832 0.1750 5.3819 1.7144
+#> 279: 93.8503 -6.1124 -0.1636 2.1744 -0.9867 3.7930 4.2390 0.4298 0.2834 0.1753 5.3826 1.7144
+#> 280: 93.8466 -6.1146 -0.1636 2.1743 -0.9867 3.7946 4.2470 0.4299 0.2838 0.1755 5.3832 1.7142
+#> 281: 93.8435 -6.1165 -0.1638 2.1743 -0.9867 3.7994 4.2552 0.4298 0.2840 0.1756 5.3828 1.7140
+#> 282: 93.8421 -6.1162 -0.1639 2.1741 -0.9868 3.7967 4.2496 0.4296 0.2843 0.1758 5.3816 1.7137
+#> 283: 93.8382 -6.1146 -0.1641 2.1740 -0.9866 3.7957 4.2387 0.4294 0.2845 0.1760 5.3796 1.7135
+#> 284: 93.8356 -6.1131 -0.1641 2.1740 -0.9865 3.7904 4.2263 0.4292 0.2848 0.1762 5.3776 1.7127
+#> 285: 93.8349 -6.1113 -0.1642 2.1740 -0.9865 3.7841 4.2129 0.4291 0.2850 0.1765 5.3763 1.7130
+#> 286: 93.8372 -6.1095 -0.1643 2.1741 -0.9864 3.7801 4.2035 0.4289 0.2853 0.1769 5.3779 1.7130
+#> 287: 93.8393 -6.1077 -0.1643 2.1741 -0.9864 3.7804 4.1908 0.4287 0.2857 0.1771 5.3785 1.7132
+#> 288: 93.8395 -6.1071 -0.1644 2.1740 -0.9866 3.7714 4.1834 0.4284 0.2859 0.1772 5.3798 1.7120
+#> 289: 93.8398 -6.1065 -0.1645 2.1738 -0.9865 3.7635 4.1765 0.4282 0.2861 0.1774 5.3821 1.7111
+#> 290: 93.8376 -6.1089 -0.1647 2.1737 -0.9865 3.7495 4.1853 0.4281 0.2863 0.1776 5.3852 1.7106
+#> 291: 93.8341 -6.1091 -0.1647 2.1738 -0.9863 3.7340 4.1854 0.4278 0.2865 0.1776 5.3868 1.7098
+#> 292: 93.8329 -6.1080 -0.1647 2.1741 -0.9863 3.7189 4.1760 0.4275 0.2868 0.1777 5.3885 1.7091
+#> 293: 93.8312 -6.1065 -0.1647 2.1743 -0.9862 3.7091 4.1651 0.4272 0.2871 0.1778 5.3896 1.7086
+#> 294: 93.8310 -6.1042 -0.1647 2.1745 -0.9861 3.6946 4.1521 0.4269 0.2874 0.1780 5.3908 1.7077
+#> 295: 93.8299 -6.1033 -0.1648 2.1747 -0.9861 3.6968 4.1433 0.4265 0.2880 0.1781 5.3904 1.7066
+#> 296: 93.8276 -6.1027 -0.1648 2.1749 -0.9862 3.7072 4.1361 0.4261 0.2885 0.1782 5.3910 1.7056
+#> 297: 93.8212 -6.1015 -0.1647 2.1750 -0.9859 3.7253 4.1278 0.4256 0.2891 0.1783 5.3927 1.7051
+#> 298: 93.8173 -6.0980 -0.1647 2.1751 -0.9858 3.7552 4.1115 0.4251 0.2897 0.1784 5.3932 1.7045
+#> 299: 93.8168 -6.0984 -0.1646 2.1754 -0.9856 3.7687 4.1143 0.4246 0.2902 0.1786 5.3949 1.7037
+#> 300: 93.8154 -6.0967 -0.1646 2.1756 -0.9855 3.7888 4.1072 0.4241 0.2906 0.1788 5.3962 1.7030
+#> 301: 93.8129 -6.0946 -0.1646 2.1757 -0.9852 3.8097 4.1006 0.4236 0.2911 0.1791 5.3971 1.7026
+#> 302: 93.8120 -6.0932 -0.1646 2.1759 -0.9849 3.8403 4.0955 0.4231 0.2917 0.1792 5.3971 1.7021
+#> 303: 93.8115 -6.0942 -0.1646 2.1762 -0.9850 3.8602 4.1004 0.4227 0.2922 0.1795 5.3976 1.7020
+#> 304: 93.8106 -6.0979 -0.1645 2.1765 -0.9850 3.8898 4.1217 0.4222 0.2926 0.1798 5.3975 1.7024
+#> 305: 93.8091 -6.1009 -0.1644 2.1767 -0.9851 3.9165 4.1374 0.4218 0.2931 0.1801 5.3989 1.7024
+#> 306: 93.8090 -6.1043 -0.1644 2.1770 -0.9850 3.9485 4.1617 0.4214 0.2936 0.1803 5.3998 1.7021
+#> 307: 93.8082 -6.1063 -0.1644 2.1772 -0.9850 3.9730 4.1797 0.4210 0.2940 0.1803 5.3998 1.7017
+#> 308: 93.8093 -6.1090 -0.1644 2.1775 -0.9850 3.9874 4.2026 0.4205 0.2945 0.1804 5.3996 1.7006
+#> 309: 93.8092 -6.1122 -0.1643 2.1777 -0.9849 3.9948 4.2297 0.4201 0.2948 0.1804 5.4001 1.6998
+#> 310: 93.8080 -6.1142 -0.1642 2.1780 -0.9850 3.9976 4.2436 0.4197 0.2951 0.1803 5.4016 1.6989
+#> 311: 93.8094 -6.1164 -0.1641 2.1784 -0.9851 4.0015 4.2552 0.4194 0.2952 0.1803 5.4033 1.6978
+#> 312: 93.8107 -6.1184 -0.1640 2.1788 -0.9851 4.0006 4.2628 0.4190 0.2954 0.1802 5.4042 1.6972
+#> 313: 93.8118 -6.1190 -0.1640 2.1789 -0.9851 3.9991 4.2638 0.4186 0.2955 0.1802 5.4053 1.6967
+#> 314: 93.8139 -6.1188 -0.1639 2.1791 -0.9851 4.0019 4.2619 0.4183 0.2956 0.1802 5.4049 1.6966
+#> 315: 93.8152 -6.1173 -0.1639 2.1792 -0.9851 4.0111 4.2553 0.4179 0.2957 0.1802 5.4052 1.6966
+#> 316: 93.8178 -6.1158 -0.1639 2.1792 -0.9851 4.0073 4.2498 0.4175 0.2957 0.1802 5.4050 1.6966
+#> 317: 93.8205 -6.1155 -0.1639 2.1792 -0.9851 3.9999 4.2491 0.4172 0.2957 0.1802 5.4048 1.6963
+#> 318: 93.8216 -6.1145 -0.1639 2.1792 -0.9850 3.9961 4.2438 0.4168 0.2957 0.1802 5.4031 1.6961
+#> 319: 93.8241 -6.1143 -0.1639 2.1792 -0.9849 4.0009 4.2412 0.4164 0.2958 0.1801 5.4004 1.6956
+#> 320: 93.8257 -6.1142 -0.1639 2.1792 -0.9849 4.0018 4.2380 0.4160 0.2958 0.1801 5.3986 1.6952
+#> 321: 93.8280 -6.1134 -0.1639 2.1792 -0.9849 4.0055 4.2339 0.4156 0.2959 0.1802 5.3966 1.6950
+#> 322: 93.8299 -6.1122 -0.1639 2.1793 -0.9848 4.0075 4.2274 0.4152 0.2959 0.1802 5.3969 1.6948
+#> 323: 93.8318 -6.1123 -0.1639 2.1794 -0.9848 4.0087 4.2257 0.4149 0.2960 0.1802 5.3980 1.6941
+#> 324: 93.8352 -6.1098 -0.1639 2.1795 -0.9848 4.0123 4.2136 0.4145 0.2960 0.1802 5.3988 1.6936
+#> 325: 93.8374 -6.1072 -0.1638 2.1796 -0.9848 4.0230 4.2005 0.4142 0.2961 0.1802 5.3991 1.6933
+#> 326: 93.8410 -6.1050 -0.1637 2.1796 -0.9849 4.0327 4.1891 0.4139 0.2963 0.1802 5.4004 1.6927
+#> 327: 93.8457 -6.1023 -0.1637 2.1796 -0.9849 4.0327 4.1767 0.4135 0.2964 0.1802 5.4013 1.6922
+#> 328: 93.8493 -6.1017 -0.1637 2.1797 -0.9850 4.0440 4.1730 0.4131 0.2964 0.1802 5.4019 1.6915
+#> 329: 93.8515 -6.1001 -0.1637 2.1799 -0.9851 4.0556 4.1648 0.4128 0.2963 0.1803 5.4017 1.6912
+#> 330: 93.8541 -6.1001 -0.1636 2.1800 -0.9852 4.0606 4.1631 0.4124 0.2962 0.1804 5.4025 1.6912
+#> 331: 93.8539 -6.0994 -0.1635 2.1801 -0.9854 4.0654 4.1584 0.4120 0.2961 0.1805 5.4025 1.6907
+#> 332: 93.8536 -6.0999 -0.1634 2.1803 -0.9854 4.0696 4.1601 0.4116 0.2960 0.1808 5.4027 1.6904
+#> 333: 93.8531 -6.1002 -0.1633 2.1806 -0.9853 4.0682 4.1646 0.4112 0.2960 0.1810 5.4038 1.6893
+#> 334: 93.8543 -6.1005 -0.1632 2.1809 -0.9852 4.0771 4.1690 0.4108 0.2960 0.1812 5.4040 1.6883
+#> 335: 93.8552 -6.1010 -0.1631 2.1813 -0.9851 4.0888 4.1775 0.4104 0.2960 0.1813 5.4044 1.6878
+#> 336: 93.8555 -6.1016 -0.1630 2.1817 -0.9850 4.0969 4.1858 0.4099 0.2961 0.1814 5.4046 1.6873
+#> 337: 93.8553 -6.1025 -0.1628 2.1820 -0.9849 4.1152 4.1921 0.4094 0.2962 0.1815 5.4070 1.6863
+#> 338: 93.8553 -6.1018 -0.1626 2.1824 -0.9848 4.1314 4.1904 0.4090 0.2963 0.1816 5.4080 1.6852
+#> 339: 93.8567 -6.1004 -0.1625 2.1828 -0.9847 4.1449 4.1855 0.4087 0.2964 0.1817 5.4087 1.6841
+#> 340: 93.8582 -6.0987 -0.1623 2.1832 -0.9846 4.1603 4.1799 0.4083 0.2965 0.1819 5.4086 1.6832
+#> 341: 93.8589 -6.0962 -0.1620 2.1836 -0.9844 4.1692 4.1694 0.4079 0.2965 0.1820 5.4102 1.6828
+#> 342: 93.8583 -6.0932 -0.1618 2.1841 -0.9844 4.1729 4.1563 0.4075 0.2966 0.1821 5.4117 1.6821
+#> 343: 93.8590 -6.0906 -0.1615 2.1845 -0.9844 4.1840 4.1447 0.4071 0.2966 0.1822 5.4125 1.6819
+#> 344: 93.8582 -6.0890 -0.1613 2.1851 -0.9845 4.1860 4.1347 0.4068 0.2968 0.1826 5.4135 1.6814
+#> 345: 93.8576 -6.0876 -0.1610 2.1857 -0.9846 4.1889 4.1252 0.4064 0.2969 0.1829 5.4143 1.6810
+#> 346: 93.8549 -6.0853 -0.1608 2.1862 -0.9845 4.1925 4.1121 0.4061 0.2969 0.1832 5.4157 1.6803
+#> 347: 93.8540 -6.0829 -0.1605 2.1867 -0.9845 4.2031 4.0990 0.4058 0.2970 0.1834 5.4158 1.6803
+#> 348: 93.8516 -6.0814 -0.1602 2.1873 -0.9845 4.2169 4.0885 0.4055 0.2971 0.1836 5.4174 1.6801
+#> 349: 93.8505 -6.0797 -0.1600 2.1879 -0.9845 4.2253 4.0779 0.4052 0.2971 0.1837 5.4190 1.6799
+#> 350: 93.8512 -6.0773 -0.1597 2.1885 -0.9845 4.2268 4.0657 0.4049 0.2972 0.1839 5.4209 1.6797
+#> 351: 93.8507 -6.0754 -0.1595 2.1890 -0.9845 4.2245 4.0559 0.4046 0.2972 0.1840 5.4230 1.6794
+#> 352: 93.8490 -6.0736 -0.1592 2.1896 -0.9845 4.2296 4.0474 0.4044 0.2973 0.1841 5.4252 1.6790
+#> 353: 93.8460 -6.0718 -0.1589 2.1901 -0.9845 4.2356 4.0374 0.4042 0.2973 0.1843 5.4272 1.6790
+#> 354: 93.8437 -6.0695 -0.1586 2.1906 -0.9845 4.2408 4.0255 0.4041 0.2973 0.1844 5.4303 1.6787
+#> 355: 93.8420 -6.0679 -0.1584 2.1912 -0.9844 4.2428 4.0166 0.4040 0.2973 0.1845 5.4342 1.6785
+#> 356: 93.8413 -6.0666 -0.1581 2.1916 -0.9843 4.2418 4.0072 0.4040 0.2973 0.1845 5.4348 1.6792
+#> 357: 93.8406 -6.0650 -0.1578 2.1921 -0.9844 4.2531 3.9973 0.4040 0.2973 0.1846 5.4350 1.6798
+#> 358: 93.8404 -6.0639 -0.1575 2.1926 -0.9844 4.2596 3.9901 0.4040 0.2973 0.1846 5.4357 1.6805
+#> 359: 93.8373 -6.0630 -0.1572 2.1931 -0.9845 4.2724 3.9820 0.4039 0.2973 0.1848 5.4368 1.6816
+#> 360: 93.8347 -6.0622 -0.1569 2.1936 -0.9845 4.2788 3.9747 0.4039 0.2973 0.1849 5.4377 1.6824
+#> 361: 93.8327 -6.0626 -0.1566 2.1942 -0.9846 4.2919 3.9749 0.4038 0.2973 0.1850 5.4382 1.6831
+#> 362: 93.8326 -6.0629 -0.1562 2.1947 -0.9846 4.2989 3.9737 0.4038 0.2973 0.1850 5.4408 1.6838
+#> 363: 93.8316 -6.0629 -0.1559 2.1953 -0.9846 4.3007 3.9725 0.4037 0.2972 0.1850 5.4420 1.6842
+#> 364: 93.8317 -6.0629 -0.1556 2.1957 -0.9846 4.2910 3.9739 0.4038 0.2971 0.1850 5.4430 1.6840
+#> 365: 93.8317 -6.0629 -0.1553 2.1962 -0.9846 4.2878 3.9759 0.4040 0.2967 0.1849 5.4441 1.6839
+#> 366: 93.8319 -6.0633 -0.1549 2.1966 -0.9845 4.2870 3.9823 0.4042 0.2963 0.1849 5.4461 1.6839
+#> 367: 93.8320 -6.0636 -0.1546 2.1971 -0.9845 4.2828 3.9850 0.4042 0.2959 0.1849 5.4479 1.6843
+#> 368: 93.8312 -6.0635 -0.1544 2.1975 -0.9844 4.2781 3.9859 0.4043 0.2955 0.1849 5.4475 1.6841
+#> 369: 93.8301 -6.0640 -0.1541 2.1979 -0.9844 4.2760 3.9891 0.4043 0.2953 0.1850 5.4472 1.6835
+#> 370: 93.8306 -6.0651 -0.1539 2.1983 -0.9844 4.2690 3.9967 0.4042 0.2950 0.1850 5.4484 1.6829
+#> 371: 93.8312 -6.0669 -0.1536 2.1988 -0.9845 4.2613 4.0111 0.4042 0.2947 0.1851 5.4494 1.6822
+#> 372: 93.8312 -6.0681 -0.1533 2.1992 -0.9845 4.2585 4.0252 0.4042 0.2945 0.1852 5.4513 1.6817
+#> 373: 93.8307 -6.0681 -0.1531 2.1996 -0.9846 4.2605 4.0284 0.4042 0.2943 0.1853 5.4523 1.6815
+#> 374: 93.8305 -6.0678 -0.1529 2.1999 -0.9846 4.2676 4.0279 0.4040 0.2942 0.1853 5.4533 1.6816
+#> 375: 93.8313 -6.0673 -0.1528 2.2002 -0.9846 4.2708 4.0232 0.4038 0.2940 0.1854 5.4543 1.6813
+#> 376: 93.8310 -6.0672 -0.1527 2.2004 -0.9846 4.2775 4.0214 0.4037 0.2938 0.1855 5.4538 1.6809
+#> 377: 93.8298 -6.0666 -0.1526 2.2007 -0.9846 4.2787 4.0166 0.4035 0.2937 0.1856 5.4532 1.6806
+#> 378: 93.8276 -6.0664 -0.1525 2.2009 -0.9846 4.2781 4.0135 0.4033 0.2935 0.1857 5.4538 1.6801
+#> 379: 93.8262 -6.0671 -0.1524 2.2012 -0.9846 4.2800 4.0157 0.4031 0.2932 0.1857 5.4530 1.6803
+#> 380: 93.8243 -6.0675 -0.1523 2.2015 -0.9846 4.2735 4.0168 0.4029 0.2929 0.1857 5.4523 1.6803
+#> 381: 93.8233 -6.0677 -0.1522 2.2017 -0.9845 4.2670 4.0189 0.4027 0.2926 0.1858 5.4517 1.6798
+#> 382: 93.8229 -6.0674 -0.1521 2.2019 -0.9845 4.2655 4.0211 0.4025 0.2924 0.1858 5.4510 1.6794
+#> 383: 93.8196 -6.0681 -0.1521 2.2021 -0.9843 4.2696 4.0291 0.4023 0.2922 0.1859 5.4504 1.6788
+#> 384: 93.8174 -6.0688 -0.1520 2.2023 -0.9842 4.2851 4.0333 0.4021 0.2919 0.1860 5.4500 1.6783
+#> 385: 93.8156 -6.0682 -0.1518 2.2028 -0.9840 4.3056 4.0305 0.4019 0.2920 0.1862 5.4503 1.6774
+#> 386: 93.8145 -6.0684 -0.1516 2.2032 -0.9838 4.3195 4.0302 0.4016 0.2920 0.1863 5.4499 1.6765
+#> 387: 93.8121 -6.0679 -0.1514 2.2036 -0.9837 4.3290 4.0272 0.4014 0.2920 0.1864 5.4501 1.6756
+#> 388: 93.8105 -6.0676 -0.1513 2.2040 -0.9835 4.3393 4.0267 0.4011 0.2920 0.1865 5.4509 1.6751
+#> 389: 93.8089 -6.0664 -0.1510 2.2045 -0.9833 4.3458 4.0224 0.4009 0.2920 0.1865 5.4512 1.6746
+#> 390: 93.8080 -6.0658 -0.1508 2.2049 -0.9832 4.3422 4.0199 0.4007 0.2920 0.1866 5.4514 1.6744
+#> 391: 93.8077 -6.0669 -0.1507 2.2053 -0.9831 4.3500 4.0277 0.4007 0.2920 0.1867 5.4511 1.6740
+#> 392: 93.8069 -6.0676 -0.1505 2.2056 -0.9831 4.3525 4.0326 0.4006 0.2920 0.1868 5.4500 1.6733
+#> 393: 93.8072 -6.0678 -0.1504 2.2059 -0.9830 4.3562 4.0344 0.4005 0.2920 0.1868 5.4491 1.6725
+#> 394: 93.8083 -6.0684 -0.1503 2.2061 -0.9829 4.3577 4.0386 0.4004 0.2920 0.1869 5.4493 1.6716
+#> 395: 93.8086 -6.0685 -0.1501 2.2064 -0.9828 4.3574 4.0394 0.4003 0.2920 0.1869 5.4493 1.6709
+#> 396: 93.8078 -6.0677 -0.1500 2.2067 -0.9827 4.3591 4.0355 0.4002 0.2921 0.1870 5.4493 1.6707
+#> 397: 93.8064 -6.0668 -0.1499 2.2071 -0.9825 4.3621 4.0317 0.4000 0.2922 0.1871 5.4495 1.6704
+#> 398: 93.8058 -6.0661 -0.1499 2.2073 -0.9823 4.3701 4.0285 0.3999 0.2923 0.1872 5.4491 1.6699
+#> 399: 93.8057 -6.0651 -0.1498 2.2075 -0.9822 4.3803 4.0243 0.3997 0.2924 0.1872 5.4485 1.6699
+#> 400: 93.8057 -6.0647 -0.1498 2.2076 -0.9820 4.3854 4.0225 0.3996 0.2924 0.1872 5.4488 1.6699
+#> 401: 93.8059 -6.0635 -0.1498 2.2078 -0.9819 4.3939 4.0178 0.3995 0.2925 0.1873 5.4491 1.6702
+#> 402: 93.8063 -6.0621 -0.1498 2.2079 -0.9818 4.4033 4.0120 0.3993 0.2926 0.1875 5.4492 1.6704
+#> 403: 93.8055 -6.0609 -0.1498 2.2080 -0.9816 4.4098 4.0069 0.3992 0.2926 0.1876 5.4494 1.6703
+#> 404: 93.8040 -6.0608 -0.1499 2.2081 -0.9815 4.4153 4.0050 0.3991 0.2927 0.1877 5.4494 1.6701
+#> 405: 93.8030 -6.0604 -0.1499 2.2082 -0.9814 4.4181 4.0047 0.3990 0.2928 0.1879 5.4491 1.6700
+#> 406: 93.8002 -6.0597 -0.1499 2.2083 -0.9812 4.4257 4.0025 0.3989 0.2928 0.1880 5.4498 1.6702
+#> 407: 93.7969 -6.0593 -0.1500 2.2085 -0.9810 4.4343 3.9994 0.3988 0.2928 0.1881 5.4514 1.6703
+#> 408: 93.7947 -6.0582 -0.1499 2.2087 -0.9809 4.4509 3.9936 0.3987 0.2927 0.1882 5.4526 1.6704
+#> 409: 93.7929 -6.0579 -0.1499 2.2088 -0.9807 4.4584 3.9918 0.3987 0.2926 0.1882 5.4537 1.6707
+#> 410: 93.7896 -6.0593 -0.1499 2.2089 -0.9807 4.4664 4.0002 0.3987 0.2925 0.1883 5.4560 1.6705
+#> 411: 93.7875 -6.0601 -0.1499 2.2090 -0.9807 4.4626 4.0057 0.3987 0.2924 0.1883 5.4567 1.6705
+#> 412: 93.7862 -6.0602 -0.1499 2.2091 -0.9808 4.4574 4.0095 0.3986 0.2923 0.1884 5.4565 1.6706
+#> 413: 93.7858 -6.0606 -0.1498 2.2092 -0.9808 4.4527 4.0146 0.3986 0.2922 0.1885 5.4561 1.6708
+#> 414: 93.7859 -6.0615 -0.1498 2.2093 -0.9808 4.4451 4.0211 0.3987 0.2921 0.1885 5.4574 1.6708
+#> 415: 93.7864 -6.0629 -0.1498 2.2092 -0.9808 4.4443 4.0298 0.3986 0.2921 0.1885 5.4576 1.6707
+#> 416: 93.7851 -6.0639 -0.1498 2.2092 -0.9808 4.4462 4.0362 0.3985 0.2920 0.1884 5.4575 1.6706
+#> 417: 93.7820 -6.0644 -0.1499 2.2092 -0.9808 4.4425 4.0387 0.3985 0.2920 0.1884 5.4577 1.6703
+#> 418: 93.7801 -6.0652 -0.1499 2.2093 -0.9808 4.4365 4.0420 0.3985 0.2920 0.1883 5.4589 1.6702
+#> 419: 93.7799 -6.0648 -0.1499 2.2094 -0.9807 4.4303 4.0418 0.3984 0.2921 0.1883 5.4596 1.6703
+#> 420: 93.7797 -6.0641 -0.1498 2.2095 -0.9807 4.4216 4.0383 0.3983 0.2921 0.1884 5.4607 1.6702
+#> 421: 93.7803 -6.0641 -0.1498 2.2096 -0.9808 4.4120 4.0396 0.3983 0.2922 0.1885 5.4621 1.6702
+#> 422: 93.7806 -6.0638 -0.1498 2.2097 -0.9809 4.4017 4.0373 0.3981 0.2923 0.1885 5.4635 1.6702
+#> 423: 93.7800 -6.0636 -0.1498 2.2098 -0.9810 4.3948 4.0339 0.3981 0.2923 0.1885 5.4640 1.6701
+#> 424: 93.7789 -6.0638 -0.1498 2.2099 -0.9810 4.3884 4.0336 0.3980 0.2924 0.1885 5.4651 1.6700
+#> 425: 93.7774 -6.0628 -0.1498 2.2101 -0.9810 4.3814 4.0271 0.3978 0.2925 0.1884 5.4666 1.6699
+#> 426: 93.7755 -6.0619 -0.1498 2.2102 -0.9811 4.3841 4.0221 0.3977 0.2925 0.1884 5.4693 1.6697
+#> 427: 93.7753 -6.0612 -0.1498 2.2103 -0.9810 4.3785 4.0167 0.3975 0.2926 0.1883 5.4712 1.6696
+#> 428: 93.7741 -6.0613 -0.1498 2.2104 -0.9810 4.3767 4.0161 0.3973 0.2926 0.1882 5.4729 1.6696
+#> 429: 93.7717 -6.0613 -0.1498 2.2105 -0.9810 4.3744 4.0158 0.3971 0.2926 0.1880 5.4743 1.6694
+#> 430: 93.7690 -6.0619 -0.1498 2.2106 -0.9809 4.3744 4.0189 0.3969 0.2926 0.1879 5.4753 1.6692
+#> 431: 93.7668 -6.0615 -0.1498 2.2107 -0.9809 4.3709 4.0174 0.3967 0.2925 0.1878 5.4762 1.6691
+#> 432: 93.7656 -6.0619 -0.1498 2.2108 -0.9809 4.3710 4.0173 0.3966 0.2926 0.1878 5.4770 1.6688
+#> 433: 93.7632 -6.0625 -0.1498 2.2108 -0.9809 4.3689 4.0204 0.3964 0.2926 0.1877 5.4774 1.6687
+#> 434: 93.7624 -6.0621 -0.1498 2.2109 -0.9808 4.3687 4.0178 0.3962 0.2926 0.1876 5.4774 1.6683
+#> 435: 93.7608 -6.0622 -0.1497 2.2111 -0.9808 4.3714 4.0182 0.3961 0.2927 0.1875 5.4777 1.6679
+#> 436: 93.7586 -6.0622 -0.1498 2.2112 -0.9808 4.3695 4.0178 0.3959 0.2928 0.1874 5.4784 1.6679
+#> 437: 93.7558 -6.0622 -0.1498 2.2114 -0.9809 4.3658 4.0167 0.3957 0.2928 0.1873 5.4795 1.6678
+#> 438: 93.7519 -6.0627 -0.1499 2.2115 -0.9808 4.3601 4.0183 0.3955 0.2928 0.1872 5.4807 1.6674
+#> 439: 93.7478 -6.0618 -0.1499 2.2115 -0.9807 4.3538 4.0133 0.3952 0.2928 0.1871 5.4814 1.6672
+#> 440: 93.7449 -6.0612 -0.1499 2.2117 -0.9805 4.3504 4.0103 0.3951 0.2928 0.1870 5.4820 1.6669
+#> 441: 93.7433 -6.0608 -0.1499 2.2117 -0.9805 4.3438 4.0077 0.3949 0.2928 0.1869 5.4818 1.6666
+#> 442: 93.7417 -6.0604 -0.1500 2.2118 -0.9805 4.3354 4.0058 0.3947 0.2927 0.1868 5.4824 1.6666
+#> 443: 93.7407 -6.0604 -0.1500 2.2119 -0.9805 4.3281 4.0046 0.3946 0.2927 0.1867 5.4832 1.6667
+#> 444: 93.7397 -6.0608 -0.1500 2.2118 -0.9805 4.3180 4.0069 0.3944 0.2928 0.1866 5.4857 1.6664
+#> 445: 93.7387 -6.0613 -0.1501 2.2118 -0.9805 4.3092 4.0085 0.3942 0.2929 0.1866 5.4866 1.6663
+#> 446: 93.7376 -6.0612 -0.1502 2.2117 -0.9805 4.3022 4.0075 0.3939 0.2930 0.1865 5.4866 1.6660
+#> 447: 93.7375 -6.0613 -0.1503 2.2116 -0.9806 4.2981 4.0076 0.3937 0.2931 0.1865 5.4863 1.6658
+#> 448: 93.7388 -6.0617 -0.1504 2.2115 -0.9806 4.2970 4.0087 0.3935 0.2932 0.1864 5.4870 1.6658
+#> 449: 93.7400 -6.0617 -0.1504 2.2115 -0.9807 4.2904 4.0069 0.3933 0.2933 0.1864 5.4880 1.6655
+#> 450: 93.7414 -6.0623 -0.1505 2.2113 -0.9808 4.2829 4.0095 0.3930 0.2935 0.1863 5.4880 1.6653
+#> 451: 93.7426 -6.0634 -0.1506 2.2112 -0.9808 4.2797 4.0146 0.3928 0.2936 0.1863 5.4877 1.6655
+#> 452: 93.7447 -6.0642 -0.1507 2.2110 -0.9809 4.2770 4.0171 0.3926 0.2938 0.1862 5.4876 1.6657
+#> 453: 93.7465 -6.0644 -0.1508 2.2108 -0.9810 4.2698 4.0184 0.3924 0.2940 0.1862 5.4877 1.6652
+#> 454: 93.7478 -6.0645 -0.1509 2.2106 -0.9810 4.2657 4.0182 0.3922 0.2941 0.1861 5.4874 1.6648
+#> 455: 93.7486 -6.0650 -0.1511 2.2104 -0.9811 4.2656 4.0203 0.3921 0.2943 0.1861 5.4871 1.6644
+#> 456: 93.7485 -6.0659 -0.1512 2.2102 -0.9812 4.2646 4.0240 0.3920 0.2945 0.1860 5.4869 1.6641
+#> 457: 93.7487 -6.0668 -0.1514 2.2099 -0.9813 4.2613 4.0277 0.3919 0.2946 0.1860 5.4866 1.6640
+#> 458: 93.7484 -6.0667 -0.1515 2.2097 -0.9812 4.2586 4.0263 0.3918 0.2947 0.1859 5.4854 1.6639
+#> 459: 93.7468 -6.0661 -0.1517 2.2095 -0.9812 4.2565 4.0225 0.3917 0.2948 0.1858 5.4853 1.6639
+#> 460: 93.7458 -6.0652 -0.1518 2.2093 -0.9812 4.2548 4.0171 0.3916 0.2950 0.1858 5.4843 1.6638
+#> 461: 93.7435 -6.0645 -0.1519 2.2091 -0.9811 4.2554 4.0121 0.3914 0.2951 0.1858 5.4843 1.6637
+#> 462: 93.7421 -6.0637 -0.1521 2.2089 -0.9811 4.2509 4.0079 0.3913 0.2953 0.1857 5.4840 1.6638
+#> 463: 93.7406 -6.0630 -0.1522 2.2088 -0.9810 4.2534 4.0036 0.3912 0.2955 0.1857 5.4834 1.6640
+#> 464: 93.7406 -6.0622 -0.1524 2.2086 -0.9810 4.2548 3.9986 0.3911 0.2956 0.1857 5.4828 1.6639
+#> 465: 93.7404 -6.0617 -0.1525 2.2084 -0.9810 4.2511 3.9955 0.3910 0.2958 0.1857 5.4828 1.6638
+#> 466: 93.7414 -6.0610 -0.1527 2.2080 -0.9809 4.2468 3.9918 0.3910 0.2959 0.1857 5.4812 1.6640
+#> 467: 93.7419 -6.0606 -0.1529 2.2077 -0.9810 4.2446 3.9885 0.3909 0.2960 0.1858 5.4799 1.6642
+#> 468: 93.7427 -6.0604 -0.1531 2.2074 -0.9809 4.2473 3.9872 0.3909 0.2961 0.1858 5.4790 1.6643
+#> 469: 93.7435 -6.0608 -0.1532 2.2073 -0.9810 4.2457 3.9891 0.3907 0.2963 0.1858 5.4789 1.6641
+#> 470: 93.7442 -6.0611 -0.1533 2.2071 -0.9811 4.2443 3.9895 0.3905 0.2965 0.1858 5.4785 1.6640
+#> 471: 93.7443 -6.0618 -0.1534 2.2070 -0.9812 4.2415 3.9932 0.3903 0.2967 0.1858 5.4773 1.6639
+#> 472: 93.7433 -6.0624 -0.1535 2.2069 -0.9812 4.2414 3.9958 0.3901 0.2969 0.1858 5.4765 1.6637
+#> 473: 93.7421 -6.0621 -0.1536 2.2067 -0.9811 4.2330 3.9962 0.3899 0.2970 0.1858 5.4762 1.6637
+#> 474: 93.7415 -6.0621 -0.1537 2.2066 -0.9812 4.2263 3.9968 0.3897 0.2972 0.1858 5.4755 1.6638
+#> 475: 93.7396 -6.0621 -0.1538 2.2066 -0.9812 4.2261 3.9956 0.3895 0.2973 0.1859 5.4751 1.6637
+#> 476: 93.7373 -6.0626 -0.1539 2.2065 -0.9811 4.2265 3.9976 0.3893 0.2975 0.1859 5.4743 1.6634
+#> 477: 93.7357 -6.0623 -0.1540 2.2063 -0.9811 4.2222 3.9953 0.3891 0.2976 0.1859 5.4741 1.6635
+#> 478: 93.7345 -6.0620 -0.1541 2.2062 -0.9811 4.2165 3.9939 0.3889 0.2978 0.1860 5.4745 1.6638
+#> 479: 93.7341 -6.0615 -0.1542 2.2062 -0.9812 4.2122 3.9916 0.3887 0.2979 0.1860 5.4751 1.6637
+#> 480: 93.7338 -6.0619 -0.1543 2.2061 -0.9812 4.2084 3.9932 0.3885 0.2980 0.1860 5.4753 1.6635
+#> 481: 93.7336 -6.0618 -0.1544 2.2060 -0.9812 4.2066 3.9945 0.3883 0.2981 0.1860 5.4748 1.6637
+#> 482: 93.7340 -6.0622 -0.1545 2.2058 -0.9812 4.2069 3.9969 0.3882 0.2983 0.1860 5.4741 1.6636
+#> 483: 93.7328 -6.0627 -0.1547 2.2057 -0.9813 4.2062 3.9992 0.3879 0.2985 0.1861 5.4739 1.6636
+#> 484: 93.7323 -6.0629 -0.1547 2.2056 -0.9813 4.2075 3.9995 0.3877 0.2987 0.1861 5.4730 1.6638
+#> 485: 93.7326 -6.0634 -0.1548 2.2055 -0.9814 4.2045 4.0013 0.3875 0.2989 0.1862 5.4727 1.6637
+#> 486: 93.7320 -6.0632 -0.1549 2.2055 -0.9814 4.2084 3.9989 0.3872 0.2991 0.1863 5.4718 1.6635
+#> 487: 93.7321 -6.0625 -0.1549 2.2054 -0.9814 4.2105 3.9949 0.3870 0.2993 0.1864 5.4712 1.6634
+#> 488: 93.7326 -6.0623 -0.1550 2.2054 -0.9814 4.2104 3.9935 0.3868 0.2996 0.1865 5.4721 1.6635
+#> 489: 93.7342 -6.0615 -0.1551 2.2054 -0.9815 4.2103 3.9893 0.3866 0.2998 0.1866 5.4725 1.6635
+#> 490: 93.7360 -6.0610 -0.1551 2.2053 -0.9815 4.2116 3.9857 0.3864 0.3001 0.1867 5.4730 1.6636
+#> 491: 93.7374 -6.0601 -0.1551 2.2052 -0.9815 4.2128 3.9804 0.3862 0.3003 0.1868 5.4722 1.6638
+#> 492: 93.7386 -6.0597 -0.1552 2.2050 -0.9816 4.2171 3.9774 0.3861 0.3006 0.1869 5.4714 1.6642
+#> 493: 93.7399 -6.0597 -0.1553 2.2049 -0.9816 4.2262 3.9766 0.3859 0.3008 0.1869 5.4712 1.6643
+#> 494: 93.7404 -6.0596 -0.1553 2.2047 -0.9816 4.2347 3.9746 0.3857 0.3011 0.1870 5.4711 1.6646
+#> 495: 93.7406 -6.0590 -0.1554 2.2046 -0.9817 4.2395 3.9711 0.3855 0.3014 0.1871 5.4705 1.6650
+#> 496: 93.7416 -6.0582 -0.1554 2.2045 -0.9817 4.2456 3.9660 0.3853 0.3017 0.1871 5.4707 1.6656
+#> 497: 93.7433 -6.0575 -0.1555 2.2044 -0.9818 4.2511 3.9631 0.3851 0.3020 0.1871 5.4714 1.6658
+#> 498: 93.7444 -6.0574 -0.1556 2.2042 -0.9817 4.2516 3.9632 0.3848 0.3023 0.1871 5.4721 1.6660
+#> 499: 93.7457 -6.0576 -0.1557 2.2041 -0.9817 4.2518 3.9660 0.3846 0.3025 0.1871 5.4728 1.6660
+#> 500: 93.7469 -6.0586 -0.1557 2.2040 -0.9817 4.2481 3.9757 0.3844 0.3028 0.1871 5.4738 1.6661
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.5791 -5.6199 -2.0817 -3.9984 -1.2037 0.1481 4.5359 1.6042 1.1515 2.4545 0.4989 0.5230 19.1822 10.0277
-#> 2: 93.5157 -5.6781 -1.9742 -4.0546 -1.1333 0.1109 4.4678 1.5240 1.0939 2.3318 0.4740 0.6338 12.8885 7.4711
-#> 3: 93.2898 -5.7047 -1.8559 -4.1328 -1.0939 0.0438 5.0096 1.4478 1.1939 2.2152 0.4503 0.6021 11.0381 5.1444
-#> 4: 93.0426 -5.7814 -1.8501 -4.1839 -1.0410 0.0594 6.3802 1.4778 1.2229 2.1556 0.4278 0.5972 10.2381 4.4049
-#> 5: 92.9134 -5.8482 -1.8162 -4.2071 -1.0582 0.0732 6.9858 1.8242 1.1718 2.3151 0.4064 0.5822 9.8642 4.4088
-#> 6: 92.7655 -5.8047 -1.8535 -4.2041 -0.9870 0.0611 6.6365 1.7739 1.1619 2.2910 0.3861 0.5531 8.6374 4.0594
-#> 7: 93.0259 -5.8252 -1.9173 -4.2093 -0.9549 0.0995 6.3047 2.2731 1.1038 2.1765 0.3668 0.5255 9.0819 3.0678
-#> 8: 93.1406 -5.7510 -1.9019 -4.2213 -0.9559 0.1508 5.9894 2.5908 1.0919 2.0948 0.3484 0.4992 8.3332 2.3703
-#> 9: 93.3980 -5.5162 -1.9512 -4.2707 -0.9026 0.1570 5.6900 2.4612 1.0373 2.3579 0.3310 0.4742 7.7762 2.1692
-#> 10: 93.5148 -5.4966 -1.9184 -4.2482 -0.9045 0.1396 5.4055 2.3382 0.9855 2.2400 0.3145 0.4652 7.5796 1.9233
-#> 11: 93.1833 -5.5679 -1.9315 -4.2869 -0.9148 0.1713 5.1352 2.2213 0.9362 2.1465 0.2987 0.4622 7.5181 1.8003
-#> 12: 92.9902 -5.7249 -1.9741 -4.3054 -0.9148 0.1927 4.8784 2.9298 0.8975 2.3858 0.2838 0.5005 7.3638 1.7074
-#> 13: 92.5821 -5.7143 -1.9662 -4.3403 -0.8940 0.1595 4.6345 2.8035 0.9305 2.5370 0.2696 0.4755 7.1732 1.6333
-#> 14: 92.1385 -5.5571 -1.9874 -4.2935 -0.8815 0.1762 5.5000 2.6634 0.9011 2.4102 0.2561 0.5012 7.1920 1.7020
-#> 15: 92.1244 -5.5198 -1.9701 -4.3134 -0.8984 0.1704 5.2250 2.5302 0.9705 2.4401 0.2433 0.4839 7.4072 1.6160
-#> 16: 92.6306 -5.4666 -1.9776 -4.3023 -0.8906 0.1737 4.9638 2.4037 1.0278 2.3181 0.2312 0.5183 7.5105 1.6033
-#> 17: 92.5769 -5.4886 -2.0034 -4.3892 -0.8863 0.1967 5.6659 2.2835 1.0796 2.7700 0.2196 0.5138 7.6495 1.4656
-#> 18: 92.0321 -5.5257 -2.0086 -4.3651 -0.8914 0.1869 6.5345 2.1693 1.0771 2.6315 0.2086 0.4906 7.8248 1.4297
-#> 19: 92.5497 -5.5509 -1.9892 -4.3590 -0.8947 0.2148 6.2078 2.0936 1.0629 2.4999 0.1992 0.4847 7.8809 1.4881
-#> 20: 92.3638 -5.5322 -1.9943 -4.3507 -0.9153 0.1787 6.2176 2.1784 1.0242 2.5190 0.1923 0.4604 7.7900 1.5147
-#> 21: 92.3946 -5.5963 -1.9984 -4.3234 -0.9031 0.1961 5.9067 2.4305 0.9962 2.3930 0.1827 0.4374 7.6671 1.5182
-#> 22: 92.3389 -5.7757 -1.9686 -4.3485 -0.9054 0.1677 5.6113 3.2010 0.9650 2.4493 0.1907 0.4220 7.1305 1.5425
-#> 23: 92.5054 -5.7766 -1.9947 -4.3613 -0.9069 0.1781 5.3308 3.2506 0.9932 2.5478 0.1868 0.4217 7.6690 1.4526
-#> 24: 92.5865 -5.8597 -1.9691 -4.4676 -0.8950 0.1755 5.0642 4.0954 0.9471 3.5482 0.1891 0.4438 7.2397 1.6349
-#> 25: 92.3775 -5.8727 -1.9577 -4.4964 -0.8955 0.1477 4.8354 3.8906 0.9557 3.5054 0.2003 0.4216 6.7966 1.5576
-#> 26: 92.2427 -5.9696 -1.9672 -4.4384 -0.9063 0.1733 4.5937 4.0917 0.9924 3.3326 0.1918 0.4341 6.9377 1.5723
-#> 27: 92.7312 -5.8434 -1.9590 -4.3655 -0.9095 0.1669 4.4448 3.8871 1.0032 3.1660 0.2006 0.4320 7.1970 1.5118
-#> 28: 92.7033 -5.8759 -1.9827 -4.3776 -0.9145 0.1844 4.5885 3.6928 0.9750 3.0077 0.2093 0.4104 6.8745 1.4865
-#> 29: 92.5242 -5.8627 -1.9806 -4.4623 -0.9142 0.2069 5.2823 3.5081 0.9748 3.5849 0.2098 0.4120 6.9735 1.5115
-#> 30: 92.2312 -5.8332 -1.9739 -4.3699 -0.9100 0.1624 5.0182 3.5473 0.9553 3.4056 0.2102 0.3914 6.8547 1.5172
-#> 31: 92.1659 -5.7898 -1.9642 -4.3956 -0.9105 0.1625 4.7672 3.3700 0.9442 3.2571 0.2071 0.3795 6.5191 1.5452
-#> 32: 92.5436 -5.7968 -1.9642 -4.3987 -0.9179 0.1110 4.5289 3.2015 0.9382 3.0943 0.2024 0.3605 6.5921 1.5105
-#> 33: 92.7837 -5.8155 -1.9539 -4.3145 -0.9157 0.1398 4.3024 3.3616 0.9119 2.9395 0.1981 0.3494 6.2870 1.6036
-#> 34: 93.0500 -5.8853 -1.9587 -4.2507 -0.9146 0.1455 4.0873 4.3592 0.9129 2.7926 0.1961 0.3319 6.3493 1.6059
-#> 35: 93.1208 -5.8581 -1.9614 -4.2722 -0.9127 0.1255 4.0645 4.1413 0.9262 2.6529 0.1964 0.3157 6.1337 1.6010
-#> 36: 93.1002 -5.8598 -1.9886 -4.2092 -0.9076 0.1192 4.2392 3.9342 0.9566 2.5203 0.2015 0.3222 6.5326 1.4847
-#> 37: 92.8242 -5.6228 -1.9655 -4.2054 -0.9099 0.1010 6.8190 3.7375 0.9087 2.3943 0.1942 0.3141 6.2613 1.6015
-#> 38: 93.1512 -5.5747 -1.9736 -4.2054 -0.9115 0.0887 6.4781 3.5506 0.8904 2.2746 0.1930 0.3298 6.4960 1.5750
-#> 39: 92.9998 -5.5416 -1.9750 -4.2124 -0.9101 0.0953 6.1542 3.3731 0.9013 2.1608 0.1858 0.3204 6.6470 1.5705
-#> 40: 93.2158 -5.7057 -1.9587 -4.2101 -0.9122 0.0630 5.8464 3.2044 0.9350 2.1357 0.1851 0.3044 6.6842 1.5069
-#> 41: 93.0585 -5.5453 -1.9306 -4.2101 -0.9021 0.0531 5.5541 3.0442 0.9458 2.1673 0.1851 0.2892 6.3923 1.5949
-#> 42: 93.0958 -5.4512 -1.9484 -4.2227 -0.8959 0.0649 5.2764 2.8920 0.9571 2.1930 0.1829 0.2747 6.3082 1.5985
-#> 43: 93.2333 -5.5398 -1.9391 -4.2400 -0.8972 0.0870 5.0126 2.7474 0.9913 2.2830 0.1984 0.2720 6.0810 1.6131
-#> 44: 92.9479 -5.5648 -1.9227 -4.2468 -0.9104 0.0963 4.7620 2.6100 0.9682 2.2976 0.2038 0.2648 5.8461 1.6955
-#> 45: 93.0244 -5.6247 -1.9379 -4.2588 -0.9093 0.0865 5.2997 2.4894 0.9837 2.3100 0.2039 0.2844 5.9439 1.6121
-#> 46: 92.5959 -5.6240 -1.9513 -4.2588 -0.9172 0.0923 5.3111 2.5081 1.0158 2.3100 0.2050 0.2702 6.0141 1.6189
-#> 47: 92.8483 -5.5823 -1.9529 -4.2684 -0.9194 0.0770 6.2469 2.3827 1.0328 2.3567 0.2104 0.2567 6.0472 1.5858
-#> 48: 92.6210 -5.6336 -1.9379 -4.3049 -0.9054 0.0747 7.5721 2.3177 1.0379 2.5427 0.2103 0.2439 6.0431 1.5860
-#> 49: 92.6337 -5.6723 -1.9486 -4.2879 -0.8985 0.0773 7.1935 2.6572 1.0181 2.4515 0.2056 0.2559 6.0895 1.5217
-#> 50: 92.2413 -5.7138 -1.9587 -4.2804 -0.8926 0.0774 8.1551 2.9779 1.0282 2.4807 0.2090 0.2510 6.2355 1.5223
-#> 51: 92.2223 -5.6765 -1.9496 -4.2971 -0.8840 0.1034 7.7638 3.0625 1.0017 2.6024 0.2075 0.2384 6.3495 1.6621
-#> 52: 92.4242 -5.6573 -1.9408 -4.2943 -0.8993 0.1136 8.3190 2.9093 1.0044 2.4822 0.2163 0.2411 6.0611 1.5241
-#> 53: 92.6070 -5.5921 -1.9397 -4.2873 -0.9046 0.0904 10.3681 2.7639 1.0098 2.4895 0.2194 0.2393 6.1728 1.5264
-#> 54: 92.9339 -5.6194 -1.9292 -4.2950 -0.9006 0.1010 9.9150 2.6257 1.0088 2.4268 0.2346 0.2492 5.9203 1.5693
-#> 55: 93.4640 -5.5851 -1.8969 -4.2614 -0.9065 0.1058 10.3986 2.4944 1.0204 2.3055 0.2257 0.2403 5.7030 1.5717
-#> 56: 93.3646 -5.5851 -1.9127 -4.3130 -0.9196 0.1077 9.8787 2.3697 1.0067 2.6259 0.2261 0.2370 5.7389 1.5053
-#> 57: 93.5408 -5.4962 -1.9150 -4.3285 -0.9148 0.0880 9.3848 2.2512 0.9903 2.6118 0.2160 0.2494 5.7530 1.5780
-#> 58: 93.5195 -5.4358 -1.9459 -4.3041 -0.9076 0.1022 8.9155 2.1386 1.0220 2.5253 0.2220 0.2578 6.0138 1.4494
-#> 59: 93.5906 -5.4624 -1.9507 -4.3065 -0.9124 0.1374 8.4698 2.0317 1.0230 2.5539 0.2212 0.2449 5.7538 1.6021
-#> 60: 93.3308 -5.3784 -1.9540 -4.2417 -0.9173 0.1337 8.0463 1.9301 1.0298 2.4262 0.2173 0.2327 5.8841 1.4634
-#> 61: 93.3506 -5.4000 -1.9688 -4.2389 -0.9130 0.0942 7.6440 1.8336 1.0437 2.3049 0.2216 0.2210 6.0098 1.4243
-#> 62: 93.6969 -5.4175 -1.9467 -4.2389 -0.9135 0.1315 7.2618 1.7419 1.0213 2.2519 0.2250 0.2149 5.6278 1.4755
-#> 63: 93.6188 -5.3860 -1.9295 -4.2637 -0.9222 0.1196 7.8033 1.6548 1.0340 2.2699 0.2282 0.2282 5.6763 1.4755
-#> 64: 93.6782 -5.4118 -1.9518 -4.2655 -0.9298 0.1055 8.3519 1.5721 1.0227 2.4426 0.2317 0.2560 5.8006 1.4724
-#> 65: 93.5253 -5.4313 -1.9314 -4.2538 -0.9245 0.0919 7.9343 1.4980 1.0771 2.3486 0.2249 0.2635 5.8752 1.4850
-#> 66: 93.3192 -5.5672 -1.9715 -4.2575 -0.9224 0.1404 8.2293 1.9722 1.0233 2.3758 0.2365 0.2546 5.9462 1.5148
-#> 67: 93.0765 -5.4861 -1.9673 -4.2472 -0.9103 0.0935 8.3227 1.8736 0.9889 2.3305 0.2493 0.2419 5.7836 1.4946
-#> 68: 93.2666 -5.4963 -1.9635 -4.2435 -0.9093 0.0940 9.2911 1.7800 1.0050 2.3179 0.2495 0.2298 5.7104 1.4797
-#> 69: 93.3894 -5.5666 -1.9342 -4.2325 -0.9227 0.0957 9.0211 2.0287 1.0012 2.3052 0.2483 0.2348 5.8939 1.5158
-#> 70: 93.2671 -5.5710 -1.9486 -4.2723 -0.9323 0.1062 8.5700 2.1251 0.9714 2.3266 0.2498 0.2466 6.1562 1.5041
-#> 71: 92.9975 -5.5829 -1.9507 -4.2632 -0.9317 0.1166 8.1415 2.0322 0.9403 2.3654 0.2373 0.2454 5.8668 1.5122
-#> 72: 92.6364 -5.5255 -1.9888 -4.2605 -0.9255 0.1062 8.8866 1.9306 0.9680 2.4488 0.2314 0.2438 6.2101 1.5098
-#> 73: 92.4442 -5.5679 -1.9880 -4.3501 -0.9070 0.0972 9.1986 1.9203 0.9597 3.1091 0.2369 0.2412 6.1257 1.5029
-#> 74: 92.3866 -5.5447 -1.9895 -4.3137 -0.9004 0.0898 10.2222 1.8961 0.9573 2.9536 0.2494 0.2361 6.0474 1.4875
-#> 75: 92.2491 -5.6481 -1.9591 -4.3587 -0.8991 0.1028 9.7111 2.2694 1.0140 2.9121 0.2524 0.2243 6.0995 1.4780
-#> 76: 92.4656 -5.6014 -1.9860 -4.3538 -0.9015 0.0978 11.3121 2.1560 0.9861 2.9372 0.2489 0.2314 6.0996 1.4464
-#> 77: 92.5076 -5.5929 -1.9560 -4.3624 -0.9051 0.1008 12.0483 2.0482 1.0212 3.0132 0.2551 0.2378 5.9595 1.5081
-#> 78: 92.5987 -5.7000 -1.9592 -4.3611 -0.9131 0.0958 11.4458 2.3873 1.0062 2.9848 0.2549 0.2372 6.0385 1.4666
-#> 79: 92.4883 -5.7675 -1.9900 -4.4226 -0.9163 0.1153 10.8735 2.7867 0.9616 3.4984 0.2546 0.2309 5.9441 1.4722
-#> 80: 92.1716 -5.7782 -1.9810 -4.4398 -0.9122 0.1193 10.3299 3.0280 0.9642 3.6766 0.2520 0.2291 6.3013 1.4698
-#> 81: 92.1145 -5.8494 -1.9836 -4.3634 -0.9196 0.1013 9.8134 3.1850 0.9160 3.4927 0.2562 0.2409 6.2458 1.4664
-#> 82: 92.3761 -5.9668 -1.9722 -4.3888 -0.9240 0.1139 9.9738 3.9484 0.8923 3.3519 0.2434 0.2318 6.0987 1.4847
-#> 83: 92.7805 -6.1135 -1.9335 -4.3600 -0.9273 0.1027 11.2060 4.7684 0.8932 3.1843 0.2454 0.2202 5.9824 1.4920
-#> 84: 92.9601 -6.2190 -1.9374 -4.3187 -0.9376 0.1140 10.6457 5.6632 0.9077 3.0250 0.2464 0.2188 5.9979 1.5152
-#> 85: 92.4579 -6.1486 -1.9398 -4.3269 -0.9417 0.0979 10.1134 5.3800 0.9011 2.8738 0.2446 0.2330 5.7007 1.5648
-#> 86: 92.3580 -6.2177 -1.9549 -4.3287 -0.9510 0.1073 9.6077 5.1608 0.9318 2.7301 0.2497 0.2214 5.9916 1.5305
-#> 87: 92.8919 -6.3309 -1.9480 -4.3285 -0.9647 0.1009 9.1273 6.4577 0.9494 2.7023 0.2408 0.2126 5.9053 1.4313
-#> 88: 93.0621 -6.1220 -1.9623 -4.3341 -0.9624 0.1300 8.6710 6.1349 0.9563 2.6593 0.2404 0.2130 6.1925 1.4510
-#> 89: 92.7711 -6.2636 -1.9545 -4.3520 -0.9496 0.1227 8.2374 6.2143 0.9791 2.5862 0.2346 0.2333 5.9772 1.4523
-#> 90: 92.9148 -6.5481 -1.9586 -4.3275 -0.9496 0.1096 7.8255 8.2617 0.9787 2.4647 0.2346 0.2216 5.9136 1.4247
-#> 91: 92.8129 -6.4655 -1.9753 -4.3287 -0.9435 0.1210 9.1893 7.8487 0.9642 2.5304 0.2354 0.2268 5.9129 1.4229
-#> 92: 93.1090 -6.4752 -1.9841 -4.3533 -0.9428 0.1509 10.1133 7.7232 0.9160 2.6037 0.2457 0.2265 5.8601 1.4646
-#> 93: 93.4781 -6.3780 -1.9909 -4.3713 -0.9450 0.1544 9.6076 7.3370 0.9153 2.7656 0.2485 0.2499 5.9150 1.5180
-#> 94: 93.2125 -6.3021 -1.9798 -4.3459 -0.9470 0.1520 9.6738 6.9702 0.9314 2.6273 0.2428 0.2519 5.8752 1.4456
-#> 95: 93.0091 -5.9727 -1.9828 -4.3777 -0.9447 0.1370 9.6411 6.6217 0.9107 2.7137 0.2428 0.2556 5.8302 1.4477
-#> 96: 92.8731 -5.7813 -1.9952 -4.3343 -0.9352 0.1505 9.1590 6.2906 0.9011 2.5780 0.2366 0.2546 6.0545 1.4887
-#> 97: 92.7834 -5.8119 -1.9975 -4.3303 -0.9258 0.1231 8.8022 5.9760 0.9005 2.5331 0.2392 0.2419 5.9522 1.4754
-#> 98: 92.8447 -5.9773 -1.9940 -4.3353 -0.9301 0.1409 8.3621 5.6772 0.9244 2.4828 0.2426 0.2490 6.1027 1.4129
-#> 99: 93.1697 -5.8958 -1.9964 -4.3325 -0.9248 0.1411 7.9440 5.3934 0.9586 2.6138 0.2378 0.2545 6.2793 1.3719
-#> 100: 93.2536 -5.8481 -2.0009 -4.3408 -0.9304 0.1718 8.7965 5.1237 0.9290 2.6161 0.2398 0.2418 6.0908 1.4534
-#> 101: 93.2942 -5.8684 -1.9650 -4.3096 -0.9305 0.1496 9.7633 4.8675 0.9166 2.4853 0.2372 0.2565 5.9079 1.4948
-#> 102: 93.2636 -6.1363 -1.9517 -4.2653 -0.9235 0.1175 10.7772 5.1927 0.8944 2.3610 0.2448 0.2812 5.7748 1.5533
-#> 103: 92.6954 -5.9371 -1.9524 -4.2792 -0.9045 0.1288 10.2383 4.9331 0.8876 2.2429 0.2406 0.2720 5.5496 1.5601
-#> 104: 92.6149 -6.0650 -1.9532 -4.2752 -0.9048 0.0973 10.9914 4.6864 0.8845 2.1875 0.2475 0.2584 5.5593 1.4897
-#> 105: 92.8231 -5.9779 -1.9650 -4.2939 -0.9013 0.1112 10.4712 4.4521 0.9193 2.1985 0.2416 0.2455 5.4420 1.4910
-#> 106: 92.7599 -5.9602 -1.9594 -4.3018 -0.9026 0.1273 10.1396 4.2295 0.9308 2.1700 0.2453 0.2625 5.5458 1.4429
-#> 107: 93.1433 -5.9509 -1.9638 -4.2715 -0.9324 0.1385 9.6327 4.0415 0.9271 2.1026 0.2415 0.2626 5.4762 1.4286
-#> 108: 93.1354 -5.7359 -1.9691 -4.2962 -0.9256 0.1346 10.2794 3.8394 0.9387 2.1671 0.2412 0.2627 5.5107 1.4200
-#> 109: 92.9608 -5.8252 -1.9780 -4.3149 -0.9125 0.1564 9.7654 4.0619 0.9380 2.1731 0.2325 0.2657 5.8118 1.4379
-#> 110: 93.1043 -5.7632 -1.9874 -4.2868 -0.9113 0.1178 9.2771 3.8588 0.9420 2.1477 0.2214 0.2524 5.9352 1.4377
-#> 111: 92.8879 -5.7965 -1.9781 -4.2851 -0.9147 0.1107 8.8133 3.6659 0.9526 2.1891 0.2130 0.2398 5.6360 1.4461
-#> 112: 92.9347 -5.7484 -1.9460 -4.2825 -0.9195 0.1078 8.3726 3.4826 0.9710 2.2687 0.2051 0.2278 5.5771 1.5123
-#> 113: 92.7217 -5.7193 -1.9328 -4.2721 -0.9252 0.1021 7.9540 3.3085 1.0056 2.2848 0.2244 0.2164 5.7135 1.5082
-#> 114: 92.9944 -5.7382 -1.9414 -4.2835 -0.9210 0.1210 7.5563 3.1430 1.0184 2.2457 0.2260 0.2182 5.6799 1.4751
-#> 115: 93.1261 -5.8876 -1.9290 -4.2753 -0.9382 0.0960 9.7696 3.4406 1.0140 2.2745 0.2171 0.2073 5.3919 1.4919
-#> 116: 92.7669 -5.9842 -1.9484 -4.2828 -0.9504 0.1122 9.2811 4.1332 1.0202 2.2835 0.2160 0.2136 5.3651 1.5337
-#> 117: 92.9804 -5.9847 -1.9584 -4.2879 -0.9474 0.1234 9.2911 3.9265 0.9692 2.3115 0.2135 0.2163 5.1053 1.4774
-#> 118: 93.2853 -5.8443 -1.9494 -4.2700 -0.9400 0.1105 9.8572 3.7302 0.9736 2.2489 0.2192 0.2223 5.2416 1.4668
-#> 119: 93.2776 -5.8592 -1.9458 -4.2600 -0.9394 0.1072 9.3643 3.5437 0.9789 2.1964 0.2176 0.2205 5.2942 1.4847
-#> 120: 93.0335 -5.8156 -1.9453 -4.2623 -0.9437 0.1139 8.8961 3.3665 0.9698 2.2380 0.2206 0.2231 5.4427 1.4470
-#> 121: 93.0115 -5.8402 -1.9355 -4.2596 -0.9291 0.1138 8.4513 3.3018 0.9743 2.1463 0.2096 0.2120 5.1537 1.4487
-#> 122: 93.6277 -5.8852 -1.9276 -4.2787 -0.9419 0.1388 8.0287 3.4114 0.9438 2.1410 0.2072 0.2104 5.1198 1.5201
-#> 123: 93.4952 -6.0977 -1.9332 -4.2847 -0.9431 0.1412 7.6273 4.8225 0.9472 2.1335 0.2081 0.2129 5.2003 1.6193
-#> 124: 93.7207 -6.2280 -1.9105 -4.2692 -0.9551 0.1422 7.2459 5.4835 0.9657 2.0896 0.2148 0.2272 5.2901 1.5482
-#> 125: 93.6041 -6.0808 -1.9356 -4.2748 -0.9531 0.1184 7.0201 5.2094 0.9591 2.0421 0.2089 0.2158 5.3848 1.4896
-#> 126: 93.5193 -6.0164 -1.9296 -4.2890 -0.9600 0.1351 7.6848 4.9489 0.9931 2.1387 0.1989 0.2129 5.1988 1.4492
-#> 127: 93.7135 -5.9340 -1.9448 -4.2883 -0.9633 0.1428 8.3411 4.7014 0.9820 2.1192 0.1985 0.2046 5.3953 1.4985
-#> 128: 94.2312 -5.8849 -1.9404 -4.2754 -0.9633 0.1495 7.9240 4.4664 0.9884 2.0587 0.1902 0.2171 5.7113 1.4987
-#> 129: 94.0390 -5.8674 -1.9229 -4.3309 -0.9614 0.1472 8.5108 4.2430 1.0319 2.1023 0.1909 0.2154 5.5654 1.4294
-#> 130: 93.4178 -6.0458 -1.9224 -4.3364 -0.9560 0.1570 8.0852 4.4639 1.0184 2.2804 0.1869 0.2182 5.6585 1.4443
-#> 131: 93.5483 -6.2682 -1.9258 -4.3654 -0.9554 0.1449 7.6810 5.6020 1.0254 2.3477 0.1857 0.2230 5.4266 1.4324
-#> 132: 93.5180 -6.3297 -1.9204 -4.3577 -0.9640 0.1365 7.2969 5.5672 1.0354 2.3257 0.1788 0.2118 5.4913 1.4859
-#> 133: 93.4707 -6.0990 -1.9415 -4.3315 -0.9775 0.1232 6.9321 5.2888 1.0686 2.3421 0.1851 0.2012 5.8429 1.4618
-#> 134: 93.1012 -6.1236 -1.9308 -4.3409 -0.9654 0.1225 7.6471 5.0244 1.0517 2.4652 0.1947 0.2008 5.6902 1.5432
-#> 135: 93.2545 -6.1070 -1.9408 -4.3415 -0.9553 0.1228 9.2701 4.7732 1.0160 2.3607 0.1919 0.1907 5.5154 1.5317
-#> 136: 93.3338 -6.0321 -1.9336 -4.3074 -0.9598 0.1120 8.8066 4.5345 0.9652 2.2427 0.1999 0.2249 5.3667 1.6036
-#> 137: 93.5910 -6.0627 -1.9339 -4.3074 -0.9529 0.1407 8.3663 4.3078 0.9538 2.2128 0.1966 0.2195 5.2959 1.6015
-#> 138: 93.6338 -5.9702 -1.9252 -4.3105 -0.9615 0.1373 7.9480 4.0924 0.9875 2.2635 0.1964 0.2218 5.4532 1.5261
-#> 139: 93.6403 -5.8913 -1.9237 -4.2962 -0.9582 0.1165 8.0749 3.8878 0.9746 2.2457 0.1972 0.2125 5.9356 1.5173
-#> 140: 92.8503 -5.8314 -1.9452 -4.3180 -0.9487 0.1142 8.6356 3.6934 0.9933 2.2044 0.1961 0.2019 5.7908 1.5138
-#> 141: 93.1249 -6.0584 -1.9448 -4.3139 -0.9367 0.0950 8.9231 4.4196 1.0220 2.2246 0.2079 0.2077 6.0233 1.4339
-#> 142: 93.1846 -6.3026 -1.9152 -4.3093 -0.9392 0.0866 10.1508 5.9592 1.0562 2.3325 0.2082 0.2133 5.5285 1.4832
-#> 143: 92.4682 -6.1485 -1.9146 -4.2812 -0.9376 0.0260 9.6433 5.6613 1.0618 2.3594 0.2000 0.2027 6.0573 1.4428
-#> 144: 92.7792 -6.1108 -1.8939 -4.2740 -0.9341 0.0765 9.1611 5.3782 1.0917 2.3074 0.2057 0.2240 6.2141 1.4953
-#> 145: 93.1314 -6.2086 -1.8939 -4.3580 -0.9341 0.0741 8.7031 5.1093 1.0931 2.7164 0.2105 0.2229 5.8543 1.4855
-#> 146: 93.2254 -6.2170 -1.8998 -4.3724 -0.9311 0.0677 8.2679 5.0506 1.0811 2.8434 0.2049 0.2118 5.5455 1.4763
-#> 147: 93.3264 -6.0136 -1.8998 -4.3853 -0.9328 0.0817 9.4673 4.7980 1.0668 2.8512 0.2009 0.2114 5.5518 1.5225
-#> 148: 93.2298 -5.9143 -1.8921 -4.5001 -0.9296 0.1057 8.9939 4.5581 1.0563 3.8266 0.1982 0.2043 5.5242 1.5614
-#> 149: 93.3604 -5.9894 -1.8832 -4.5223 -0.9338 0.0858 8.5442 4.3302 1.0544 4.3930 0.1986 0.2003 5.4353 1.4957
-#> 150: 93.4715 -5.9630 -1.8833 -4.4796 -0.9335 0.0827 8.1170 4.1137 1.0912 4.1733 0.1984 0.1903 5.7477 1.4554
-#> 151: 93.3385 -5.8026 -1.9052 -4.4507 -0.9368 0.0684 8.7726 3.9080 1.1249 3.9647 0.2074 0.1808 5.7693 1.4400
-#> 152: 93.1682 -5.8529 -1.9441 -4.3545 -0.9309 0.0752 8.8042 3.1783 1.0496 3.0168 0.2069 0.1688 5.9161 1.4565
-#> 153: 93.0559 -6.0261 -1.9425 -4.3431 -0.9327 0.1016 9.1435 3.9939 1.0120 2.8470 0.1894 0.1509 5.4435 1.5486
-#> 154: 92.8582 -6.0887 -1.9278 -4.3094 -0.9352 0.1064 8.4316 4.2991 0.9819 2.6257 0.1907 0.1609 5.4587 1.5208
-#> 155: 93.3200 -5.8480 -1.9149 -4.3363 -0.9294 0.1143 9.6700 3.1734 0.9942 2.6441 0.1824 0.1906 5.5193 1.6410
-#> 156: 93.3199 -5.9053 -1.9213 -4.3163 -0.9369 0.1291 7.5899 3.5902 0.9823 2.4648 0.1770 0.1956 5.3816 1.5356
-#> 157: 93.2434 -5.8763 -1.9161 -4.3035 -0.9549 0.1075 8.4137 3.2576 0.9935 2.5007 0.1795 0.1852 5.4053 1.5706
-#> 158: 93.1494 -5.9243 -1.8929 -4.3162 -0.9680 0.1296 8.2959 3.3262 1.0029 2.4943 0.1866 0.1921 5.4369 1.5510
-#> 159: 93.5683 -6.0335 -1.9127 -4.3040 -0.9675 0.1271 7.7222 4.0079 0.9768 2.5765 0.1869 0.2028 5.7165 1.4968
-#> 160: 93.9417 -6.0018 -1.9085 -4.2818 -0.9611 0.1161 5.8791 4.4991 0.9658 2.4933 0.1878 0.1986 6.0579 1.5272
-#> 161: 94.1252 -5.9264 -1.8943 -4.2805 -0.9645 0.0860 4.9517 3.6307 0.9754 2.4988 0.1934 0.1785 5.7457 1.5878
-#> 162: 93.9389 -5.7613 -1.8946 -4.2410 -0.9752 0.0898 6.7269 2.5865 1.0184 2.4379 0.1933 0.1908 5.9052 1.5215
-#> 163: 93.5890 -5.7243 -1.8992 -4.2636 -0.9722 0.0759 8.4484 2.5137 1.0151 2.3869 0.1928 0.1889 5.4694 1.5048
-#> 164: 93.9751 -5.7314 -1.8786 -4.3271 -0.9702 0.1020 6.6884 2.5136 1.0133 2.8395 0.1907 0.1998 5.4625 1.4854
-#> 165: 93.9708 -5.7409 -1.8856 -4.3129 -0.9616 0.1094 5.8809 2.4589 1.0401 2.6662 0.1912 0.1998 5.4339 1.4549
-#> 166: 93.9265 -5.6937 -1.9134 -4.3080 -0.9702 0.1151 5.6940 2.4086 1.0065 2.6864 0.1983 0.1987 5.6907 1.4857
-#> 167: 93.4157 -5.7312 -1.9163 -4.3286 -0.9638 0.1216 5.1230 2.5468 1.0487 2.5930 0.1917 0.1940 5.5938 1.4267
-#> 168: 93.3701 -5.8757 -1.9196 -4.3493 -0.9579 0.1134 6.0802 3.3929 1.0517 2.6981 0.1888 0.2063 5.4125 1.4365
-#> 169: 93.4342 -6.0262 -1.9041 -4.3347 -0.9526 0.0997 6.0780 3.6349 1.0623 2.7344 0.1946 0.1978 5.4930 1.4594
-#> 170: 93.3751 -6.1195 -1.9093 -4.3541 -0.9872 0.0834 6.8972 4.0337 1.0763 2.8428 0.2077 0.2005 5.6759 1.4455
-#> 171: 93.3603 -6.0360 -1.9196 -4.4632 -0.9763 0.0866 7.4236 3.6025 1.0684 3.7611 0.2046 0.1894 5.6282 1.4414
-#> 172: 93.2776 -5.9538 -1.9031 -4.4815 -0.9779 0.1024 5.4751 3.2802 1.0599 3.9487 0.2115 0.1990 5.6116 1.4230
-#> 173: 93.4470 -5.8580 -1.9193 -4.4170 -0.9641 0.0957 5.6416 2.8005 1.0440 3.4509 0.2066 0.1863 5.5804 1.4485
-#> 174: 93.2952 -5.8590 -1.9010 -4.3600 -0.9640 0.0789 6.4314 2.9503 1.0808 2.9773 0.2045 0.1969 5.4423 1.4421
-#> 175: 93.3756 -5.7733 -1.8959 -4.3621 -0.9504 0.0609 6.1723 2.5287 1.0950 3.0019 0.2127 0.2053 5.4338 1.4470
-#> 176: 93.1450 -5.8266 -1.9053 -4.3401 -0.9457 0.0633 6.5237 3.0522 1.0942 2.9464 0.2134 0.2021 5.6501 1.3664
-#> 177: 92.7723 -5.9978 -1.9231 -4.3529 -0.9524 0.0658 7.4519 4.2374 1.0640 3.0260 0.2158 0.2146 5.9180 1.4100
-#> 178: 92.7261 -5.9836 -1.9189 -4.3349 -0.9576 0.0768 5.5211 4.2557 1.0611 2.8827 0.2169 0.2088 5.8872 1.4206
-#> 179: 92.9599 -6.0071 -1.9259 -4.3081 -0.9581 0.0657 6.0953 3.8205 1.0816 2.6709 0.2122 0.2014 5.8221 1.4026
-#> 180: 93.0831 -6.1544 -1.9400 -4.3018 -0.9496 0.0411 4.2312 4.9005 1.1064 2.6542 0.2143 0.2221 6.3264 1.3820
-#> 181: 92.8840 -6.0889 -1.9364 -4.3200 -0.9566 0.0861 4.2186 4.4615 1.0930 2.7270 0.2142 0.2424 6.0486 1.4035
-#> 182: 93.1913 -6.1457 -1.9384 -4.3085 -0.9606 0.0733 6.2878 4.6026 1.0917 2.6393 0.2131 0.2151 5.7042 1.4952
-#> 183: 93.1218 -6.3114 -1.9355 -4.2883 -0.9742 0.0741 7.2675 5.1377 1.0914 2.5060 0.2220 0.2111 5.5099 1.4097
-#> 184: 93.1462 -6.3147 -1.9068 -4.2880 -0.9653 0.0893 7.6928 5.6510 1.0563 2.5066 0.2256 0.2201 5.4138 1.5319
-#> 185: 93.1825 -6.3608 -1.9265 -4.2815 -0.9549 0.0873 7.1340 5.9801 1.0363 2.4788 0.2177 0.1958 5.4202 1.4569
-#> 186: 93.6270 -6.1413 -1.9278 -4.2702 -0.9696 0.1185 6.7652 4.5535 1.0400 2.3673 0.2163 0.1932 5.3005 1.5012
-#> 187: 93.9922 -6.3364 -1.9269 -4.2702 -0.9729 0.1197 7.7694 6.1592 0.9948 2.3673 0.2196 0.2091 5.3075 1.5105
-#> 188: 93.8884 -6.0236 -1.9207 -4.2928 -0.9900 0.1343 7.8090 4.2847 0.9840 2.4238 0.2195 0.1966 5.2861 1.5607
-#> 189: 94.3110 -6.0809 -1.9145 -4.2826 -0.9840 0.1224 8.5580 4.0998 0.9800 2.4505 0.2294 0.1840 5.7107 1.5180
-#> 190: 94.0039 -6.0996 -1.9140 -4.2793 -0.9782 0.1429 10.6594 4.1655 0.9796 2.4415 0.2297 0.1960 5.7533 1.5720
-#> 191: 93.9692 -6.1129 -1.9362 -4.3261 -0.9705 0.1462 8.8201 4.3146 1.0124 2.4625 0.2287 0.2049 5.5670 1.5206
-#> 192: 93.3178 -5.9759 -1.9192 -4.3378 -0.9664 0.1434 8.8047 3.7150 1.0282 2.4137 0.2243 0.1977 5.3858 1.4599
-#> 193: 93.1427 -5.9388 -1.9391 -4.3211 -0.9650 0.1401 7.1862 3.2835 1.0218 2.3216 0.2163 0.1866 5.3930 1.5017
-#> 194: 93.0588 -6.0605 -1.9361 -4.3350 -0.9462 0.1330 6.8930 4.0020 1.0166 2.3186 0.2057 0.1818 5.2535 1.5075
-#> 195: 93.1820 -6.1201 -1.9579 -4.3034 -0.9534 0.1557 8.1300 4.4218 0.9932 2.1873 0.2099 0.1834 5.4862 1.4698
-#> 196: 93.2230 -5.8879 -1.9725 -4.2965 -0.9584 0.1390 8.1307 3.0777 1.0051 2.1597 0.2089 0.1683 5.7058 1.3970
-#> 197: 93.3504 -5.8829 -1.9677 -4.3075 -0.9577 0.1638 6.7115 3.0660 1.0050 2.1377 0.2024 0.1642 5.4691 1.5016
-#> 198: 93.3016 -5.8771 -1.9885 -4.3241 -0.9605 0.1562 6.4722 3.0381 0.9727 2.2053 0.1975 0.1683 5.3434 1.4885
-#> 199: 93.2464 -5.8787 -1.9871 -4.3430 -0.9528 0.1751 4.5894 3.0445 0.9748 2.2247 0.1886 0.1780 5.4469 1.4405
-#> 200: 93.3474 -5.7995 -1.9767 -4.3298 -0.9480 0.1947 4.7024 2.8535 0.9895 2.2234 0.1951 0.2012 5.5130 1.4641
-#> 201: 93.3231 -5.8169 -1.9737 -4.3268 -0.9510 0.1804 4.4248 2.8913 0.9738 2.2141 0.1955 0.2057 5.5422 1.4843
-#> 202: 93.3484 -5.8009 -1.9732 -4.3240 -0.9519 0.1674 4.4068 2.8084 0.9736 2.2040 0.1959 0.2033 5.5843 1.4744
-#> 203: 93.2617 -5.7915 -1.9678 -4.3211 -0.9535 0.1629 4.5333 2.7678 0.9877 2.1980 0.1961 0.2023 5.6265 1.4811
-#> 204: 93.2210 -5.8071 -1.9647 -4.3220 -0.9504 0.1629 4.6144 2.8347 0.9922 2.1938 0.1937 0.2013 5.5745 1.4988
-#> 205: 93.1914 -5.8104 -1.9667 -4.3225 -0.9484 0.1593 4.5880 2.8639 0.9931 2.1952 0.1916 0.1979 5.5960 1.5057
-#> 206: 93.1827 -5.8348 -1.9697 -4.3236 -0.9498 0.1587 4.7189 3.0353 0.9929 2.2016 0.1922 0.1947 5.6096 1.5136
-#> 207: 93.2017 -5.8760 -1.9714 -4.3239 -0.9518 0.1592 4.8171 3.2659 0.9947 2.2042 0.1927 0.1910 5.6413 1.5078
-#> 208: 93.2226 -5.8819 -1.9736 -4.3261 -0.9532 0.1610 4.8241 3.2964 0.9957 2.2122 0.1938 0.1878 5.6704 1.5031
-#> 209: 93.2158 -5.8786 -1.9743 -4.3278 -0.9538 0.1595 4.6275 3.2763 0.9963 2.2279 0.1950 0.1848 5.6758 1.5038
-#> 210: 93.2216 -5.8798 -1.9746 -4.3286 -0.9535 0.1589 4.5667 3.2857 0.9974 2.2473 0.1948 0.1834 5.6707 1.5054
-#> 211: 93.2238 -5.8847 -1.9763 -4.3302 -0.9530 0.1591 4.5745 3.2932 0.9956 2.2576 0.1948 0.1823 5.6691 1.4990
-#> 212: 93.2242 -5.8893 -1.9777 -4.3323 -0.9532 0.1600 4.6203 3.2955 0.9938 2.2704 0.1958 0.1814 5.6732 1.4994
-#> 213: 93.2246 -5.8950 -1.9756 -4.3345 -0.9532 0.1588 4.7363 3.3106 0.9894 2.2864 0.1960 0.1791 5.6401 1.5015
-#> 214: 93.2056 -5.9070 -1.9740 -4.3368 -0.9532 0.1586 4.7814 3.3538 0.9888 2.3047 0.1960 0.1761 5.6265 1.5008
-#> 215: 93.2126 -5.9157 -1.9720 -4.3405 -0.9533 0.1580 4.9117 3.3916 0.9890 2.3191 0.1959 0.1742 5.6054 1.5015
-#> 216: 93.2161 -5.9242 -1.9716 -4.3423 -0.9533 0.1594 5.0163 3.4425 0.9897 2.3291 0.1959 0.1739 5.5975 1.5005
-#> 217: 93.2193 -5.9351 -1.9715 -4.3445 -0.9537 0.1614 4.9927 3.5085 0.9905 2.3309 0.1957 0.1739 5.5905 1.5024
-#> 218: 93.1973 -5.9314 -1.9725 -4.3479 -0.9548 0.1640 5.0502 3.4902 0.9918 2.3344 0.1952 0.1740 5.5909 1.5046
-#> 219: 93.1938 -5.9312 -1.9729 -4.3508 -0.9539 0.1664 5.0446 3.4901 0.9922 2.3365 0.1949 0.1746 5.5808 1.5046
-#> 220: 93.1994 -5.9424 -1.9734 -4.3531 -0.9536 0.1683 5.0462 3.5593 0.9917 2.3370 0.1945 0.1754 5.5831 1.5055
-#> 221: 93.2015 -5.9511 -1.9746 -4.3550 -0.9537 0.1702 5.1062 3.6002 0.9899 2.3368 0.1945 0.1762 5.5731 1.5043
-#> 222: 93.2057 -5.9653 -1.9756 -4.3571 -0.9541 0.1718 5.1727 3.6876 0.9886 2.3364 0.1943 0.1776 5.5813 1.5047
-#> 223: 93.1998 -5.9723 -1.9761 -4.3592 -0.9540 0.1726 5.1866 3.7239 0.9871 2.3428 0.1940 0.1791 5.5702 1.5047
-#> 224: 93.2042 -5.9799 -1.9768 -4.3615 -0.9540 0.1734 5.1516 3.7613 0.9849 2.3531 0.1934 0.1809 5.5705 1.5039
-#> 225: 93.1974 -5.9813 -1.9776 -4.3648 -0.9540 0.1740 5.1225 3.7676 0.9840 2.3663 0.1929 0.1834 5.5698 1.5030
-#> 226: 93.1963 -5.9807 -1.9777 -4.3679 -0.9535 0.1751 5.1632 3.7694 0.9839 2.3785 0.1927 0.1850 5.5676 1.5069
-#> 227: 93.1912 -5.9740 -1.9783 -4.3707 -0.9533 0.1768 5.1987 3.7421 0.9835 2.3931 0.1922 0.1855 5.5597 1.5091
-#> 228: 93.1902 -5.9799 -1.9792 -4.3745 -0.9533 0.1784 5.2070 3.7641 0.9825 2.4134 0.1917 0.1861 5.5502 1.5086
-#> 229: 93.1903 -5.9894 -1.9805 -4.3792 -0.9533 0.1796 5.2398 3.8109 0.9812 2.4382 0.1910 0.1870 5.5486 1.5075
-#> 230: 93.1833 -5.9946 -1.9816 -4.3836 -0.9530 0.1814 5.2357 3.8346 0.9800 2.4614 0.1904 0.1883 5.5515 1.5065
-#> 231: 93.1740 -6.0001 -1.9834 -4.3871 -0.9528 0.1833 5.2848 3.8635 0.9783 2.4814 0.1898 0.1893 5.5526 1.5057
-#> 232: 93.1581 -6.0071 -1.9852 -4.3904 -0.9523 0.1857 5.3056 3.8967 0.9766 2.5002 0.1891 0.1904 5.5571 1.5057
-#> 233: 93.1417 -6.0131 -1.9865 -4.3933 -0.9517 0.1869 5.3290 3.9227 0.9745 2.5129 0.1885 0.1909 5.5609 1.5069
-#> 234: 93.1245 -6.0198 -1.9878 -4.3961 -0.9514 0.1880 5.3062 3.9567 0.9731 2.5269 0.1886 0.1916 5.5645 1.5074
-#> 235: 93.1084 -6.0269 -1.9885 -4.3985 -0.9514 0.1892 5.3213 3.9969 0.9729 2.5390 0.1887 0.1931 5.5722 1.5065
-#> 236: 93.1037 -6.0382 -1.9897 -4.4009 -0.9517 0.1899 5.3601 4.0674 0.9744 2.5501 0.1886 0.1949 5.5811 1.5066
-#> 237: 93.0989 -6.0432 -1.9906 -4.4031 -0.9518 0.1909 5.3744 4.0877 0.9755 2.5623 0.1885 0.1964 5.5890 1.5051
-#> 238: 93.0932 -6.0433 -1.9912 -4.4041 -0.9521 0.1915 5.4192 4.0775 0.9772 2.5698 0.1886 0.1980 5.5980 1.5029
-#> 239: 93.0943 -6.0475 -1.9913 -4.4056 -0.9520 0.1921 5.4483 4.0960 0.9792 2.5785 0.1888 0.1997 5.5999 1.5011
-#> 240: 93.0904 -6.0498 -1.9909 -4.4070 -0.9520 0.1925 5.4921 4.1095 0.9814 2.5867 0.1887 0.2011 5.5974 1.5013
-#> 241: 93.0883 -6.0508 -1.9910 -4.4086 -0.9520 0.1931 5.5503 4.1140 0.9827 2.5966 0.1887 0.2023 5.6049 1.4997
-#> 242: 93.0884 -6.0487 -1.9916 -4.4102 -0.9517 0.1940 5.5634 4.1021 0.9831 2.6059 0.1886 0.2039 5.6116 1.5005
-#> 243: 93.0836 -6.0466 -1.9920 -4.4123 -0.9517 0.1950 5.5786 4.0878 0.9837 2.6204 0.1887 0.2054 5.6217 1.5000
-#> 244: 93.0756 -6.0477 -1.9926 -4.4149 -0.9517 0.1956 5.5827 4.0904 0.9843 2.6385 0.1887 0.2070 5.6306 1.4995
-#> 245: 93.0664 -6.0533 -1.9930 -4.4174 -0.9514 0.1963 5.6228 4.1208 0.9857 2.6549 0.1888 0.2086 5.6346 1.4996
-#> 246: 93.0643 -6.0543 -1.9931 -4.4200 -0.9511 0.1969 5.6236 4.1257 0.9872 2.6735 0.1886 0.2096 5.6381 1.4989
-#> 247: 93.0631 -6.0568 -1.9929 -4.4227 -0.9511 0.1974 5.6045 4.1389 0.9889 2.6910 0.1886 0.2107 5.6408 1.4984
-#> 248: 93.0636 -6.0567 -1.9924 -4.4264 -0.9513 0.1974 5.6016 4.1412 0.9906 2.7225 0.1886 0.2117 5.6424 1.4992
-#> 249: 93.0727 -6.0560 -1.9920 -4.4302 -0.9514 0.1973 5.6088 4.1383 0.9922 2.7584 0.1885 0.2125 5.6441 1.4992
-#> 250: 93.0865 -6.0551 -1.9915 -4.4337 -0.9512 0.1973 5.6127 4.1386 0.9941 2.7852 0.1884 0.2135 5.6522 1.4977
-#> 251: 93.0887 -6.0551 -1.9910 -4.4364 -0.9511 0.1967 5.5869 4.1455 0.9964 2.8060 0.1883 0.2146 5.6561 1.4968
-#> 252: 93.0877 -6.0522 -1.9904 -4.4376 -0.9511 0.1964 5.5778 4.1346 0.9987 2.8151 0.1883 0.2155 5.6583 1.4964
-#> 253: 93.0843 -6.0518 -1.9897 -4.4391 -0.9512 0.1961 5.5948 4.1323 1.0011 2.8253 0.1884 0.2164 5.6588 1.4972
-#> 254: 93.0818 -6.0518 -1.9896 -4.4399 -0.9512 0.1957 5.6122 4.1352 1.0016 2.8319 0.1882 0.2169 5.6573 1.4991
-#> 255: 93.0838 -6.0524 -1.9895 -4.4401 -0.9514 0.1954 5.6310 4.1366 1.0025 2.8408 0.1880 0.2174 5.6584 1.4996
-#> 256: 93.0850 -6.0579 -1.9892 -4.4400 -0.9515 0.1948 5.6526 4.1752 1.0043 2.8482 0.1879 0.2181 5.6611 1.4979
-#> 257: 93.0868 -6.0600 -1.9890 -4.4391 -0.9517 0.1940 5.6742 4.1941 1.0055 2.8499 0.1878 0.2189 5.6649 1.4985
-#> 258: 93.0873 -6.0606 -1.9888 -4.4391 -0.9518 0.1932 5.7088 4.2037 1.0066 2.8552 0.1877 0.2196 5.6668 1.4983
-#> 259: 93.0912 -6.0650 -1.9882 -4.4377 -0.9519 0.1925 5.7494 4.2300 1.0080 2.8537 0.1877 0.2204 5.6729 1.4977
-#> 260: 93.0964 -6.0699 -1.9874 -4.4362 -0.9519 0.1918 5.7609 4.2588 1.0100 2.8513 0.1877 0.2212 5.6792 1.4974
-#> 261: 93.1014 -6.0737 -1.9866 -4.4350 -0.9522 0.1913 5.7971 4.2807 1.0115 2.8496 0.1877 0.2220 5.6812 1.4969
-#> 262: 93.1064 -6.0734 -1.9859 -4.4346 -0.9526 0.1909 5.7936 4.2719 1.0129 2.8505 0.1877 0.2228 5.6824 1.4958
-#> 263: 93.1092 -6.0783 -1.9850 -4.4344 -0.9530 0.1906 5.8078 4.2973 1.0141 2.8525 0.1879 0.2233 5.6815 1.4954
-#> 264: 93.1128 -6.0830 -1.9842 -4.4338 -0.9535 0.1901 5.8245 4.3273 1.0146 2.8527 0.1880 0.2237 5.6768 1.4958
-#> 265: 93.1198 -6.0874 -1.9834 -4.4331 -0.9541 0.1895 5.8467 4.3490 1.0149 2.8522 0.1880 0.2238 5.6693 1.4965
-#> 266: 93.1284 -6.0890 -1.9828 -4.4327 -0.9546 0.1888 5.8350 4.3488 1.0149 2.8513 0.1881 0.2239 5.6650 1.4970
-#> 267: 93.1380 -6.0926 -1.9819 -4.4326 -0.9549 0.1883 5.8440 4.3677 1.0156 2.8526 0.1883 0.2240 5.6609 1.4974
-#> 268: 93.1480 -6.0915 -1.9810 -4.4321 -0.9552 0.1873 5.8565 4.3552 1.0163 2.8522 0.1886 0.2238 5.6537 1.4990
-#> 269: 93.1539 -6.0910 -1.9803 -4.4314 -0.9556 0.1866 5.8709 4.3438 1.0179 2.8503 0.1888 0.2237 5.6495 1.4989
-#> 270: 93.1620 -6.0898 -1.9798 -4.4311 -0.9561 0.1861 5.8678 4.3301 1.0197 2.8507 0.1890 0.2235 5.6466 1.4984
-#> 271: 93.1668 -6.0881 -1.9792 -4.4305 -0.9565 0.1857 5.8508 4.3147 1.0209 2.8487 0.1891 0.2234 5.6487 1.4997
-#> 272: 93.1725 -6.0848 -1.9787 -4.4300 -0.9569 0.1855 5.8431 4.2948 1.0217 2.8474 0.1894 0.2233 5.6488 1.5000
-#> 273: 93.1770 -6.0809 -1.9783 -4.4297 -0.9572 0.1850 5.8432 4.2739 1.0227 2.8470 0.1897 0.2235 5.6497 1.5000
-#> 274: 93.1797 -6.0774 -1.9776 -4.4299 -0.9574 0.1846 5.8549 4.2532 1.0243 2.8494 0.1901 0.2235 5.6511 1.5003
-#> 275: 93.1829 -6.0759 -1.9774 -4.4303 -0.9578 0.1845 5.8633 4.2387 1.0255 2.8514 0.1906 0.2234 5.6561 1.5010
-#> 276: 93.1846 -6.0764 -1.9771 -4.4303 -0.9581 0.1845 5.8738 4.2322 1.0267 2.8523 0.1911 0.2232 5.6554 1.5020
-#> 277: 93.1880 -6.0792 -1.9768 -4.4305 -0.9584 0.1844 5.8980 4.2423 1.0278 2.8541 0.1915 0.2229 5.6586 1.5019
-#> 278: 93.1920 -6.0791 -1.9766 -4.4307 -0.9586 0.1841 5.9368 4.2391 1.0289 2.8559 0.1919 0.2226 5.6600 1.5024
-#> 279: 93.1892 -6.0786 -1.9766 -4.4310 -0.9586 0.1839 5.9822 4.2309 1.0300 2.8584 0.1925 0.2226 5.6642 1.5015
-#> 280: 93.1868 -6.0782 -1.9765 -4.4311 -0.9587 0.1836 6.0381 4.2253 1.0311 2.8616 0.1930 0.2227 5.6686 1.5008
-#> 281: 93.1805 -6.0781 -1.9764 -4.4309 -0.9586 0.1832 6.0718 4.2228 1.0325 2.8626 0.1936 0.2227 5.6741 1.5002
-#> 282: 93.1780 -6.0768 -1.9762 -4.4318 -0.9585 0.1829 6.0867 4.2160 1.0341 2.8701 0.1941 0.2228 5.6740 1.4998
-#> 283: 93.1777 -6.0736 -1.9760 -4.4325 -0.9583 0.1825 6.1250 4.2003 1.0355 2.8768 0.1946 0.2228 5.6761 1.5010
-#> 284: 93.1745 -6.0726 -1.9757 -4.4337 -0.9582 0.1823 6.1509 4.1975 1.0370 2.8843 0.1951 0.2227 5.6764 1.5009
-#> 285: 93.1742 -6.0719 -1.9755 -4.4348 -0.9579 0.1820 6.1652 4.1936 1.0381 2.8910 0.1954 0.2225 5.6773 1.5011
-#> 286: 93.1706 -6.0698 -1.9754 -4.4356 -0.9576 0.1818 6.1840 4.1844 1.0394 2.8966 0.1958 0.2224 5.6780 1.5011
-#> 287: 93.1672 -6.0678 -1.9752 -4.4370 -0.9573 0.1816 6.2123 4.1767 1.0400 2.9079 0.1963 0.2224 5.6757 1.5015
-#> 288: 93.1628 -6.0658 -1.9753 -4.4379 -0.9572 0.1815 6.2355 4.1700 1.0407 2.9150 0.1967 0.2223 5.6742 1.5013
-#> 289: 93.1588 -6.0628 -1.9753 -4.4389 -0.9569 0.1818 6.2435 4.1565 1.0416 2.9217 0.1969 0.2218 5.6777 1.5007
-#> 290: 93.1560 -6.0590 -1.9754 -4.4399 -0.9565 0.1820 6.2564 4.1394 1.0425 2.9291 0.1971 0.2214 5.6778 1.5006
-#> 291: 93.1552 -6.0555 -1.9754 -4.4409 -0.9562 0.1821 6.2753 4.1246 1.0435 2.9375 0.1973 0.2210 5.6779 1.5009
-#> 292: 93.1546 -6.0541 -1.9754 -4.4415 -0.9558 0.1820 6.2881 4.1183 1.0444 2.9414 0.1975 0.2205 5.6762 1.5006
-#> 293: 93.1506 -6.0535 -1.9756 -4.4424 -0.9555 0.1821 6.2856 4.1182 1.0454 2.9474 0.1976 0.2200 5.6770 1.4994
-#> 294: 93.1453 -6.0520 -1.9758 -4.4424 -0.9553 0.1819 6.2733 4.1124 1.0463 2.9487 0.1979 0.2195 5.6792 1.4985
-#> 295: 93.1431 -6.0487 -1.9760 -4.4421 -0.9551 0.1820 6.2655 4.1009 1.0469 2.9498 0.1982 0.2190 5.6797 1.4989
-#> 296: 93.1425 -6.0460 -1.9760 -4.4432 -0.9548 0.1818 6.2801 4.0912 1.0478 2.9566 0.1984 0.2185 5.6795 1.4989
-#> 297: 93.1403 -6.0442 -1.9761 -4.4440 -0.9545 0.1818 6.2979 4.0836 1.0485 2.9626 0.1987 0.2182 5.6783 1.4978
-#> 298: 93.1400 -6.0438 -1.9763 -4.4440 -0.9543 0.1817 6.3069 4.0842 1.0492 2.9646 0.1989 0.2178 5.6783 1.4968
-#> 299: 93.1373 -6.0426 -1.9764 -4.4445 -0.9540 0.1813 6.3134 4.0790 1.0505 2.9694 0.1991 0.2175 5.6800 1.4953
-#> 300: 93.1340 -6.0412 -1.9764 -4.4450 -0.9538 0.1811 6.3192 4.0731 1.0516 2.9744 0.1993 0.2171 5.6782 1.4938
-#> 301: 93.1330 -6.0402 -1.9766 -4.4455 -0.9535 0.1808 6.3278 4.0685 1.0531 2.9784 0.1996 0.2167 5.6819 1.4925
-#> 302: 93.1308 -6.0402 -1.9768 -4.4457 -0.9534 0.1806 6.3417 4.0684 1.0549 2.9813 0.1998 0.2163 5.6824 1.4905
-#> 303: 93.1294 -6.0373 -1.9769 -4.4459 -0.9532 0.1804 6.3489 4.0538 1.0565 2.9838 0.2000 0.2159 5.6841 1.4890
-#> 304: 93.1304 -6.0345 -1.9771 -4.4461 -0.9530 0.1801 6.3543 4.0409 1.0581 2.9859 0.2002 0.2155 5.6869 1.4875
-#> 305: 93.1287 -6.0319 -1.9772 -4.4463 -0.9528 0.1800 6.3496 4.0293 1.0597 2.9882 0.2003 0.2151 5.6902 1.4867
-#> 306: 93.1261 -6.0301 -1.9775 -4.4474 -0.9527 0.1802 6.3479 4.0231 1.0614 2.9989 0.2003 0.2145 5.6963 1.4856
-#> 307: 93.1232 -6.0284 -1.9777 -4.4479 -0.9526 0.1802 6.3507 4.0135 1.0629 3.0036 0.2004 0.2141 5.6987 1.4849
-#> 308: 93.1192 -6.0264 -1.9779 -4.4483 -0.9524 0.1802 6.3641 4.0019 1.0644 3.0084 0.2004 0.2135 5.6991 1.4837
-#> 309: 93.1137 -6.0253 -1.9783 -4.4487 -0.9522 0.1803 6.3579 3.9953 1.0658 3.0133 0.2004 0.2130 5.7035 1.4826
-#> 310: 93.1100 -6.0223 -1.9787 -4.4489 -0.9520 0.1804 6.3423 3.9800 1.0665 3.0171 0.2005 0.2126 5.7061 1.4822
-#> 311: 93.1044 -6.0215 -1.9791 -4.4496 -0.9517 0.1804 6.3365 3.9744 1.0675 3.0251 0.2005 0.2121 5.7092 1.4816
-#> 312: 93.1006 -6.0206 -1.9795 -4.4501 -0.9516 0.1806 6.3317 3.9681 1.0688 3.0321 0.2006 0.2115 5.7128 1.4805
-#> 313: 93.0951 -6.0194 -1.9797 -4.4499 -0.9516 0.1805 6.3297 3.9609 1.0702 3.0333 0.2008 0.2109 5.7137 1.4805
-#> 314: 93.0922 -6.0192 -1.9800 -4.4497 -0.9515 0.1804 6.3486 3.9570 1.0715 3.0345 0.2009 0.2104 5.7144 1.4800
-#> 315: 93.0883 -6.0186 -1.9804 -4.4495 -0.9515 0.1803 6.3712 3.9528 1.0726 3.0351 0.2011 0.2100 5.7156 1.4794
-#> 316: 93.0808 -6.0182 -1.9808 -4.4492 -0.9514 0.1802 6.3979 3.9483 1.0738 3.0345 0.2013 0.2097 5.7164 1.4792
-#> 317: 93.0758 -6.0174 -1.9813 -4.4487 -0.9513 0.1801 6.4377 3.9428 1.0747 3.0327 0.2015 0.2094 5.7175 1.4787
-#> 318: 93.0713 -6.0166 -1.9816 -4.4484 -0.9513 0.1801 6.4856 3.9375 1.0757 3.0316 0.2017 0.2091 5.7197 1.4778
-#> 319: 93.0659 -6.0176 -1.9819 -4.4482 -0.9511 0.1800 6.5263 3.9425 1.0768 3.0313 0.2018 0.2088 5.7218 1.4772
-#> 320: 93.0607 -6.0165 -1.9822 -4.4484 -0.9510 0.1798 6.5554 3.9372 1.0777 3.0329 0.2019 0.2087 5.7236 1.4771
-#> 321: 93.0551 -6.0145 -1.9825 -4.4487 -0.9509 0.1797 6.5844 3.9275 1.0787 3.0368 0.2021 0.2085 5.7256 1.4766
-#> 322: 93.0531 -6.0130 -1.9827 -4.4491 -0.9507 0.1797 6.6073 3.9201 1.0797 3.0400 0.2021 0.2082 5.7250 1.4759
-#> 323: 93.0477 -6.0123 -1.9828 -4.4493 -0.9506 0.1794 6.6255 3.9149 1.0804 3.0420 0.2021 0.2080 5.7249 1.4756
-#> 324: 93.0425 -6.0107 -1.9829 -4.4498 -0.9504 0.1792 6.6282 3.9060 1.0813 3.0457 0.2022 0.2078 5.7250 1.4754
-#> 325: 93.0389 -6.0090 -1.9830 -4.4504 -0.9503 0.1792 6.6252 3.8965 1.0819 3.0496 0.2022 0.2077 5.7246 1.4749
-#> 326: 93.0411 -6.0093 -1.9832 -4.4509 -0.9503 0.1795 6.6358 3.8976 1.0827 3.0516 0.2022 0.2076 5.7248 1.4738
-#> 327: 93.0418 -6.0095 -1.9834 -4.4514 -0.9503 0.1797 6.6415 3.8962 1.0834 3.0533 0.2022 0.2075 5.7237 1.4737
-#> 328: 93.0434 -6.0093 -1.9835 -4.4520 -0.9503 0.1798 6.6621 3.8957 1.0841 3.0550 0.2022 0.2074 5.7247 1.4731
-#> 329: 93.0446 -6.0109 -1.9836 -4.4522 -0.9503 0.1798 6.6763 3.9048 1.0847 3.0543 0.2022 0.2072 5.7259 1.4725
-#> 330: 93.0451 -6.0133 -1.9838 -4.4518 -0.9503 0.1799 6.6859 3.9192 1.0852 3.0521 0.2022 0.2070 5.7252 1.4719
-#> 331: 93.0456 -6.0136 -1.9838 -4.4516 -0.9503 0.1799 6.6773 3.9217 1.0858 3.0505 0.2022 0.2067 5.7250 1.4715
-#> 332: 93.0463 -6.0133 -1.9839 -4.4515 -0.9504 0.1799 6.6560 3.9195 1.0863 3.0494 0.2022 0.2063 5.7255 1.4710
-#> 333: 93.0496 -6.0122 -1.9839 -4.4513 -0.9505 0.1800 6.6484 3.9134 1.0869 3.0474 0.2022 0.2060 5.7253 1.4705
-#> 334: 93.0520 -6.0105 -1.9838 -4.4513 -0.9505 0.1801 6.6314 3.9035 1.0877 3.0462 0.2022 0.2056 5.7259 1.4702
-#> 335: 93.0550 -6.0088 -1.9836 -4.4510 -0.9507 0.1800 6.6194 3.8941 1.0887 3.0451 0.2022 0.2051 5.7263 1.4702
-#> 336: 93.0554 -6.0081 -1.9834 -4.4509 -0.9508 0.1800 6.6100 3.8896 1.0896 3.0444 0.2022 0.2048 5.7266 1.4705
-#> 337: 93.0582 -6.0067 -1.9832 -4.4507 -0.9509 0.1800 6.6089 3.8805 1.0904 3.0445 0.2021 0.2044 5.7260 1.4706
-#> 338: 93.0631 -6.0073 -1.9831 -4.4507 -0.9511 0.1801 6.5993 3.8798 1.0908 3.0443 0.2021 0.2040 5.7250 1.4711
-#> 339: 93.0689 -6.0071 -1.9831 -4.4508 -0.9513 0.1803 6.5976 3.8749 1.0911 3.0442 0.2021 0.2037 5.7240 1.4714
-#> 340: 93.0694 -6.0085 -1.9831 -4.4507 -0.9516 0.1804 6.5915 3.8779 1.0914 3.0436 0.2022 0.2032 5.7227 1.4711
-#> 341: 93.0709 -6.0097 -1.9830 -4.4508 -0.9518 0.1804 6.5862 3.8803 1.0915 3.0429 0.2023 0.2026 5.7213 1.4715
-#> 342: 93.0741 -6.0104 -1.9829 -4.4507 -0.9521 0.1804 6.5894 3.8812 1.0918 3.0417 0.2024 0.2022 5.7204 1.4714
-#> 343: 93.0781 -6.0122 -1.9829 -4.4505 -0.9523 0.1804 6.5907 3.8870 1.0921 3.0410 0.2024 0.2016 5.7202 1.4712
-#> 344: 93.0818 -6.0134 -1.9829 -4.4503 -0.9525 0.1804 6.5908 3.8895 1.0926 3.0400 0.2025 0.2011 5.7182 1.4712
-#> 345: 93.0850 -6.0148 -1.9829 -4.4500 -0.9528 0.1806 6.5984 3.8931 1.0926 3.0387 0.2026 0.2006 5.7169 1.4712
-#> 346: 93.0849 -6.0155 -1.9831 -4.4502 -0.9529 0.1807 6.6079 3.8986 1.0931 3.0401 0.2028 0.2002 5.7172 1.4716
-#> 347: 93.0859 -6.0161 -1.9832 -4.4503 -0.9530 0.1809 6.6307 3.9028 1.0941 3.0404 0.2029 0.1998 5.7170 1.4712
-#> 348: 93.0885 -6.0173 -1.9833 -4.4503 -0.9532 0.1809 6.6470 3.9096 1.0951 3.0404 0.2030 0.1993 5.7174 1.4708
-#> 349: 93.0894 -6.0189 -1.9835 -4.4503 -0.9534 0.1810 6.6443 3.9190 1.0955 3.0410 0.2031 0.1989 5.7175 1.4707
-#> 350: 93.0924 -6.0196 -1.9836 -4.4502 -0.9535 0.1813 6.6543 3.9218 1.0957 3.0409 0.2032 0.1983 5.7182 1.4705
-#> 351: 93.0938 -6.0203 -1.9838 -4.4503 -0.9536 0.1814 6.6630 3.9233 1.0963 3.0417 0.2032 0.1977 5.7189 1.4703
-#> 352: 93.0946 -6.0210 -1.9838 -4.4505 -0.9537 0.1816 6.6698 3.9263 1.0968 3.0432 0.2033 0.1973 5.7196 1.4701
-#> 353: 93.0969 -6.0214 -1.9839 -4.4505 -0.9538 0.1818 6.6837 3.9270 1.0973 3.0442 0.2034 0.1968 5.7199 1.4701
-#> 354: 93.1014 -6.0199 -1.9839 -4.4504 -0.9539 0.1817 6.7040 3.9204 1.0978 3.0438 0.2034 0.1962 5.7191 1.4703
-#> 355: 93.1035 -6.0197 -1.9838 -4.4502 -0.9539 0.1816 6.7119 3.9222 1.0983 3.0433 0.2034 0.1957 5.7194 1.4706
-#> 356: 93.1055 -6.0198 -1.9839 -4.4496 -0.9539 0.1815 6.7302 3.9277 1.0989 3.0409 0.2035 0.1952 5.7206 1.4707
-#> 357: 93.1080 -6.0188 -1.9837 -4.4490 -0.9540 0.1813 6.7558 3.9243 1.0997 3.0386 0.2035 0.1948 5.7217 1.4706
-#> 358: 93.1111 -6.0182 -1.9835 -4.4484 -0.9541 0.1812 6.7733 3.9204 1.1005 3.0365 0.2035 0.1944 5.7209 1.4700
-#> 359: 93.1148 -6.0175 -1.9834 -4.4481 -0.9542 0.1811 6.7997 3.9151 1.1012 3.0355 0.2035 0.1940 5.7191 1.4696
-#> 360: 93.1157 -6.0176 -1.9832 -4.4478 -0.9543 0.1810 6.8133 3.9155 1.1017 3.0340 0.2035 0.1937 5.7158 1.4691
-#> 361: 93.1169 -6.0185 -1.9830 -4.4476 -0.9544 0.1808 6.8098 3.9232 1.1022 3.0328 0.2035 0.1934 5.7143 1.4690
-#> 362: 93.1173 -6.0205 -1.9829 -4.4472 -0.9545 0.1805 6.8125 3.9361 1.1024 3.0319 0.2035 0.1931 5.7137 1.4693
-#> 363: 93.1162 -6.0230 -1.9828 -4.4467 -0.9545 0.1801 6.8240 3.9524 1.1025 3.0312 0.2035 0.1928 5.7125 1.4695
-#> 364: 93.1173 -6.0240 -1.9826 -4.4464 -0.9546 0.1799 6.8341 3.9575 1.1027 3.0307 0.2035 0.1924 5.7092 1.4695
-#> 365: 93.1199 -6.0259 -1.9824 -4.4462 -0.9547 0.1796 6.8476 3.9687 1.1028 3.0316 0.2036 0.1920 5.7073 1.4695
-#> 366: 93.1220 -6.0277 -1.9821 -4.4461 -0.9548 0.1793 6.8542 3.9777 1.1032 3.0319 0.2037 0.1916 5.7060 1.4694
-#> 367: 93.1230 -6.0287 -1.9819 -4.4460 -0.9548 0.1791 6.8633 3.9829 1.1038 3.0331 0.2038 0.1914 5.7056 1.4693
-#> 368: 93.1255 -6.0276 -1.9816 -4.4459 -0.9549 0.1789 6.8734 3.9764 1.1038 3.0341 0.2038 0.1912 5.7050 1.4695
-#> 369: 93.1258 -6.0263 -1.9814 -4.4461 -0.9549 0.1787 6.8756 3.9698 1.1039 3.0357 0.2039 0.1910 5.7031 1.4697
-#> 370: 93.1288 -6.0252 -1.9811 -4.4463 -0.9548 0.1785 6.8892 3.9639 1.1039 3.0375 0.2040 0.1909 5.7029 1.4701
-#> 371: 93.1317 -6.0245 -1.9810 -4.4467 -0.9548 0.1784 6.8974 3.9601 1.1037 3.0391 0.2040 0.1907 5.7037 1.4700
-#> 372: 93.1346 -6.0233 -1.9811 -4.4465 -0.9548 0.1781 6.9042 3.9536 1.1035 3.0386 0.2040 0.1905 5.7038 1.4700
-#> 373: 93.1340 -6.0234 -1.9810 -4.4461 -0.9547 0.1778 6.9034 3.9548 1.1034 3.0371 0.2039 0.1903 5.7040 1.4698
-#> 374: 93.1324 -6.0230 -1.9811 -4.4456 -0.9547 0.1775 6.9080 3.9527 1.1034 3.0349 0.2038 0.1901 5.7055 1.4691
-#> 375: 93.1309 -6.0226 -1.9812 -4.4451 -0.9546 0.1773 6.9093 3.9493 1.1034 3.0334 0.2037 0.1899 5.7063 1.4683
-#> 376: 93.1298 -6.0215 -1.9811 -4.4447 -0.9546 0.1770 6.9039 3.9432 1.1035 3.0319 0.2036 0.1897 5.7064 1.4678
-#> 377: 93.1296 -6.0209 -1.9811 -4.4443 -0.9546 0.1768 6.8932 3.9390 1.1036 3.0305 0.2035 0.1895 5.7056 1.4672
-#> 378: 93.1292 -6.0200 -1.9810 -4.4438 -0.9545 0.1764 6.8850 3.9349 1.1037 3.0288 0.2034 0.1892 5.7068 1.4667
-#> 379: 93.1284 -6.0196 -1.9808 -4.4432 -0.9544 0.1760 6.8766 3.9318 1.1038 3.0266 0.2033 0.1890 5.7072 1.4665
-#> 380: 93.1304 -6.0182 -1.9806 -4.4425 -0.9543 0.1756 6.8737 3.9249 1.1040 3.0236 0.2033 0.1888 5.7074 1.4662
-#> 381: 93.1315 -6.0169 -1.9804 -4.4417 -0.9542 0.1754 6.8707 3.9193 1.1040 3.0210 0.2032 0.1886 5.7066 1.4661
-#> 382: 93.1331 -6.0160 -1.9801 -4.4409 -0.9542 0.1750 6.8645 3.9150 1.1040 3.0187 0.2032 0.1885 5.7063 1.4664
-#> 383: 93.1334 -6.0153 -1.9800 -4.4403 -0.9542 0.1746 6.8599 3.9123 1.1037 3.0167 0.2032 0.1882 5.7074 1.4665
-#> 384: 93.1328 -6.0140 -1.9801 -4.4397 -0.9540 0.1742 6.8600 3.9074 1.1034 3.0149 0.2031 0.1879 5.7072 1.4667
-#> 385: 93.1306 -6.0137 -1.9801 -4.4392 -0.9539 0.1739 6.8449 3.9073 1.1031 3.0137 0.2030 0.1876 5.7084 1.4665
-#> 386: 93.1281 -6.0134 -1.9801 -4.4388 -0.9539 0.1735 6.8356 3.9088 1.1028 3.0123 0.2029 0.1872 5.7087 1.4667
-#> 387: 93.1267 -6.0141 -1.9801 -4.4384 -0.9537 0.1732 6.8364 3.9150 1.1025 3.0110 0.2028 0.1869 5.7101 1.4669
-#> 388: 93.1252 -6.0142 -1.9801 -4.4380 -0.9536 0.1730 6.8374 3.9192 1.1022 3.0097 0.2028 0.1866 5.7110 1.4670
-#> 389: 93.1223 -6.0140 -1.9801 -4.4375 -0.9535 0.1728 6.8334 3.9209 1.1019 3.0083 0.2028 0.1862 5.7105 1.4674
-#> 390: 93.1221 -6.0144 -1.9800 -4.4371 -0.9534 0.1726 6.8248 3.9256 1.1014 3.0068 0.2028 0.1859 5.7098 1.4675
-#> 391: 93.1210 -6.0149 -1.9799 -4.4365 -0.9533 0.1725 6.8339 3.9293 1.1011 3.0054 0.2028 0.1856 5.7109 1.4678
-#> 392: 93.1193 -6.0145 -1.9799 -4.4360 -0.9532 0.1724 6.8360 3.9279 1.1009 3.0040 0.2028 0.1852 5.7107 1.4678
-#> 393: 93.1200 -6.0149 -1.9799 -4.4357 -0.9532 0.1723 6.8461 3.9287 1.1005 3.0019 0.2028 0.1849 5.7100 1.4678
-#> 394: 93.1202 -6.0138 -1.9799 -4.4355 -0.9532 0.1723 6.8520 3.9229 1.1006 3.0003 0.2028 0.1846 5.7085 1.4679
-#> 395: 93.1203 -6.0134 -1.9800 -4.4354 -0.9532 0.1723 6.8583 3.9200 1.1005 2.9987 0.2027 0.1844 5.7072 1.4680
-#> 396: 93.1195 -6.0131 -1.9800 -4.4353 -0.9532 0.1724 6.8593 3.9169 1.1004 2.9969 0.2027 0.1842 5.7062 1.4676
-#> 397: 93.1195 -6.0130 -1.9801 -4.4352 -0.9532 0.1724 6.8591 3.9143 1.1004 2.9958 0.2027 0.1839 5.7046 1.4675
-#> 398: 93.1200 -6.0128 -1.9801 -4.4352 -0.9532 0.1725 6.8522 3.9125 1.1004 2.9945 0.2028 0.1836 5.7032 1.4675
-#> 399: 93.1200 -6.0135 -1.9803 -4.4351 -0.9531 0.1726 6.8471 3.9166 1.1003 2.9933 0.2028 0.1833 5.7032 1.4673
-#> 400: 93.1204 -6.0139 -1.9803 -4.4351 -0.9531 0.1727 6.8438 3.9191 1.1003 2.9918 0.2027 0.1832 5.7026 1.4671
-#> 401: 93.1198 -6.0139 -1.9804 -4.4351 -0.9530 0.1728 6.8373 3.9186 1.1004 2.9901 0.2027 0.1831 5.7015 1.4670
-#> 402: 93.1199 -6.0141 -1.9804 -4.4351 -0.9530 0.1729 6.8357 3.9194 1.1005 2.9882 0.2027 0.1830 5.7003 1.4671
-#> 403: 93.1196 -6.0155 -1.9804 -4.4350 -0.9530 0.1730 6.8285 3.9255 1.1007 2.9863 0.2026 0.1829 5.7001 1.4671
-#> 404: 93.1183 -6.0164 -1.9805 -4.4350 -0.9531 0.1732 6.8204 3.9308 1.1009 2.9843 0.2026 0.1829 5.7008 1.4670
-#> 405: 93.1178 -6.0161 -1.9805 -4.4350 -0.9532 0.1733 6.8205 3.9286 1.1012 2.9823 0.2025 0.1829 5.7013 1.4669
-#> 406: 93.1176 -6.0171 -1.9806 -4.4348 -0.9533 0.1735 6.8253 3.9319 1.1013 2.9801 0.2025 0.1828 5.7026 1.4666
-#> 407: 93.1168 -6.0185 -1.9807 -4.4348 -0.9533 0.1736 6.8290 3.9373 1.1015 2.9788 0.2024 0.1830 5.7033 1.4664
-#> 408: 93.1165 -6.0198 -1.9808 -4.4349 -0.9534 0.1738 6.8217 3.9428 1.1017 2.9773 0.2023 0.1830 5.7047 1.4663
-#> 409: 93.1165 -6.0210 -1.9809 -4.4350 -0.9534 0.1741 6.8208 3.9505 1.1019 2.9761 0.2021 0.1830 5.7055 1.4661
-#> 410: 93.1169 -6.0230 -1.9810 -4.4351 -0.9535 0.1745 6.8239 3.9617 1.1020 2.9751 0.2020 0.1829 5.7052 1.4658
-#> 411: 93.1166 -6.0237 -1.9811 -4.4353 -0.9536 0.1748 6.8234 3.9664 1.1020 2.9741 0.2019 0.1829 5.7043 1.4657
-#> 412: 93.1164 -6.0235 -1.9812 -4.4355 -0.9536 0.1751 6.8205 3.9643 1.1020 2.9735 0.2017 0.1827 5.7053 1.4654
-#> 413: 93.1182 -6.0232 -1.9814 -4.4356 -0.9537 0.1755 6.8133 3.9615 1.1020 2.9726 0.2016 0.1825 5.7070 1.4650
-#> 414: 93.1190 -6.0226 -1.9815 -4.4360 -0.9537 0.1760 6.8113 3.9578 1.1021 2.9726 0.2015 0.1825 5.7081 1.4648
-#> 415: 93.1183 -6.0226 -1.9817 -4.4364 -0.9538 0.1765 6.8081 3.9557 1.1021 2.9725 0.2014 0.1824 5.7085 1.4646
-#> 416: 93.1185 -6.0238 -1.9818 -4.4369 -0.9538 0.1768 6.8134 3.9617 1.1020 2.9734 0.2013 0.1822 5.7103 1.4645
-#> 417: 93.1190 -6.0245 -1.9819 -4.4373 -0.9540 0.1770 6.8164 3.9664 1.1022 2.9743 0.2012 0.1819 5.7102 1.4650
-#> 418: 93.1219 -6.0256 -1.9818 -4.4376 -0.9542 0.1773 6.8206 3.9710 1.1026 2.9745 0.2011 0.1816 5.7110 1.4655
-#> 419: 93.1255 -6.0261 -1.9817 -4.4381 -0.9543 0.1776 6.8183 3.9714 1.1030 2.9759 0.2010 0.1814 5.7134 1.4659
-#> 420: 93.1294 -6.0262 -1.9816 -4.4385 -0.9546 0.1779 6.8113 3.9704 1.1033 2.9768 0.2009 0.1810 5.7156 1.4666
-#> 421: 93.1319 -6.0259 -1.9815 -4.4392 -0.9547 0.1781 6.7989 3.9685 1.1036 2.9786 0.2008 0.1808 5.7171 1.4676
-#> 422: 93.1338 -6.0263 -1.9814 -4.4398 -0.9548 0.1783 6.7922 3.9681 1.1038 2.9806 0.2006 0.1808 5.7179 1.4681
-#> 423: 93.1353 -6.0266 -1.9813 -4.4406 -0.9550 0.1786 6.7868 3.9674 1.1040 2.9837 0.2006 0.1808 5.7181 1.4687
-#> 424: 93.1374 -6.0270 -1.9811 -4.4414 -0.9550 0.1787 6.7758 3.9674 1.1043 2.9866 0.2004 0.1807 5.7198 1.4693
-#> 425: 93.1383 -6.0270 -1.9811 -4.4420 -0.9551 0.1787 6.7547 3.9674 1.1042 2.9887 0.2003 0.1806 5.7211 1.4702
-#> 426: 93.1400 -6.0268 -1.9811 -4.4427 -0.9551 0.1789 6.7376 3.9654 1.1043 2.9917 0.2002 0.1805 5.7241 1.4706
-#> 427: 93.1391 -6.0268 -1.9811 -4.4433 -0.9552 0.1790 6.7196 3.9634 1.1045 2.9951 0.2001 0.1805 5.7271 1.4710
-#> 428: 93.1404 -6.0268 -1.9810 -4.4442 -0.9552 0.1792 6.7104 3.9628 1.1044 2.9999 0.2000 0.1803 5.7282 1.4712
-#> 429: 93.1431 -6.0265 -1.9810 -4.4450 -0.9553 0.1793 6.7029 3.9612 1.1045 3.0043 0.1999 0.1803 5.7293 1.4716
-#> 430: 93.1464 -6.0263 -1.9809 -4.4457 -0.9554 0.1795 6.6962 3.9606 1.1046 3.0074 0.1999 0.1802 5.7291 1.4724
-#> 431: 93.1485 -6.0267 -1.9809 -4.4460 -0.9555 0.1797 6.6865 3.9623 1.1046 3.0082 0.1998 0.1802 5.7287 1.4726
-#> 432: 93.1509 -6.0277 -1.9808 -4.4462 -0.9556 0.1798 6.6843 3.9658 1.1047 3.0086 0.1998 0.1801 5.7280 1.4727
-#> 433: 93.1528 -6.0289 -1.9806 -4.4464 -0.9557 0.1798 6.6840 3.9714 1.1049 3.0087 0.1998 0.1801 5.7282 1.4729
-#> 434: 93.1555 -6.0286 -1.9804 -4.4467 -0.9557 0.1798 6.6870 3.9693 1.1052 3.0094 0.1997 0.1800 5.7277 1.4729
-#> 435: 93.1574 -6.0290 -1.9803 -4.4467 -0.9558 0.1798 6.6893 3.9712 1.1055 3.0095 0.1996 0.1800 5.7278 1.4727
-#> 436: 93.1594 -6.0299 -1.9802 -4.4468 -0.9558 0.1798 6.6934 3.9749 1.1059 3.0103 0.1996 0.1801 5.7271 1.4727
-#> 437: 93.1600 -6.0311 -1.9800 -4.4469 -0.9558 0.1797 6.7010 3.9812 1.1065 3.0110 0.1996 0.1801 5.7275 1.4727
-#> 438: 93.1617 -6.0318 -1.9799 -4.4471 -0.9559 0.1796 6.7120 3.9865 1.1069 3.0121 0.1995 0.1801 5.7271 1.4727
-#> 439: 93.1634 -6.0329 -1.9798 -4.4472 -0.9559 0.1795 6.7279 3.9930 1.1075 3.0127 0.1995 0.1802 5.7268 1.4727
-#> 440: 93.1644 -6.0332 -1.9797 -4.4473 -0.9559 0.1794 6.7338 3.9962 1.1080 3.0136 0.1994 0.1803 5.7270 1.4726
-#> 441: 93.1654 -6.0335 -1.9795 -4.4477 -0.9558 0.1794 6.7435 3.9988 1.1085 3.0155 0.1994 0.1805 5.7274 1.4728
-#> 442: 93.1670 -6.0340 -1.9792 -4.4480 -0.9558 0.1794 6.7493 4.0028 1.1091 3.0173 0.1993 0.1808 5.7282 1.4729
-#> 443: 93.1685 -6.0346 -1.9790 -4.4485 -0.9558 0.1793 6.7577 4.0073 1.1092 3.0202 0.1992 0.1811 5.7267 1.4732
-#> 444: 93.1671 -6.0346 -1.9789 -4.4491 -0.9558 0.1792 6.7559 4.0069 1.1093 3.0238 0.1992 0.1813 5.7258 1.4733
-#> 445: 93.1655 -6.0355 -1.9789 -4.4497 -0.9557 0.1790 6.7552 4.0127 1.1094 3.0276 0.1992 0.1814 5.7262 1.4733
-#> 446: 93.1641 -6.0361 -1.9787 -4.4501 -0.9557 0.1789 6.7579 4.0169 1.1096 3.0306 0.1991 0.1816 5.7262 1.4732
-#> 447: 93.1628 -6.0363 -1.9786 -4.4503 -0.9556 0.1787 6.7680 4.0196 1.1099 3.0318 0.1991 0.1818 5.7258 1.4729
-#> 448: 93.1629 -6.0371 -1.9787 -4.4509 -0.9556 0.1786 6.7705 4.0248 1.1100 3.0358 0.1990 0.1820 5.7267 1.4725
-#> 449: 93.1626 -6.0381 -1.9785 -4.4510 -0.9556 0.1784 6.7800 4.0298 1.1101 3.0368 0.1989 0.1822 5.7266 1.4722
-#> 450: 93.1614 -6.0386 -1.9782 -4.4514 -0.9556 0.1782 6.7796 4.0316 1.1103 3.0392 0.1989 0.1824 5.7260 1.4720
-#> 451: 93.1603 -6.0397 -1.9779 -4.4518 -0.9556 0.1780 6.7799 4.0381 1.1107 3.0416 0.1988 0.1827 5.7264 1.4720
-#> 452: 93.1610 -6.0406 -1.9775 -4.4522 -0.9556 0.1777 6.7813 4.0424 1.1111 3.0443 0.1988 0.1828 5.7268 1.4719
-#> 453: 93.1618 -6.0414 -1.9771 -4.4523 -0.9556 0.1774 6.7814 4.0490 1.1115 3.0456 0.1987 0.1830 5.7262 1.4721
-#> 454: 93.1625 -6.0415 -1.9767 -4.4525 -0.9555 0.1771 6.7799 4.0499 1.1118 3.0473 0.1986 0.1831 5.7260 1.4723
-#> 455: 93.1636 -6.0412 -1.9765 -4.4528 -0.9555 0.1769 6.7778 4.0489 1.1123 3.0496 0.1985 0.1832 5.7268 1.4722
-#> 456: 93.1653 -6.0401 -1.9762 -4.4532 -0.9554 0.1768 6.7703 4.0441 1.1127 3.0517 0.1983 0.1834 5.7282 1.4725
-#> 457: 93.1672 -6.0396 -1.9760 -4.4535 -0.9554 0.1766 6.7683 4.0427 1.1129 3.0539 0.1982 0.1835 5.7281 1.4727
-#> 458: 93.1692 -6.0398 -1.9757 -4.4539 -0.9554 0.1765 6.7627 4.0450 1.1132 3.0570 0.1981 0.1835 5.7294 1.4729
-#> 459: 93.1708 -6.0402 -1.9756 -4.4542 -0.9554 0.1763 6.7615 4.0483 1.1133 3.0596 0.1980 0.1836 5.7320 1.4728
-#> 460: 93.1710 -6.0401 -1.9755 -4.4544 -0.9553 0.1762 6.7629 4.0487 1.1135 3.0615 0.1979 0.1835 5.7323 1.4730
-#> 461: 93.1708 -6.0403 -1.9755 -4.4546 -0.9552 0.1762 6.7639 4.0492 1.1136 3.0631 0.1978 0.1834 5.7321 1.4729
-#> 462: 93.1707 -6.0405 -1.9755 -4.4548 -0.9552 0.1760 6.7657 4.0506 1.1136 3.0647 0.1977 0.1833 5.7323 1.4727
-#> 463: 93.1690 -6.0403 -1.9755 -4.4548 -0.9551 0.1759 6.7607 4.0494 1.1136 3.0651 0.1976 0.1832 5.7332 1.4726
-#> 464: 93.1673 -6.0400 -1.9755 -4.4548 -0.9551 0.1758 6.7588 4.0480 1.1138 3.0652 0.1975 0.1832 5.7344 1.4724
-#> 465: 93.1657 -6.0399 -1.9755 -4.4548 -0.9550 0.1756 6.7601 4.0474 1.1138 3.0652 0.1974 0.1831 5.7350 1.4724
-#> 466: 93.1656 -6.0406 -1.9754 -4.4548 -0.9549 0.1755 6.7589 4.0514 1.1139 3.0658 0.1973 0.1831 5.7355 1.4723
-#> 467: 93.1657 -6.0408 -1.9753 -4.4548 -0.9549 0.1754 6.7558 4.0525 1.1139 3.0664 0.1972 0.1831 5.7358 1.4725
-#> 468: 93.1664 -6.0411 -1.9752 -4.4551 -0.9548 0.1753 6.7546 4.0551 1.1140 3.0679 0.1971 0.1832 5.7358 1.4723
-#> 469: 93.1667 -6.0412 -1.9751 -4.4552 -0.9547 0.1752 6.7547 4.0554 1.1141 3.0676 0.1970 0.1833 5.7354 1.4721
-#> 470: 93.1664 -6.0413 -1.9750 -4.4552 -0.9546 0.1751 6.7579 4.0564 1.1143 3.0676 0.1969 0.1833 5.7352 1.4718
-#> 471: 93.1656 -6.0411 -1.9750 -4.4553 -0.9545 0.1750 6.7611 4.0555 1.1142 3.0681 0.1968 0.1834 5.7354 1.4715
-#> 472: 93.1644 -6.0408 -1.9751 -4.4554 -0.9544 0.1749 6.7577 4.0542 1.1142 3.0686 0.1968 0.1834 5.7362 1.4712
-#> 473: 93.1632 -6.0405 -1.9751 -4.4554 -0.9543 0.1749 6.7527 4.0526 1.1141 3.0686 0.1967 0.1835 5.7363 1.4708
-#> 474: 93.1619 -6.0405 -1.9752 -4.4555 -0.9542 0.1748 6.7479 4.0521 1.1140 3.0689 0.1967 0.1835 5.7366 1.4705
-#> 475: 93.1609 -6.0413 -1.9753 -4.4557 -0.9542 0.1748 6.7469 4.0558 1.1139 3.0698 0.1967 0.1835 5.7379 1.4702
-#> 476: 93.1607 -6.0411 -1.9754 -4.4556 -0.9542 0.1747 6.7414 4.0549 1.1139 3.0697 0.1966 0.1835 5.7388 1.4698
-#> 477: 93.1597 -6.0413 -1.9754 -4.4560 -0.9542 0.1747 6.7321 4.0560 1.1137 3.0733 0.1966 0.1836 5.7392 1.4697
-#> 478: 93.1591 -6.0421 -1.9754 -4.4563 -0.9542 0.1745 6.7239 4.0608 1.1137 3.0765 0.1965 0.1836 5.7399 1.4697
-#> 479: 93.1589 -6.0438 -1.9754 -4.4564 -0.9542 0.1744 6.7150 4.0719 1.1136 3.0785 0.1964 0.1838 5.7421 1.4695
-#> 480: 93.1594 -6.0459 -1.9754 -4.4566 -0.9542 0.1742 6.7102 4.0895 1.1135 3.0807 0.1964 0.1839 5.7446 1.4695
-#> 481: 93.1604 -6.0472 -1.9754 -4.4570 -0.9542 0.1741 6.7104 4.1016 1.1135 3.0848 0.1964 0.1841 5.7456 1.4693
-#> 482: 93.1584 -6.0486 -1.9754 -4.4573 -0.9542 0.1739 6.7061 4.1152 1.1136 3.0877 0.1964 0.1842 5.7464 1.4690
-#> 483: 93.1561 -6.0501 -1.9754 -4.4576 -0.9541 0.1737 6.7067 4.1286 1.1135 3.0903 0.1963 0.1843 5.7475 1.4688
-#> 484: 93.1545 -6.0507 -1.9754 -4.4578 -0.9541 0.1737 6.7113 4.1362 1.1134 3.0918 0.1963 0.1845 5.7488 1.4687
-#> 485: 93.1524 -6.0507 -1.9754 -4.4583 -0.9540 0.1736 6.7094 4.1381 1.1134 3.0970 0.1964 0.1847 5.7496 1.4685
-#> 486: 93.1510 -6.0508 -1.9754 -4.4586 -0.9540 0.1735 6.7118 4.1405 1.1134 3.0996 0.1964 0.1847 5.7502 1.4682
-#> 487: 93.1495 -6.0507 -1.9755 -4.4591 -0.9539 0.1734 6.7128 4.1406 1.1134 3.1037 0.1965 0.1848 5.7510 1.4680
-#> 488: 93.1494 -6.0502 -1.9756 -4.4597 -0.9538 0.1734 6.7171 4.1384 1.1135 3.1081 0.1965 0.1848 5.7508 1.4677
-#> 489: 93.1497 -6.0497 -1.9756 -4.4604 -0.9538 0.1734 6.7188 4.1358 1.1135 3.1133 0.1966 0.1847 5.7499 1.4675
-#> 490: 93.1507 -6.0486 -1.9757 -4.4607 -0.9538 0.1735 6.7206 4.1319 1.1136 3.1157 0.1967 0.1847 5.7498 1.4672
-#> 491: 93.1507 -6.0476 -1.9757 -4.4612 -0.9537 0.1735 6.7141 4.1270 1.1136 3.1187 0.1968 0.1846 5.7503 1.4672
-#> 492: 93.1507 -6.0470 -1.9758 -4.4618 -0.9536 0.1735 6.7140 4.1238 1.1139 3.1218 0.1969 0.1846 5.7511 1.4669
-#> 493: 93.1513 -6.0468 -1.9758 -4.4623 -0.9535 0.1736 6.7214 4.1232 1.1141 3.1246 0.1970 0.1845 5.7514 1.4668
-#> 494: 93.1511 -6.0467 -1.9759 -4.4629 -0.9534 0.1737 6.7332 4.1232 1.1144 3.1278 0.1971 0.1845 5.7512 1.4664
-#> 495: 93.1511 -6.0464 -1.9761 -4.4635 -0.9533 0.1738 6.7377 4.1218 1.1145 3.1309 0.1972 0.1845 5.7515 1.4661
-#> 496: 93.1498 -6.0465 -1.9762 -4.4639 -0.9532 0.1739 6.7412 4.1241 1.1147 3.1325 0.1974 0.1845 5.7514 1.4657
-#> 497: 93.1482 -6.0467 -1.9764 -4.4644 -0.9532 0.1741 6.7506 4.1259 1.1149 3.1346 0.1975 0.1846 5.7513 1.4652
-#> 498: 93.1479 -6.0465 -1.9765 -4.4647 -0.9531 0.1743 6.7588 4.1263 1.1150 3.1357 0.1977 0.1846 5.7511 1.4648
-#> 499: 93.1462 -6.0455 -1.9766 -4.4651 -0.9530 0.1745 6.7659 4.1219 1.1152 3.1374 0.1978 0.1847 5.7515 1.4645
-#> 500: 93.1455 -6.0439 -1.9768 -4.4657 -0.9529 0.1747 6.7747 4.1151 1.1154 3.1404 0.1980 0.1848 5.7516 1.4641
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> → generate SAEM model
#> ✔ done
#> 1: 93.0952 -5.6337 -1.8988 -4.1294 -1.2035 0.1038 5.2152 1.6150 1.0450 2.6377 0.5035 0.5225 20.0768 11.4566
+#> 2: 93.1464 -5.6948 -1.8729 -4.2029 -1.1302 0.1295 5.5478 1.5342 0.9927 2.5059 0.4783 0.5147 11.2089 8.1577
+#> 3: 93.1719 -5.7029 -1.8810 -4.2024 -1.0686 0.1063 5.2764 1.5217 0.9431 2.3806 0.4544 0.5587 9.3753 5.7166
+#> 4: 92.8647 -5.8139 -1.8979 -4.1992 -1.0168 0.1122 5.4892 1.7893 0.8960 2.2615 0.4317 0.5307 9.4134 4.7166
+#> 5: 92.7759 -5.8627 -1.8873 -4.1402 -1.0347 0.1243 6.2028 2.1819 0.8795 2.1485 0.4101 0.5042 9.5964 4.7340
+#> 6: 92.8080 -5.8954 -1.9186 -4.1772 -0.9727 0.1311 5.8926 2.0728 0.8633 2.0410 0.3896 0.4790 8.7334 4.1957
+#> 7: 92.9042 -5.9034 -1.9603 -4.1854 -0.9717 0.1630 5.5980 2.2068 0.8672 1.9390 0.3701 0.4550 8.7213 3.3409
+#> 8: 92.9302 -5.8545 -1.9240 -4.2343 -0.9748 0.1686 5.3181 2.3934 0.8239 1.9533 0.3516 0.4323 7.6950 2.9174
+#> 9: 92.9518 -5.5561 -1.9734 -4.1856 -0.9322 0.2129 5.0522 2.2738 0.7830 2.0138 0.3340 0.4689 7.9230 2.1930
+#> 10: 93.0672 -5.5564 -1.9633 -4.1456 -0.9343 0.2049 4.7996 2.1601 0.7438 2.0517 0.3173 0.4771 8.0644 2.0682
+#> 11: 92.6849 -5.6187 -1.9773 -4.1793 -0.9342 0.2290 4.5596 2.0521 0.7123 2.0774 0.3015 0.5052 8.2355 1.9349
+#> 12: 92.6425 -5.6989 -2.0144 -4.1395 -0.9342 0.2669 4.3316 2.2634 0.7142 2.3008 0.2864 0.5728 7.5188 1.8028
+#> 13: 92.2996 -5.6700 -1.9885 -4.0443 -0.9202 0.2750 4.5787 2.1608 0.7019 2.7515 0.2721 0.6641 7.0744 1.8958
+#> 14: 92.2457 -5.5825 -2.0314 -3.9788 -0.9142 0.2908 6.3744 2.0527 0.7018 3.2703 0.2585 0.6387 6.9499 1.8421
+#> 15: 92.1741 -5.5333 -2.0318 -3.9664 -0.9059 0.2894 6.0557 1.9501 0.7179 3.2869 0.2455 0.6068 7.0951 1.6824
+#> 16: 92.5772 -5.4982 -2.0352 -3.9471 -0.9063 0.2930 5.7529 1.8526 0.7244 3.6994 0.2333 0.5764 7.2138 1.7042
+#> 17: 92.7024 -5.4902 -2.0438 -4.0347 -0.9079 0.2959 5.4652 1.7600 0.7393 3.5144 0.2216 0.5765 7.0258 1.6793
+#> 18: 92.0240 -5.5539 -2.0520 -3.9601 -0.9079 0.2884 6.5142 1.9232 0.7320 3.9052 0.2157 0.5521 7.2568 1.6151
+#> 19: 92.6532 -5.6325 -2.0456 -3.9091 -0.9179 0.3047 6.5743 2.3363 0.7405 4.5825 0.2049 0.5425 7.6201 1.6565
+#> 20: 92.3488 -5.6617 -2.0554 -3.9501 -0.9216 0.3056 6.7080 2.7562 0.7218 4.7569 0.2083 0.5432 7.3481 1.8059
+#> 21: 92.5679 -5.7469 -2.0614 -4.0829 -0.8890 0.3158 6.6510 3.1993 0.7136 4.5191 0.1978 0.5281 7.3723 1.7461
+#> 22: 92.4785 -5.9527 -2.0657 -4.0580 -0.8971 0.3084 6.3184 4.1791 0.7144 4.2931 0.1929 0.5157 7.1922 1.6984
+#> 23: 92.5594 -5.8590 -2.0723 -4.0580 -0.9020 0.2952 6.0025 3.9702 0.7335 4.0784 0.1833 0.5129 7.7560 1.6302
+#> 24: 92.6152 -5.9488 -2.0658 -4.1187 -0.9050 0.2997 5.7024 4.5381 0.7215 3.8745 0.1875 0.5129 7.6182 1.6362
+#> 25: 92.4658 -5.8715 -2.0791 -4.0949 -0.8922 0.3074 6.1428 4.3112 0.7353 3.6808 0.1896 0.5157 7.2703 1.5633
+#> 26: 92.2507 -5.9797 -2.0707 -4.0834 -0.8868 0.3266 6.4124 4.7125 0.7334 3.5368 0.1851 0.5217 7.3085 1.5828
+#> 27: 92.7055 -5.9792 -2.0779 -4.2066 -0.8887 0.2993 6.0918 4.8624 0.7659 3.7456 0.1841 0.4956 7.3534 1.5240
+#> 28: 92.3971 -6.0253 -2.0648 -4.1406 -0.9042 0.2897 5.7872 4.7690 0.7449 3.5583 0.1823 0.4709 7.2479 1.5008
+#> 29: 92.4045 -5.9045 -2.0730 -4.1407 -0.8969 0.3103 5.6683 4.5306 0.7349 3.3816 0.1849 0.5054 7.1719 1.6004
+#> 30: 92.1714 -5.8598 -2.0645 -4.0913 -0.8964 0.2743 5.3849 4.3040 0.7538 3.3509 0.1757 0.4801 7.3739 1.5736
+#> 31: 91.9134 -5.7867 -2.0367 -4.0563 -0.8957 0.2280 5.1156 4.0888 0.7299 3.3452 0.1749 0.4673 6.5991 1.5909
+#> 32: 92.3743 -5.9967 -2.0255 -4.0668 -0.9025 0.2247 4.8599 4.6666 0.7256 3.3271 0.1714 0.5008 6.4693 1.5458
+#> 33: 92.5239 -5.9301 -2.0387 -4.0365 -0.9033 0.2558 4.6169 4.4333 0.7492 3.6109 0.1688 0.5424 6.7730 1.5771
+#> 34: 92.6892 -6.1135 -2.0587 -4.0280 -0.8993 0.2430 4.3860 6.0227 0.7798 3.5725 0.1672 0.5153 6.8110 1.5417
+#> 35: 92.7276 -6.0815 -2.0629 -4.0833 -0.8943 0.2375 4.6811 5.7216 0.8010 3.3939 0.1715 0.4895 6.6812 1.5478
+#> 36: 92.7316 -6.0691 -2.0882 -4.0626 -0.9030 0.2405 4.4614 5.4355 0.8355 3.2242 0.1789 0.4650 6.8443 1.4806
+#> 37: 92.6685 -5.7905 -2.0666 -4.0663 -0.8998 0.2784 5.1916 5.1637 0.7937 3.0641 0.1823 0.4418 6.5421 1.6284
+#> 38: 93.0325 -5.6829 -2.0674 -4.0772 -0.9167 0.2499 4.9320 4.9055 0.7768 3.1213 0.1887 0.4290 6.8220 1.5224
+#> 39: 93.0378 -5.5554 -2.0743 -4.0772 -0.9189 0.2361 4.6854 4.6603 0.7822 3.1213 0.1813 0.4242 7.1137 1.5021
+#> 40: 93.3297 -5.6270 -2.0591 -4.1200 -0.9167 0.2035 4.4511 4.4272 0.8128 2.9653 0.1829 0.4030 7.3894 1.5064
+#> 41: 93.3408 -5.5437 -2.0344 -4.1042 -0.9078 0.1744 4.2286 4.2059 0.8228 2.8170 0.1881 0.3829 7.2734 1.5519
+#> 42: 93.1691 -5.4436 -2.0551 -4.1048 -0.8984 0.1732 4.0172 3.9956 0.7816 2.6762 0.1853 0.3637 6.9712 1.5332
+#> 43: 93.2443 -5.5247 -2.0722 -4.0980 -0.8992 0.1756 3.8163 3.7958 0.7781 2.7200 0.1956 0.3455 6.7012 1.5344
+#> 44: 92.9509 -5.5020 -2.0495 -4.0961 -0.8964 0.1777 3.6255 3.6060 0.7555 2.8172 0.1994 0.3283 6.2180 1.6137
+#> 45: 92.8898 -5.4913 -2.0462 -4.1079 -0.9003 0.1701 4.1177 3.4257 0.7491 2.8491 0.1989 0.3372 6.2876 1.6205
+#> 46: 92.6044 -5.6429 -2.0499 -4.1079 -0.9069 0.1999 4.2103 3.2544 0.7657 2.8491 0.1921 0.3532 6.2261 1.6435
+#> 47: 92.7740 -5.6128 -2.0804 -4.1186 -0.8976 0.1864 5.2188 3.0917 0.7381 2.9036 0.2030 0.3391 6.6803 1.6177
+#> 48: 92.4691 -5.6645 -2.0600 -4.1288 -0.8796 0.1913 6.2045 2.9371 0.7774 2.9223 0.1966 0.3396 6.7169 1.6215
+#> 49: 92.4128 -5.7079 -2.0802 -4.1166 -0.8798 0.1741 5.8943 3.1446 0.7854 2.8715 0.1935 0.3369 6.9151 1.4834
+#> 50: 91.8883 -5.7713 -2.0932 -4.0899 -0.8886 0.1758 5.5996 3.5478 0.8033 2.8192 0.2014 0.3201 7.0775 1.4635
+#> 51: 92.1187 -5.7306 -2.0903 -4.0878 -0.8923 0.2024 5.3196 3.6534 0.7823 2.7891 0.1969 0.3140 6.9879 1.5430
+#> 52: 92.3209 -5.7897 -2.0903 -4.1622 -0.9072 0.2261 5.3781 3.4707 0.8001 3.0801 0.2063 0.3088 6.7047 1.4499
+#> 53: 92.4318 -5.6954 -2.0950 -4.1866 -0.9082 0.2131 7.1200 3.2972 0.7711 3.3398 0.2034 0.3186 6.6152 1.5123
+#> 54: 92.5380 -5.6975 -2.0782 -4.2394 -0.8976 0.2118 6.7640 3.1323 0.7744 3.5385 0.2175 0.3296 6.4402 1.5403
+#> 55: 92.7213 -5.6663 -2.0427 -4.3288 -0.9028 0.2032 8.1796 2.9757 0.7748 4.4495 0.2142 0.3316 6.4111 1.5369
+#> 56: 92.7219 -5.6865 -2.0557 -4.3434 -0.9084 0.2021 7.7706 2.8269 0.7989 4.6691 0.2174 0.3433 6.4256 1.4639
+#> 57: 92.8932 -5.5736 -2.0497 -4.3955 -0.9216 0.1694 7.3821 2.6856 0.8205 4.9791 0.2142 0.3500 6.5378 1.5406
+#> 58: 92.9219 -5.5789 -2.0547 -4.3094 -0.9183 0.1838 7.0130 2.5513 0.7958 4.7302 0.2193 0.3495 6.2662 1.4940
+#> 59: 93.0432 -5.6201 -2.0395 -4.2527 -0.9199 0.2302 6.6623 2.4237 0.8241 4.4937 0.2241 0.3321 5.8693 1.6176
+#> 60: 92.9724 -5.5971 -2.0537 -4.3509 -0.9219 0.2118 7.5905 2.3026 0.8418 4.4546 0.2177 0.3155 5.5960 1.5040
+#> 61: 93.1235 -5.6332 -2.0671 -4.3572 -0.9219 0.1917 7.2521 2.3037 0.8527 4.5707 0.2230 0.2997 5.8136 1.4516
+#> 62: 93.5431 -5.6373 -2.0371 -4.3384 -0.9276 0.1997 8.5187 2.3895 0.8575 4.4378 0.2258 0.3041 5.5746 1.4572
+#> 63: 93.5009 -5.5634 -2.0224 -4.3560 -0.9339 0.2167 8.0927 2.2700 0.8462 4.4449 0.2266 0.3162 5.4922 1.5233
+#> 64: 93.7369 -5.6032 -2.0362 -4.2323 -0.9355 0.2159 9.6684 2.1949 0.8514 4.2227 0.2300 0.3318 5.7597 1.4866
+#> 65: 93.5021 -5.5769 -2.0311 -4.3204 -0.9375 0.1927 9.5537 2.0852 0.8559 4.6151 0.2208 0.3550 5.6975 1.5031
+#> 66: 93.4211 -5.7184 -2.0384 -4.3041 -0.9228 0.2121 9.0760 2.6390 0.8430 4.3843 0.2098 0.3755 5.8990 1.5133
+#> 67: 93.3435 -5.6579 -2.0456 -4.2222 -0.9183 0.1825 8.6222 2.5071 0.8719 4.1651 0.2152 0.3567 5.9004 1.4874
+#> 68: 93.3914 -5.6554 -2.0420 -4.1618 -0.9303 0.1714 8.1911 2.3817 0.8856 3.9569 0.2272 0.3388 6.1793 1.4917
+#> 69: 93.5112 -5.6834 -2.0349 -4.1591 -0.9331 0.1759 8.9900 2.5191 0.9184 3.7590 0.2236 0.3219 6.1618 1.4697
+#> 70: 93.4289 -5.6576 -2.0273 -4.1763 -0.9399 0.1738 8.5405 2.4302 0.8725 3.5711 0.2149 0.3288 6.5324 1.5410
+#> 71: 93.2936 -5.6699 -2.0256 -4.1405 -0.9370 0.1922 8.1134 2.3831 0.8289 3.3925 0.2080 0.3548 5.9794 1.5904
+#> 72: 92.9152 -5.6742 -2.0382 -4.1523 -0.9411 0.1991 7.7078 2.4322 0.7875 3.2916 0.2007 0.3456 6.0999 1.6022
+#> 73: 92.8129 -5.8099 -2.0372 -4.1735 -0.9377 0.1605 8.2752 2.8931 0.7737 3.4015 0.2057 0.3283 6.0140 1.5472
+#> 74: 92.7806 -5.7269 -2.0315 -4.1877 -0.9399 0.1675 8.4688 2.7484 0.7773 3.4620 0.2174 0.3249 5.8495 1.5779
+#> 75: 92.9128 -5.8680 -2.0304 -4.1459 -0.9387 0.1567 8.0454 3.2365 0.7681 3.2935 0.2198 0.3187 5.8539 1.5815
+#> 76: 92.8931 -5.8483 -2.0253 -4.1815 -0.9387 0.1540 9.6800 3.0747 0.8007 3.5838 0.2198 0.3291 5.9005 1.5053
+#> 77: 92.7474 -5.7995 -2.0202 -4.1904 -0.9333 0.1724 10.0488 2.9210 0.7841 3.7255 0.2148 0.3465 5.9418 1.5569
+#> 78: 92.8150 -5.9608 -2.0025 -4.1583 -0.9511 0.1566 9.5464 3.5249 0.7858 3.6988 0.2246 0.3292 5.7737 1.5904
+#> 79: 92.6663 -6.0485 -2.0245 -4.1437 -0.9446 0.1786 9.0690 4.1252 0.7803 3.6526 0.2155 0.3335 5.9109 1.5521
+#> 80: 92.5932 -6.1001 -2.0304 -4.1969 -0.9409 0.1424 8.6156 4.6478 0.8007 4.0379 0.2114 0.3168 6.1732 1.5544
+#> 81: 92.6789 -6.3510 -2.0062 -4.2272 -0.9541 0.1360 8.3363 5.9861 0.7719 3.8800 0.2202 0.3010 5.6841 1.6317
+#> 82: 92.9996 -6.5680 -2.0048 -4.1609 -0.9578 0.1367 10.6901 7.4391 0.7962 3.6860 0.2092 0.2859 5.7335 1.6391
+#> 83: 93.1087 -6.5298 -1.9757 -4.1694 -0.9596 0.1323 10.5524 7.4660 0.8237 3.8009 0.2134 0.2716 5.9664 1.6316
+#> 84: 93.1929 -6.5844 -2.0191 -4.2021 -0.9616 0.1384 10.0248 7.7313 0.8230 3.6109 0.2110 0.2580 5.7854 1.5609
+#> 85: 92.9161 -6.4934 -2.0281 -4.2008 -0.9600 0.1107 9.5236 7.4269 0.8448 3.5630 0.2110 0.2451 5.6111 1.5333
+#> 86: 92.9816 -6.5397 -2.0234 -4.1830 -0.9694 0.1111 9.1945 7.4382 0.8481 3.3849 0.2166 0.2329 5.8375 1.5263
+#> 87: 93.0930 -6.5749 -2.0168 -4.1986 -0.9816 0.0926 8.7348 8.4431 0.8646 3.3032 0.2155 0.2212 5.7542 1.5736
+#> 88: 93.0765 -6.4914 -2.0274 -4.2274 -0.9870 0.1148 8.4666 8.0209 0.8666 3.5292 0.2048 0.2102 5.8988 1.5329
+#> 89: 92.8699 -6.6431 -2.0199 -4.2175 -0.9463 0.1011 8.4648 7.7973 0.8908 3.3980 0.1945 0.2102 5.6876 1.5177
+#> 90: 92.8225 -6.6932 -2.0211 -4.2175 -0.9505 0.0887 10.1862 8.7787 0.8730 3.3980 0.1877 0.1997 5.9135 1.4821
+#> 91: 92.7874 -6.7007 -2.0420 -4.2936 -0.9468 0.0927 11.2275 8.3397 0.8600 3.9490 0.1885 0.2147 6.1108 1.4315
+#> 92: 93.2320 -6.8088 -2.0341 -4.2817 -0.9582 0.1270 12.4029 9.6204 0.8503 3.7516 0.1950 0.2070 5.9434 1.5251
+#> 93: 93.8996 -6.5471 -2.0440 -4.2123 -0.9543 0.1140 11.7828 9.1394 0.8493 3.5640 0.1988 0.2017 6.1302 1.5568
+#> 94: 93.4416 -6.4623 -2.0448 -4.2188 -0.9595 0.1174 12.1277 8.6824 0.8568 3.3858 0.1975 0.1938 5.9173 1.5204
+#> 95: 93.2953 -6.1521 -2.0477 -4.2216 -0.9551 0.1152 11.5213 8.2483 0.8356 3.2165 0.1979 0.1855 5.8298 1.5357
+#> 96: 92.9577 -6.0477 -2.0579 -4.2534 -0.9465 0.1284 10.9452 7.8359 0.8202 3.3357 0.1937 0.1917 5.8590 1.5738
+#> 97: 92.8703 -6.1037 -2.0745 -4.1960 -0.9405 0.1417 10.4858 7.4441 0.8488 3.1690 0.1969 0.2016 5.7948 1.4759
+#> 98: 92.9728 -6.3534 -2.0868 -4.2155 -0.9444 0.1069 9.9615 7.1788 0.8736 3.1913 0.1998 0.2114 5.6533 1.4322
+#> 99: 93.4116 -6.1712 -2.0837 -4.2280 -0.9473 0.1197 9.4634 6.8198 0.8959 3.1806 0.1899 0.2167 5.9149 1.3768
+#> 100: 93.2598 -6.1345 -2.0645 -4.2237 -0.9575 0.1099 8.9903 6.4788 0.9204 3.2429 0.1903 0.2058 5.7085 1.4133
+#> 101: 93.3082 -6.1574 -2.0474 -4.2315 -0.9619 0.1161 9.0819 6.1549 0.8744 3.2049 0.1891 0.2278 5.6493 1.4894
+#> 102: 93.5741 -6.2923 -2.0484 -4.2853 -0.9665 0.1325 10.4108 5.8522 0.8804 3.5370 0.2024 0.2324 5.6995 1.4594
+#> 103: 92.9199 -6.1797 -2.0522 -4.2940 -0.9568 0.1289 9.8903 5.5596 0.8722 3.6682 0.1975 0.2398 5.5536 1.4510
+#> 104: 93.1139 -6.1630 -2.0546 -4.2912 -0.9613 0.1115 9.3958 5.2816 0.8648 3.6673 0.2010 0.2278 5.5768 1.4812
+#> 105: 93.4085 -6.0359 -2.0450 -4.2889 -0.9591 0.1258 8.9260 5.0175 0.8412 3.7286 0.1917 0.2171 5.6780 1.5203
+#> 106: 93.3103 -6.1029 -2.0425 -4.2948 -0.9579 0.0934 8.4797 4.7667 0.8539 3.6947 0.1947 0.2234 5.7210 1.4760
+#> 107: 93.6389 -5.9750 -2.0309 -4.2630 -0.9660 0.1110 8.0557 4.5283 0.8470 3.5100 0.2044 0.2299 5.6280 1.5525
+#> 108: 93.8641 -5.8551 -2.0360 -4.2311 -0.9629 0.0900 7.6529 4.3019 0.8567 3.3345 0.2014 0.2302 5.7841 1.5978
+#> 109: 93.6274 -6.0268 -2.0445 -4.3047 -0.9488 0.0979 7.2703 4.7807 0.8565 3.7665 0.1929 0.2271 5.7941 1.5580
+#> 110: 93.6320 -5.8321 -2.0413 -4.2855 -0.9477 0.1143 6.9068 4.5417 0.8412 3.6165 0.1901 0.2199 5.8169 1.5477
+#> 111: 93.6245 -5.8256 -2.0157 -4.2797 -0.9612 0.0940 6.5774 4.3146 0.8460 3.5782 0.1837 0.2182 5.6157 1.6424
+#> 112: 93.8512 -5.9045 -2.0116 -4.2409 -0.9708 0.0883 6.2486 4.0989 0.8658 3.5059 0.1761 0.2073 5.8852 1.6073
+#> 113: 93.7080 -5.9935 -2.0306 -4.1884 -0.9690 0.0740 5.9361 4.0088 0.9072 3.3400 0.1957 0.2169 6.3792 1.4770
+#> 114: 93.8574 -5.9185 -2.0233 -4.2030 -0.9588 0.1137 5.6393 3.8084 0.9322 3.2878 0.1939 0.2098 5.8891 1.5325
+#> 115: 93.7414 -5.8789 -2.0183 -4.2256 -0.9701 0.1105 5.6148 3.6180 0.9222 3.5507 0.1921 0.1993 5.6441 1.5458
+#> 116: 93.4104 -5.9704 -2.0428 -4.2091 -0.9807 0.1099 5.3341 4.1157 0.9363 3.4004 0.1968 0.2134 5.7764 1.4617
+#> 117: 93.5239 -5.9057 -2.0518 -4.2494 -0.9812 0.1127 6.8839 3.9099 0.9151 3.6604 0.1921 0.2095 5.4753 1.4249
+#> 118: 93.7599 -5.9418 -2.0482 -4.2272 -0.9822 0.1094 6.8133 3.7144 0.9198 3.5160 0.1971 0.2039 5.6467 1.4116
+#> 119: 93.6617 -6.0020 -2.0483 -4.2146 -0.9816 0.1003 6.4727 3.8251 0.9103 3.4716 0.1950 0.2109 5.8513 1.4268
+#> 120: 93.5436 -5.9804 -2.0458 -4.1906 -0.9819 0.1065 6.1490 3.6756 0.9088 3.2980 0.1989 0.2123 5.8268 1.4689
+#> 121: 93.4880 -5.9047 -2.0452 -4.1957 -0.9640 0.1349 5.8416 3.4918 0.8824 3.2437 0.1889 0.2017 5.7152 1.4382
+#> 122: 93.7406 -5.9844 -2.0596 -4.2328 -0.9558 0.1563 5.5495 3.7606 0.8489 3.3043 0.1795 0.2015 5.5095 1.5112
+#> 123: 93.6728 -6.0394 -2.0372 -4.2812 -0.9592 0.1507 5.2720 4.2004 0.8341 3.5274 0.1817 0.2008 5.6936 1.6011
+#> 124: 93.9591 -6.0483 -2.0280 -4.2613 -0.9594 0.1463 5.3846 4.1913 0.8351 3.4341 0.1870 0.2193 5.5694 1.5684
+#> 125: 94.0201 -5.9102 -2.0507 -4.2686 -0.9697 0.1455 5.1154 3.9818 0.8512 3.3475 0.1859 0.2165 5.6224 1.5643
+#> 126: 93.8825 -5.8970 -2.0543 -4.2569 -0.9663 0.1493 4.9144 3.7827 0.8907 3.3030 0.1876 0.2180 5.7351 1.4722
+#> 127: 93.9893 -5.8955 -2.0624 -4.2430 -0.9802 0.1476 7.2413 3.5935 0.8915 3.2740 0.1851 0.2110 5.7614 1.4305
+#> 128: 94.1849 -5.9123 -2.0624 -4.2385 -0.9786 0.1523 7.9575 3.4139 0.9094 3.2656 0.1807 0.2198 5.7366 1.4264
+#> 129: 94.0812 -6.0044 -2.0696 -4.3056 -0.9770 0.1693 8.7809 3.7526 0.9111 3.6172 0.1859 0.2255 5.8064 1.4718
+#> 130: 93.6046 -6.1387 -2.0718 -4.3056 -0.9821 0.1477 8.3419 4.3029 0.9177 3.6172 0.1867 0.2143 5.8893 1.4447
+#> 131: 93.5216 -6.1347 -2.0740 -4.3114 -0.9766 0.1288 8.2937 4.3407 0.9250 3.5298 0.1881 0.2293 5.8054 1.4219
+#> 132: 93.6142 -6.2789 -2.0786 -4.3297 -0.9716 0.1288 8.3731 5.1225 0.9236 3.6683 0.1929 0.2295 5.8064 1.4194
+#> 133: 93.4410 -5.9177 -2.0916 -4.3557 -0.9798 0.1066 7.9544 4.8663 0.9537 3.7076 0.1937 0.2279 5.9844 1.4297
+#> 134: 93.4716 -5.9152 -2.0838 -4.3611 -0.9818 0.1332 7.5567 4.6230 0.9161 3.7833 0.2017 0.2308 6.0611 1.5717
+#> 135: 93.3787 -6.0381 -2.0728 -4.2627 -0.9719 0.1051 7.2396 4.3919 0.8970 3.5941 0.1916 0.2193 5.8837 1.6057
+#> 136: 93.4339 -5.9876 -2.0801 -4.3002 -0.9690 0.1214 6.8776 4.1723 0.8888 3.4144 0.2002 0.2227 6.0141 1.5231
+#> 137: 93.7639 -6.0411 -2.0803 -4.2799 -0.9646 0.1484 6.5337 3.9765 0.8969 3.2437 0.1995 0.2115 5.9404 1.6402
+#> 138: 93.6414 -6.0122 -2.0714 -4.2666 -0.9755 0.1506 7.4057 3.7962 0.9242 3.1524 0.1934 0.2010 6.0666 1.5001
+#> 139: 93.7743 -5.7966 -2.0613 -4.2289 -0.9722 0.1383 7.9358 3.6064 0.9015 2.9948 0.1946 0.2029 5.9655 1.5250
+#> 140: 93.1082 -5.7994 -2.0388 -4.2289 -0.9659 0.1382 8.0282 3.4261 0.9053 2.9079 0.1909 0.2138 5.9183 1.5191
+#> 141: 93.2122 -6.0181 -2.0396 -4.2398 -0.9587 0.1016 8.9769 3.9426 0.9028 2.9136 0.1941 0.2195 6.1560 1.4902
+#> 142: 93.4684 -6.1438 -2.0273 -4.2541 -0.9508 0.0848 8.5281 4.8727 0.9056 2.9875 0.1901 0.2233 6.2546 1.4695
+#> 143: 93.0059 -6.0964 -2.0145 -4.2760 -0.9563 0.0826 8.1017 4.6291 0.9312 3.1063 0.1850 0.2138 6.5768 1.4391
+#> 144: 93.0612 -6.1127 -1.9951 -4.2589 -0.9539 0.0904 7.6966 4.6160 0.9623 3.1681 0.1824 0.2032 6.1506 1.4497
+#> 145: 93.5170 -6.1066 -1.9951 -4.3574 -0.9478 0.1040 7.3118 4.6263 0.9639 3.6914 0.1986 0.2292 5.9389 1.4867
+#> 146: 93.4915 -6.3235 -2.0006 -4.3866 -0.9579 0.1202 6.9462 6.0529 0.9514 3.9899 0.1887 0.2335 5.9265 1.4978
+#> 147: 93.8963 -6.1119 -2.0055 -4.3446 -0.9682 0.1242 7.1711 5.7503 0.9315 3.7904 0.1923 0.2332 5.9346 1.5021
+#> 148: 93.6758 -5.9705 -2.0137 -4.2906 -0.9614 0.1125 6.8125 5.4628 0.9506 3.6009 0.1913 0.2371 6.2579 1.4384
+#> 149: 93.6499 -6.0049 -2.0246 -4.2730 -0.9776 0.0996 6.4719 5.1896 0.9736 3.4209 0.1817 0.2252 6.3224 1.3878
+#> 150: 94.0242 -5.9760 -2.0176 -4.2182 -0.9773 0.1032 6.1483 4.9301 0.9944 3.2498 0.1807 0.2290 6.5662 1.3618
+#> 151: 93.9234 -5.8772 -2.0132 -4.2362 -0.9651 0.1058 7.2453 4.6836 0.9824 3.4860 0.1806 0.2175 6.2575 1.4370
+#> 152: 94.2513 -5.9391 -2.0814 -4.2278 -0.9753 0.1221 4.9753 3.4013 0.9808 3.3265 0.1836 0.1897 6.6966 1.3457
+#> 153: 93.9434 -6.1294 -2.0570 -4.2447 -0.9761 0.1527 5.0454 4.3115 0.9494 3.3663 0.1684 0.1680 5.9106 1.4777
+#> 154: 93.8141 -6.2749 -2.0366 -4.2383 -0.9835 0.1440 5.5466 5.3351 0.9320 3.3337 0.1731 0.1913 5.8842 1.4325
+#> 155: 94.1987 -6.1029 -2.0252 -4.2520 -0.9780 0.1132 7.1508 4.2713 0.9457 3.3428 0.1727 0.1691 6.1632 1.4658
+#> 156: 94.0626 -6.2640 -2.0263 -4.2461 -0.9854 0.1346 5.6296 5.1645 0.9423 3.3987 0.1697 0.1778 5.9631 1.4483
+#> 157: 93.9319 -6.1392 -2.0388 -4.2294 -0.9921 0.1265 5.6768 4.7366 0.9210 3.3673 0.1733 0.1789 5.9114 1.4976
+#> 158: 93.9123 -6.1970 -2.0165 -4.2241 -0.9924 0.1540 7.2552 4.7537 0.9369 3.2727 0.1805 0.1923 5.9324 1.5351
+#> 159: 93.9704 -6.4018 -2.0455 -4.2127 -0.9919 0.1413 7.7561 6.0732 0.9802 3.3376 0.1806 0.2260 6.4511 1.4227
+#> 160: 94.1967 -6.2985 -2.0412 -4.2264 -0.9795 0.1206 8.3836 6.1319 0.9689 3.4685 0.1792 0.2150 6.5116 1.4706
+#> 161: 94.3500 -6.1427 -2.0189 -4.2242 -1.0022 0.0837 8.0282 4.5505 0.9524 3.3269 0.1859 0.1816 6.0642 1.4746
+#> 162: 94.2711 -5.9578 -2.0215 -4.2078 -1.0110 0.0946 7.8634 3.3072 0.9559 3.2374 0.1876 0.1791 6.0798 1.4903
+#> 163: 93.9824 -5.8794 -2.0409 -4.2367 -0.9970 0.1150 9.3872 3.0498 0.9830 3.3179 0.1880 0.1828 5.8091 1.4852
+#> 164: 94.2013 -5.8651 -2.0122 -4.2257 -0.9906 0.1267 7.1953 3.0510 0.9697 3.2713 0.1871 0.1832 5.8741 1.5313
+#> 165: 94.1804 -5.7868 -2.0200 -4.2053 -0.9812 0.1219 6.7375 2.4769 0.9688 3.2706 0.1910 0.1859 5.7890 1.5188
+#> 166: 93.9790 -5.8156 -2.0311 -4.2438 -0.9784 0.1247 5.7617 2.6907 0.9533 3.5342 0.1953 0.1872 5.8816 1.5243
+#> 167: 93.2524 -5.8603 -2.0497 -4.2594 -0.9787 0.1265 4.7086 2.9121 0.9117 3.4696 0.1943 0.1832 5.9672 1.4567
+#> 168: 93.2924 -6.0371 -2.0528 -4.2607 -0.9727 0.1201 5.5273 4.0286 0.9177 3.4501 0.1918 0.1908 5.7790 1.4701
+#> 169: 93.4838 -6.1497 -2.0389 -4.2716 -0.9639 0.1127 5.4524 4.2700 0.9544 3.4329 0.1940 0.1871 5.7795 1.4575
+#> 170: 93.3951 -6.2298 -2.0438 -4.4133 -0.9939 0.1088 6.1460 4.6552 0.9645 4.5240 0.1978 0.2091 5.7549 1.5233
+#> 171: 93.4113 -6.1187 -2.0536 -4.4019 -0.9771 0.0899 6.8123 4.0073 0.9531 4.4290 0.1878 0.1970 5.9067 1.4857
+#> 172: 93.1140 -5.9515 -2.0530 -4.3250 -0.9723 0.1094 5.1247 3.4502 0.9572 3.8504 0.1954 0.1944 5.8583 1.4867
+#> 173: 92.9782 -6.0415 -2.0633 -4.2887 -0.9608 0.1081 4.1020 3.8967 0.9478 3.7222 0.1890 0.1812 5.9473 1.4583
+#> 174: 92.9661 -5.9295 -2.0457 -4.2907 -0.9626 0.0991 5.7954 3.3581 0.9785 3.7311 0.1867 0.2026 5.8087 1.4797
+#> 175: 93.2577 -5.8895 -2.0281 -4.2845 -0.9560 0.0829 7.3434 3.1501 0.9975 3.6334 0.1920 0.2151 5.4717 1.4832
+#> 176: 93.1210 -5.9567 -2.0370 -4.2848 -0.9488 0.0787 6.8946 3.4999 0.9983 3.6159 0.1922 0.2233 5.8426 1.4096
+#> 177: 92.5456 -6.1797 -2.0319 -4.2684 -0.9401 0.0873 6.9744 5.2939 0.9928 3.4880 0.1989 0.2213 5.9613 1.4367
+#> 178: 92.6854 -6.1483 -2.0278 -4.2705 -0.9504 0.0630 5.0582 5.0622 0.9953 3.4915 0.1930 0.2238 5.9775 1.4263
+#> 179: 93.1323 -6.1739 -2.0353 -4.2590 -0.9455 0.0584 4.9914 4.7898 0.9817 3.4163 0.1899 0.2124 5.9579 1.4242
+#> 180: 93.0611 -6.2228 -2.0441 -4.2977 -0.9387 0.0320 4.0323 5.5685 0.9890 3.7202 0.1940 0.2335 6.2224 1.4194
+#> 181: 92.7741 -6.1462 -2.0477 -4.3335 -0.9454 0.1011 3.7007 5.1590 0.9807 3.8469 0.1939 0.2463 5.9703 1.4343
+#> 182: 93.0775 -6.0640 -2.0496 -4.3171 -0.9444 0.0897 5.0266 4.5597 0.9792 3.7741 0.1931 0.2186 5.6727 1.4858
+#> 183: 93.2566 -6.1757 -2.0368 -4.2888 -0.9560 0.0809 5.8284 5.2504 0.9636 3.7078 0.1939 0.2262 5.5170 1.4560
+#> 184: 93.0357 -6.1158 -2.0217 -4.3111 -0.9453 0.0901 6.7209 5.4048 0.9503 3.8949 0.1967 0.2209 5.3578 1.4704
+#> 185: 93.0173 -6.1998 -2.0371 -4.3713 -0.9451 0.0752 6.1040 5.8272 0.9333 4.4038 0.1951 0.2238 5.5896 1.4202
+#> 186: 93.2835 -6.1217 -2.0383 -4.3308 -0.9574 0.1110 6.0519 4.7669 0.9400 4.0265 0.1972 0.2274 5.4560 1.4602
+#> 187: 93.5312 -6.3356 -2.0253 -4.3418 -0.9583 0.1166 6.7561 5.8784 0.9346 4.0264 0.2038 0.2281 5.5024 1.4994
+#> 188: 93.6460 -5.8426 -2.0237 -4.4519 -0.9594 0.1283 6.3492 3.4189 0.9091 4.9358 0.2086 0.2348 5.4301 1.5893
+#> 189: 93.8538 -6.0183 -2.0178 -4.3911 -0.9797 0.1262 8.7939 3.7358 0.9008 4.4894 0.2125 0.2199 5.6613 1.5073
+#> 190: 93.1543 -6.1364 -2.0451 -4.4389 -0.9708 0.1584 9.9803 4.2747 0.8922 4.8507 0.2084 0.2607 5.9136 1.4572
+#> 191: 93.4334 -6.1466 -2.0389 -4.4661 -0.9678 0.1565 7.8390 4.4393 0.9022 4.7857 0.2105 0.2634 5.7161 1.5325
+#> 192: 93.3623 -6.0940 -2.0240 -4.4569 -0.9673 0.1420 8.0856 4.3185 0.8895 4.4721 0.2113 0.2350 5.5282 1.5221
+#> 193: 93.1990 -5.9864 -2.0301 -4.4538 -0.9563 0.1515 8.4425 3.7598 0.8814 4.4376 0.2013 0.2257 5.4205 1.4820
+#> 194: 93.3165 -6.0045 -2.0353 -4.4314 -0.9525 0.1486 8.2370 3.6742 0.8947 4.4594 0.1960 0.2248 5.4579 1.4767
+#> 195: 93.1288 -6.1006 -2.0551 -4.5184 -0.9503 0.1583 9.6259 4.2294 0.9040 5.1981 0.1950 0.1962 5.5602 1.4254
+#> 196: 93.1943 -5.9871 -2.0607 -4.4728 -0.9446 0.1482 9.3401 3.5579 0.8925 4.7901 0.1892 0.1879 5.7296 1.4172
+#> 197: 93.5803 -5.9131 -2.0522 -4.3675 -0.9476 0.1571 7.2599 3.4241 0.8857 3.8551 0.1886 0.1793 5.4832 1.6006
+#> 198: 93.5703 -5.9980 -2.0550 -4.3578 -0.9519 0.1491 7.0416 3.8805 0.8563 3.7930 0.1882 0.1896 5.4355 1.5402
+#> 199: 93.2909 -5.8288 -2.0532 -4.3605 -0.9518 0.1692 8.3926 3.0173 0.8566 3.8610 0.1902 0.2033 5.5735 1.5647
+#> 200: 93.4049 -5.7474 -2.0447 -4.3548 -0.9517 0.1812 7.4977 2.8256 0.8520 3.8236 0.1897 0.2060 5.5092 1.5699
+#> 201: 93.3386 -5.8209 -2.0398 -4.4174 -0.9597 0.1738 6.3555 3.0871 0.8431 4.3211 0.1853 0.2062 5.5460 1.5925
+#> 202: 93.3397 -5.8313 -2.0387 -4.4364 -0.9580 0.1669 6.0946 3.1018 0.8460 4.5093 0.1821 0.2068 5.6622 1.5740
+#> 203: 93.3071 -5.8276 -2.0384 -4.4758 -0.9571 0.1639 5.7815 3.0575 0.8608 4.9441 0.1826 0.2052 5.6855 1.5570
+#> 204: 93.3138 -5.8477 -2.0368 -4.4714 -0.9541 0.1658 5.7526 3.1322 0.8704 4.9129 0.1816 0.2057 5.6642 1.5606
+#> 205: 93.3066 -5.8537 -2.0395 -4.4842 -0.9521 0.1642 5.6045 3.1633 0.8748 5.0053 0.1805 0.2036 5.6633 1.5550
+#> 206: 93.3042 -5.8790 -2.0453 -4.4977 -0.9501 0.1633 5.7219 3.3320 0.8807 5.1121 0.1793 0.1999 5.6888 1.5413
+#> 207: 93.3281 -5.9005 -2.0504 -4.5109 -0.9480 0.1629 5.8004 3.4696 0.8865 5.2248 0.1789 0.1961 5.7206 1.5357
+#> 208: 93.3437 -5.8972 -2.0569 -4.5200 -0.9452 0.1641 5.7523 3.4604 0.8875 5.2848 0.1787 0.1933 5.7450 1.5288
+#> 209: 93.3265 -5.8864 -2.0628 -4.5092 -0.9440 0.1639 5.5355 3.4138 0.8882 5.1586 0.1791 0.1916 5.7744 1.5283
+#> 210: 93.3087 -5.8812 -2.0671 -4.5004 -0.9426 0.1677 5.3488 3.3975 0.8895 5.0589 0.1798 0.1924 5.7781 1.5307
+#> 211: 93.2807 -5.8760 -2.0703 -4.5009 -0.9413 0.1709 5.2654 3.3770 0.8894 5.0377 0.1805 0.1927 5.7808 1.5282
+#> 212: 93.2815 -5.8637 -2.0711 -4.4955 -0.9409 0.1708 5.3028 3.3250 0.8914 4.9702 0.1819 0.1941 5.7827 1.5274
+#> 213: 93.2828 -5.8481 -2.0709 -4.4895 -0.9396 0.1702 5.3840 3.2614 0.8913 4.9108 0.1826 0.1953 5.7744 1.5301
+#> 214: 93.2645 -5.8422 -2.0704 -4.4882 -0.9384 0.1710 5.3939 3.2358 0.8931 4.8944 0.1828 0.1955 5.7797 1.5351
+#> 215: 93.2591 -5.8519 -2.0709 -4.4858 -0.9380 0.1713 5.5142 3.2959 0.8953 4.8587 0.1822 0.1960 5.7853 1.5369
+#> 216: 93.2595 -5.8523 -2.0715 -4.4827 -0.9376 0.1723 5.5563 3.3077 0.8964 4.8306 0.1817 0.1973 5.7975 1.5396
+#> 217: 93.2503 -5.8512 -2.0732 -4.4737 -0.9373 0.1734 5.5036 3.3182 0.8959 4.7582 0.1817 0.1992 5.7940 1.5365
+#> 218: 93.2345 -5.8463 -2.0749 -4.4639 -0.9372 0.1747 5.5046 3.2959 0.8959 4.6771 0.1817 0.2008 5.7889 1.5340
+#> 219: 93.2264 -5.8439 -2.0757 -4.4549 -0.9364 0.1759 5.4970 3.2802 0.8966 4.6015 0.1819 0.2027 5.7804 1.5321
+#> 220: 93.2259 -5.8464 -2.0758 -4.4493 -0.9363 0.1771 5.4793 3.2944 0.8950 4.5498 0.1823 0.2049 5.7745 1.5344
+#> 221: 93.2243 -5.8505 -2.0768 -4.4443 -0.9367 0.1785 5.5360 3.3132 0.8924 4.5028 0.1829 0.2068 5.7556 1.5329
+#> 222: 93.2385 -5.8603 -2.0776 -4.4371 -0.9376 0.1800 5.5401 3.3878 0.8903 4.4416 0.1834 0.2096 5.7522 1.5317
+#> 223: 93.2339 -5.8634 -2.0780 -4.4309 -0.9377 0.1803 5.5522 3.4132 0.8882 4.3844 0.1838 0.2118 5.7457 1.5323
+#> 224: 93.2379 -5.8686 -2.0778 -4.4262 -0.9374 0.1803 5.5469 3.4421 0.8848 4.3375 0.1842 0.2137 5.7429 1.5323
+#> 225: 93.2329 -5.8654 -2.0784 -4.4222 -0.9373 0.1811 5.5553 3.4255 0.8843 4.2952 0.1848 0.2160 5.7452 1.5295
+#> 226: 93.2330 -5.8621 -2.0789 -4.4182 -0.9366 0.1816 5.5838 3.4123 0.8838 4.2565 0.1858 0.2176 5.7453 1.5284
+#> 227: 93.2309 -5.8549 -2.0794 -4.4153 -0.9365 0.1823 5.6720 3.3787 0.8827 4.2227 0.1866 0.2181 5.7339 1.5287
+#> 228: 93.2248 -5.8556 -2.0794 -4.4116 -0.9372 0.1832 5.7344 3.3780 0.8830 4.1863 0.1873 0.2200 5.7232 1.5308
+#> 229: 93.2215 -5.8615 -2.0798 -4.4081 -0.9373 0.1844 5.8478 3.4087 0.8821 4.1558 0.1878 0.2217 5.7174 1.5283
+#> 230: 93.2122 -5.8646 -2.0807 -4.4053 -0.9372 0.1858 5.8987 3.4233 0.8800 4.1288 0.1881 0.2233 5.7073 1.5272
+#> 231: 93.2080 -5.8665 -2.0816 -4.4025 -0.9372 0.1872 5.9544 3.4381 0.8782 4.1008 0.1883 0.2250 5.7006 1.5283
+#> 232: 93.1921 -5.8677 -2.0829 -4.3997 -0.9370 0.1887 5.9768 3.4440 0.8770 4.0748 0.1883 0.2268 5.7012 1.5261
+#> 233: 93.1794 -5.8674 -2.0840 -4.3972 -0.9363 0.1892 6.0074 3.4397 0.8757 4.0495 0.1884 0.2281 5.6997 1.5235
+#> 234: 93.1623 -5.8677 -2.0853 -4.3959 -0.9358 0.1898 5.9759 3.4442 0.8750 4.0330 0.1887 0.2295 5.7000 1.5223
+#> 235: 93.1499 -5.8709 -2.0862 -4.3918 -0.9356 0.1900 5.9951 3.4709 0.8747 4.0020 0.1891 0.2309 5.7002 1.5219
+#> 236: 93.1408 -5.8764 -2.0875 -4.3879 -0.9349 0.1898 6.0359 3.5027 0.8752 3.9720 0.1895 0.2321 5.7098 1.5196
+#> 237: 93.1307 -5.8766 -2.0887 -4.3843 -0.9344 0.1896 6.0589 3.5108 0.8755 3.9437 0.1900 0.2330 5.7176 1.5174
+#> 238: 93.1233 -5.8767 -2.0889 -4.3806 -0.9341 0.1891 6.0959 3.5158 0.8745 3.9173 0.1907 0.2339 5.7198 1.5169
+#> 239: 93.1245 -5.8810 -2.0889 -4.3775 -0.9337 0.1885 6.1196 3.5614 0.8746 3.8935 0.1915 0.2349 5.7177 1.5172
+#> 240: 93.1180 -5.8836 -2.0893 -4.3745 -0.9332 0.1883 6.1647 3.6004 0.8741 3.8709 0.1921 0.2360 5.7150 1.5192
+#> 241: 93.1096 -5.8838 -2.0898 -4.3714 -0.9327 0.1883 6.2283 3.6196 0.8743 3.8487 0.1927 0.2366 5.7177 1.5202
+#> 242: 93.1058 -5.8804 -2.0912 -4.3684 -0.9320 0.1888 6.2553 3.6018 0.8723 3.8274 0.1933 0.2378 5.7265 1.5198
+#> 243: 93.0953 -5.8762 -2.0924 -4.3668 -0.9315 0.1892 6.2692 3.5785 0.8705 3.8130 0.1940 0.2391 5.7353 1.5205
+#> 244: 93.0840 -5.8758 -2.0928 -4.3658 -0.9310 0.1889 6.2702 3.5746 0.8695 3.8007 0.1947 0.2401 5.7382 1.5205
+#> 245: 93.0720 -5.8795 -2.0933 -4.3647 -0.9306 0.1895 6.3022 3.5971 0.8685 3.7886 0.1953 0.2407 5.7367 1.5192
+#> 246: 93.0626 -5.8798 -2.0933 -4.3637 -0.9301 0.1898 6.2987 3.5992 0.8680 3.7781 0.1957 0.2410 5.7331 1.5184
+#> 247: 93.0526 -5.8805 -2.0934 -4.3610 -0.9298 0.1903 6.3067 3.6060 0.8682 3.7618 0.1963 0.2414 5.7329 1.5189
+#> 248: 93.0481 -5.8780 -2.0933 -4.3583 -0.9296 0.1911 6.3135 3.6007 0.8683 3.7460 0.1967 0.2420 5.7344 1.5191
+#> 249: 93.0483 -5.8762 -2.0933 -4.3558 -0.9294 0.1913 6.3095 3.5961 0.8685 3.7298 0.1970 0.2422 5.7414 1.5179
+#> 250: 93.0520 -5.8768 -2.0931 -4.3538 -0.9292 0.1912 6.2900 3.6003 0.8692 3.7176 0.1973 0.2424 5.7547 1.5148
+#> 251: 93.0430 -5.8769 -2.0930 -4.3516 -0.9291 0.1905 6.2815 3.6041 0.8704 3.7045 0.1975 0.2427 5.7653 1.5123
+#> 252: 93.0300 -5.8743 -2.0928 -4.3490 -0.9291 0.1901 6.2896 3.5885 0.8716 3.6919 0.1978 0.2428 5.7797 1.5106
+#> 253: 93.0217 -5.8740 -2.0926 -4.3468 -0.9289 0.1898 6.3238 3.5875 0.8731 3.6817 0.1981 0.2429 5.7885 1.5102
+#> 254: 93.0147 -5.8729 -2.0924 -4.3439 -0.9289 0.1892 6.3418 3.5857 0.8732 3.6683 0.1980 0.2426 5.7912 1.5102
+#> 255: 93.0144 -5.8743 -2.0922 -4.3407 -0.9290 0.1885 6.3755 3.5933 0.8735 3.6580 0.1979 0.2420 5.7932 1.5086
+#> 256: 93.0136 -5.8778 -2.0919 -4.3376 -0.9290 0.1876 6.3932 3.6240 0.8741 3.6481 0.1980 0.2418 5.7969 1.5066
+#> 257: 93.0116 -5.8792 -2.0917 -4.3345 -0.9291 0.1862 6.4096 3.6459 0.8744 3.6385 0.1980 0.2414 5.7990 1.5065
+#> 258: 93.0084 -5.8812 -2.0913 -4.3319 -0.9290 0.1842 6.4231 3.6686 0.8753 3.6281 0.1980 0.2414 5.8024 1.5050
+#> 259: 93.0090 -5.8866 -2.0909 -4.3293 -0.9287 0.1825 6.4361 3.7063 0.8762 3.6181 0.1981 0.2413 5.8106 1.5030
+#> 260: 93.0067 -5.8911 -2.0902 -4.3265 -0.9283 0.1811 6.4128 3.7384 0.8765 3.6076 0.1981 0.2412 5.8102 1.5026
+#> 261: 93.0060 -5.8933 -2.0894 -4.3237 -0.9284 0.1799 6.4253 3.7604 0.8765 3.5968 0.1981 0.2410 5.8080 1.5026
+#> 262: 93.0051 -5.8934 -2.0884 -4.3208 -0.9285 0.1789 6.4008 3.7597 0.8762 3.5855 0.1981 0.2412 5.8046 1.5020
+#> 263: 93.0019 -5.8945 -2.0875 -4.3182 -0.9287 0.1781 6.3788 3.7644 0.8758 3.5756 0.1982 0.2411 5.8048 1.5023
+#> 264: 93.0021 -5.8959 -2.0870 -4.3158 -0.9293 0.1773 6.3614 3.7682 0.8749 3.5667 0.1983 0.2410 5.8017 1.5021
+#> 265: 93.0053 -5.8989 -2.0866 -4.3130 -0.9296 0.1766 6.3506 3.7814 0.8739 3.5567 0.1982 0.2409 5.7995 1.5018
+#> 266: 93.0061 -5.8992 -2.0864 -4.3104 -0.9300 0.1757 6.3307 3.7730 0.8733 3.5471 0.1982 0.2408 5.7994 1.5012
+#> 267: 93.0098 -5.9009 -2.0861 -4.3077 -0.9302 0.1749 6.3326 3.7738 0.8730 3.5388 0.1983 0.2407 5.7964 1.5004
+#> 268: 93.0144 -5.9000 -2.0853 -4.3054 -0.9304 0.1740 6.3487 3.7623 0.8729 3.5290 0.1985 0.2405 5.7897 1.5014
+#> 269: 93.0146 -5.8984 -2.0847 -4.3032 -0.9306 0.1731 6.3716 3.7485 0.8735 3.5197 0.1985 0.2402 5.7867 1.5016
+#> 270: 93.0159 -5.8950 -2.0842 -4.3013 -0.9307 0.1722 6.3630 3.7266 0.8743 3.5098 0.1986 0.2400 5.7837 1.5016
+#> 271: 93.0161 -5.8925 -2.0837 -4.2995 -0.9309 0.1715 6.3539 3.7068 0.8744 3.5001 0.1986 0.2400 5.7843 1.5020
+#> 272: 93.0195 -5.8919 -2.0837 -4.2977 -0.9314 0.1710 6.3430 3.6964 0.8744 3.4922 0.1985 0.2400 5.7859 1.5031
+#> 273: 93.0184 -5.8923 -2.0837 -4.2961 -0.9318 0.1705 6.3531 3.6914 0.8743 3.4854 0.1984 0.2402 5.7880 1.5030
+#> 274: 93.0178 -5.8927 -2.0834 -4.2951 -0.9320 0.1701 6.3818 3.6865 0.8749 3.4824 0.1984 0.2403 5.7928 1.5020
+#> 275: 93.0204 -5.8937 -2.0833 -4.2942 -0.9324 0.1700 6.3961 3.6842 0.8754 3.4790 0.1984 0.2402 5.7949 1.5011
+#> 276: 93.0228 -5.8958 -2.0833 -4.2932 -0.9327 0.1699 6.3965 3.6870 0.8760 3.4752 0.1984 0.2402 5.7934 1.5002
+#> 277: 93.0251 -5.9000 -2.0833 -4.2921 -0.9329 0.1695 6.4076 3.7032 0.8766 3.4712 0.1985 0.2400 5.7979 1.4989
+#> 278: 93.0297 -5.9021 -2.0833 -4.2912 -0.9331 0.1690 6.4279 3.7073 0.8771 3.4671 0.1986 0.2399 5.7978 1.4981
+#> 279: 93.0273 -5.9021 -2.0832 -4.2902 -0.9332 0.1684 6.4349 3.7003 0.8779 3.4622 0.1988 0.2400 5.7993 1.4972
+#> 280: 93.0236 -5.9030 -2.0831 -4.2892 -0.9334 0.1674 6.4776 3.6986 0.8787 3.4576 0.1990 0.2401 5.8026 1.4963
+#> 281: 93.0172 -5.9037 -2.0829 -4.2881 -0.9337 0.1665 6.4942 3.6984 0.8797 3.4536 0.1992 0.2402 5.8056 1.4955
+#> 282: 93.0147 -5.9055 -2.0827 -4.2872 -0.9339 0.1656 6.4861 3.7031 0.8810 3.4492 0.1992 0.2403 5.8107 1.4954
+#> 283: 93.0138 -5.9053 -2.0824 -4.2865 -0.9341 0.1646 6.4962 3.6967 0.8822 3.4451 0.1993 0.2406 5.8142 1.4959
+#> 284: 93.0132 -5.9067 -2.0821 -4.2864 -0.9343 0.1636 6.5021 3.7013 0.8838 3.4437 0.1993 0.2406 5.8146 1.4955
+#> 285: 93.0138 -5.9081 -2.0819 -4.2859 -0.9343 0.1628 6.5037 3.7043 0.8851 3.4406 0.1994 0.2406 5.8146 1.4945
+#> 286: 93.0119 -5.9086 -2.0815 -4.2858 -0.9342 0.1620 6.5068 3.7037 0.8864 3.4395 0.1994 0.2404 5.8133 1.4936
+#> 287: 93.0122 -5.9089 -2.0813 -4.2860 -0.9342 0.1614 6.5202 3.7044 0.8872 3.4399 0.1997 0.2401 5.8096 1.4929
+#> 288: 93.0104 -5.9083 -2.0812 -4.2858 -0.9342 0.1609 6.5237 3.6997 0.8876 3.4376 0.1999 0.2398 5.8041 1.4924
+#> 289: 93.0076 -5.9066 -2.0812 -4.2854 -0.9342 0.1604 6.5121 3.6893 0.8881 3.4342 0.1999 0.2394 5.8021 1.4922
+#> 290: 93.0064 -5.9052 -2.0813 -4.2851 -0.9343 0.1602 6.5106 3.6772 0.8886 3.4309 0.2000 0.2389 5.7988 1.4915
+#> 291: 93.0071 -5.9031 -2.0813 -4.2849 -0.9345 0.1601 6.5031 3.6628 0.8891 3.4284 0.2000 0.2384 5.7959 1.4908
+#> 292: 93.0114 -5.9023 -2.0809 -4.2841 -0.9346 0.1594 6.4930 3.6538 0.8894 3.4237 0.2001 0.2383 5.7923 1.4902
+#> 293: 93.0148 -5.9032 -2.0807 -4.2834 -0.9348 0.1589 6.4836 3.6542 0.8898 3.4206 0.2002 0.2380 5.7893 1.4893
+#> 294: 93.0161 -5.9026 -2.0806 -4.2826 -0.9349 0.1582 6.4719 3.6469 0.8901 3.4176 0.2005 0.2375 5.7898 1.4886
+#> 295: 93.0212 -5.9008 -2.0806 -4.2817 -0.9350 0.1576 6.4649 3.6372 0.8904 3.4145 0.2007 0.2370 5.7885 1.4890
+#> 296: 93.0270 -5.8989 -2.0805 -4.2809 -0.9351 0.1569 6.4835 3.6279 0.8911 3.4124 0.2010 0.2366 5.7886 1.4884
+#> 297: 93.0291 -5.8969 -2.0803 -4.2800 -0.9352 0.1560 6.5014 3.6177 0.8915 3.4094 0.2012 0.2364 5.7873 1.4880
+#> 298: 93.0332 -5.8963 -2.0801 -4.2790 -0.9352 0.1551 6.5168 3.6111 0.8919 3.4065 0.2014 0.2361 5.7855 1.4875
+#> 299: 93.0339 -5.8961 -2.0799 -4.2782 -0.9352 0.1542 6.5288 3.6081 0.8927 3.4038 0.2015 0.2358 5.7844 1.4869
+#> 300: 93.0335 -5.8971 -2.0797 -4.2772 -0.9351 0.1533 6.5409 3.6097 0.8937 3.4009 0.2017 0.2356 5.7844 1.4859
+#> 301: 93.0320 -5.8979 -2.0796 -4.2762 -0.9350 0.1522 6.5553 3.6126 0.8945 3.3977 0.2020 0.2354 5.7898 1.4847
+#> 302: 93.0321 -5.8997 -2.0795 -4.2751 -0.9351 0.1513 6.5737 3.6195 0.8956 3.3943 0.2023 0.2351 5.7917 1.4835
+#> 303: 93.0328 -5.8984 -2.0792 -4.2739 -0.9351 0.1504 6.5888 3.6111 0.8964 3.3912 0.2025 0.2350 5.7915 1.4825
+#> 304: 93.0357 -5.8969 -2.0790 -4.2728 -0.9350 0.1494 6.5907 3.6018 0.8975 3.3882 0.2026 0.2348 5.7929 1.4813
+#> 305: 93.0351 -5.8953 -2.0786 -4.2718 -0.9349 0.1484 6.5764 3.5916 0.8986 3.3858 0.2027 0.2345 5.7937 1.4816
+#> 306: 93.0352 -5.8950 -2.0784 -4.2707 -0.9350 0.1475 6.5727 3.5890 0.8999 3.3835 0.2028 0.2341 5.7981 1.4810
+#> 307: 93.0354 -5.8947 -2.0784 -4.2699 -0.9351 0.1466 6.5759 3.5853 0.9010 3.3820 0.2030 0.2339 5.8028 1.4799
+#> 308: 93.0336 -5.8938 -2.0783 -4.2690 -0.9351 0.1459 6.5855 3.5776 0.9022 3.3809 0.2031 0.2333 5.8014 1.4788
+#> 309: 93.0311 -5.8931 -2.0780 -4.2683 -0.9351 0.1452 6.5799 3.5717 0.9038 3.3805 0.2033 0.2328 5.8048 1.4779
+#> 310: 93.0303 -5.8915 -2.0778 -4.2675 -0.9352 0.1447 6.5716 3.5609 0.9046 3.3797 0.2033 0.2323 5.8060 1.4774
+#> 311: 93.0275 -5.8915 -2.0776 -4.2668 -0.9352 0.1441 6.5679 3.5581 0.9052 3.3788 0.2034 0.2319 5.8056 1.4770
+#> 312: 93.0258 -5.8920 -2.0775 -4.2659 -0.9352 0.1435 6.5573 3.5571 0.9058 3.3775 0.2033 0.2314 5.8053 1.4766
+#> 313: 93.0234 -5.8928 -2.0773 -4.2649 -0.9353 0.1431 6.5510 3.5573 0.9065 3.3761 0.2033 0.2309 5.8046 1.4757
+#> 314: 93.0237 -5.8937 -2.0771 -4.2639 -0.9355 0.1425 6.5488 3.5578 0.9074 3.3747 0.2033 0.2303 5.8029 1.4751
+#> 315: 93.0237 -5.8940 -2.0769 -4.2629 -0.9357 0.1420 6.5480 3.5565 0.9081 3.3730 0.2034 0.2299 5.8010 1.4746
+#> 316: 93.0218 -5.8936 -2.0767 -4.2617 -0.9358 0.1413 6.5424 3.5517 0.9087 3.3705 0.2034 0.2296 5.7992 1.4741
+#> 317: 93.0218 -5.8932 -2.0766 -4.2606 -0.9359 0.1406 6.5576 3.5474 0.9091 3.3679 0.2034 0.2292 5.7965 1.4736
+#> 318: 93.0215 -5.8927 -2.0765 -4.2597 -0.9361 0.1402 6.5884 3.5420 0.9096 3.3661 0.2034 0.2288 5.7960 1.4727
+#> 319: 93.0201 -5.8938 -2.0764 -4.2588 -0.9361 0.1397 6.6095 3.5439 0.9101 3.3642 0.2034 0.2283 5.7943 1.4719
+#> 320: 93.0188 -5.8926 -2.0763 -4.2579 -0.9361 0.1392 6.6170 3.5368 0.9103 3.3622 0.2034 0.2282 5.7930 1.4711
+#> 321: 93.0155 -5.8908 -2.0762 -4.2569 -0.9361 0.1385 6.6328 3.5268 0.9105 3.3598 0.2033 0.2282 5.7921 1.4702
+#> 322: 93.0133 -5.8894 -2.0760 -4.2561 -0.9360 0.1378 6.6415 3.5192 0.9110 3.3580 0.2032 0.2282 5.7903 1.4698
+#> 323: 93.0089 -5.8888 -2.0759 -4.2555 -0.9360 0.1372 6.6480 3.5131 0.9107 3.3563 0.2031 0.2285 5.7915 1.4691
+#> 324: 93.0038 -5.8881 -2.0758 -4.2547 -0.9359 0.1364 6.6639 3.5076 0.9106 3.3547 0.2029 0.2287 5.7912 1.4687
+#> 325: 93.0011 -5.8871 -2.0756 -4.2540 -0.9359 0.1361 6.6587 3.5005 0.9102 3.3531 0.2028 0.2289 5.7896 1.4686
+#> 326: 93.0033 -5.8874 -2.0755 -4.2535 -0.9360 0.1360 6.6621 3.4995 0.9098 3.3510 0.2026 0.2294 5.7883 1.4686
+#> 327: 93.0039 -5.8885 -2.0754 -4.2532 -0.9361 0.1359 6.6589 3.5051 0.9093 3.3497 0.2025 0.2297 5.7869 1.4687
+#> 328: 93.0061 -5.8896 -2.0753 -4.2529 -0.9362 0.1355 6.6671 3.5132 0.9088 3.3484 0.2024 0.2299 5.7854 1.4687
+#> 329: 93.0077 -5.8915 -2.0755 -4.2525 -0.9363 0.1352 6.6719 3.5255 0.9085 3.3464 0.2024 0.2301 5.7850 1.4682
+#> 330: 93.0061 -5.8942 -2.0757 -4.2518 -0.9365 0.1351 6.6696 3.5399 0.9083 3.3438 0.2023 0.2302 5.7840 1.4680
+#> 331: 93.0032 -5.8953 -2.0759 -4.2513 -0.9366 0.1348 6.6554 3.5433 0.9080 3.3411 0.2022 0.2302 5.7839 1.4677
+#> 332: 93.0013 -5.8956 -2.0761 -4.2507 -0.9367 0.1347 6.6298 3.5423 0.9079 3.3385 0.2021 0.2302 5.7851 1.4672
+#> 333: 93.0026 -5.8950 -2.0764 -4.2502 -0.9368 0.1346 6.6207 3.5365 0.9078 3.3357 0.2021 0.2303 5.7849 1.4667
+#> 334: 93.0019 -5.8933 -2.0767 -4.2497 -0.9369 0.1348 6.6145 3.5259 0.9077 3.3330 0.2021 0.2302 5.7856 1.4662
+#> 335: 93.0038 -5.8930 -2.0768 -4.2492 -0.9370 0.1348 6.6200 3.5227 0.9078 3.3307 0.2020 0.2303 5.7845 1.4654
+#> 336: 93.0038 -5.8923 -2.0765 -4.2488 -0.9371 0.1348 6.6316 3.5180 0.9081 3.3291 0.2019 0.2304 5.7837 1.4654
+#> 337: 93.0074 -5.8927 -2.0764 -4.2485 -0.9373 0.1349 6.6509 3.5187 0.9083 3.3275 0.2018 0.2304 5.7808 1.4655
+#> 338: 93.0117 -5.8950 -2.0761 -4.2483 -0.9377 0.1349 6.6559 3.5291 0.9087 3.3263 0.2018 0.2303 5.7770 1.4657
+#> 339: 93.0172 -5.8960 -2.0759 -4.2482 -0.9380 0.1349 6.6610 3.5304 0.9090 3.3260 0.2017 0.2302 5.7744 1.4657
+#> 340: 93.0179 -5.8977 -2.0757 -4.2481 -0.9383 0.1349 6.6583 3.5340 0.9093 3.3263 0.2017 0.2301 5.7749 1.4650
+#> 341: 93.0201 -5.8986 -2.0755 -4.2484 -0.9386 0.1348 6.6603 3.5337 0.9092 3.3283 0.2018 0.2300 5.7738 1.4650
+#> 342: 93.0245 -5.8990 -2.0752 -4.2484 -0.9389 0.1348 6.6680 3.5324 0.9093 3.3297 0.2018 0.2300 5.7727 1.4649
+#> 343: 93.0302 -5.9006 -2.0751 -4.2484 -0.9391 0.1347 6.6715 3.5367 0.9093 3.3313 0.2017 0.2300 5.7729 1.4645
+#> 344: 93.0340 -5.9026 -2.0749 -4.2484 -0.9394 0.1346 6.6793 3.5438 0.9093 3.3326 0.2017 0.2301 5.7709 1.4646
+#> 345: 93.0372 -5.9049 -2.0746 -4.2484 -0.9397 0.1347 6.6874 3.5515 0.9090 3.3340 0.2017 0.2301 5.7688 1.4648
+#> 346: 93.0372 -5.9063 -2.0743 -4.2483 -0.9399 0.1348 6.6963 3.5592 0.9090 3.3348 0.2018 0.2299 5.7680 1.4656
+#> 347: 93.0383 -5.9075 -2.0742 -4.2481 -0.9402 0.1350 6.7101 3.5658 0.9093 3.3353 0.2018 0.2299 5.7672 1.4649
+#> 348: 93.0412 -5.9084 -2.0742 -4.2479 -0.9405 0.1351 6.7183 3.5707 0.9095 3.3356 0.2019 0.2297 5.7657 1.4645
+#> 349: 93.0436 -5.9097 -2.0742 -4.2477 -0.9407 0.1351 6.7143 3.5783 0.9098 3.3359 0.2019 0.2295 5.7646 1.4643
+#> 350: 93.0476 -5.9105 -2.0742 -4.2474 -0.9409 0.1351 6.7239 3.5808 0.9100 3.3354 0.2019 0.2294 5.7628 1.4639
+#> 351: 93.0506 -5.9113 -2.0741 -4.2473 -0.9411 0.1352 6.7270 3.5825 0.9103 3.3356 0.2019 0.2292 5.7604 1.4637
+#> 352: 93.0529 -5.9127 -2.0740 -4.2471 -0.9413 0.1353 6.7312 3.5886 0.9107 3.3358 0.2019 0.2290 5.7594 1.4634
+#> 353: 93.0580 -5.9139 -2.0739 -4.2470 -0.9415 0.1354 6.7315 3.5922 0.9111 3.3357 0.2019 0.2288 5.7571 1.4636
+#> 354: 93.0639 -5.9129 -2.0738 -4.2468 -0.9417 0.1354 6.7390 3.5876 0.9112 3.3356 0.2018 0.2286 5.7541 1.4642
+#> 355: 93.0671 -5.9131 -2.0737 -4.2467 -0.9417 0.1353 6.7348 3.5906 0.9113 3.3354 0.2017 0.2284 5.7520 1.4648
+#> 356: 93.0682 -5.9134 -2.0737 -4.2465 -0.9418 0.1352 6.7329 3.5962 0.9113 3.3353 0.2017 0.2283 5.7505 1.4649
+#> 357: 93.0698 -5.9128 -2.0738 -4.2471 -0.9418 0.1354 6.7397 3.5933 0.9115 3.3388 0.2016 0.2280 5.7512 1.4651
+#> 358: 93.0709 -5.9129 -2.0740 -4.2475 -0.9419 0.1355 6.7379 3.5915 0.9119 3.3416 0.2016 0.2278 5.7526 1.4644
+#> 359: 93.0718 -5.9128 -2.0742 -4.2478 -0.9419 0.1358 6.7428 3.5886 0.9123 3.3432 0.2015 0.2275 5.7516 1.4641
+#> 360: 93.0693 -5.9136 -2.0743 -4.2481 -0.9419 0.1360 6.7385 3.5930 0.9125 3.3443 0.2015 0.2272 5.7511 1.4636
+#> 361: 93.0674 -5.9148 -2.0744 -4.2484 -0.9419 0.1361 6.7230 3.6002 0.9127 3.3458 0.2015 0.2270 5.7514 1.4634
+#> 362: 93.0660 -5.9168 -2.0745 -4.2486 -0.9420 0.1361 6.7313 3.6117 0.9130 3.3473 0.2014 0.2270 5.7506 1.4636
+#> 363: 93.0635 -5.9196 -2.0746 -4.2490 -0.9421 0.1360 6.7388 3.6275 0.9132 3.3500 0.2014 0.2269 5.7493 1.4636
+#> 364: 93.0631 -5.9210 -2.0747 -4.2497 -0.9421 0.1361 6.7383 3.6323 0.9135 3.3548 0.2015 0.2268 5.7483 1.4634
+#> 365: 93.0635 -5.9219 -2.0747 -4.2504 -0.9421 0.1361 6.7402 3.6341 0.9137 3.3590 0.2015 0.2268 5.7461 1.4635
+#> 366: 93.0640 -5.9232 -2.0746 -4.2511 -0.9422 0.1362 6.7477 3.6409 0.9142 3.3624 0.2015 0.2267 5.7451 1.4641
+#> 367: 93.0616 -5.9247 -2.0746 -4.2518 -0.9422 0.1364 6.7557 3.6473 0.9148 3.3653 0.2015 0.2269 5.7472 1.4640
+#> 368: 93.0601 -5.9247 -2.0746 -4.2522 -0.9422 0.1366 6.7632 3.6452 0.9150 3.3678 0.2015 0.2270 5.7482 1.4639
+#> 369: 93.0583 -5.9240 -2.0748 -4.2527 -0.9423 0.1369 6.7737 3.6395 0.9148 3.3695 0.2015 0.2273 5.7499 1.4636
+#> 370: 93.0591 -5.9236 -2.0752 -4.2532 -0.9423 0.1373 6.7721 3.6352 0.9145 3.3718 0.2015 0.2276 5.7513 1.4636
+#> 371: 93.0607 -5.9235 -2.0755 -4.2540 -0.9424 0.1378 6.7682 3.6330 0.9143 3.3754 0.2015 0.2280 5.7535 1.4635
+#> 372: 93.0615 -5.9229 -2.0759 -4.2549 -0.9424 0.1382 6.7640 3.6288 0.9142 3.3795 0.2014 0.2284 5.7553 1.4633
+#> 373: 93.0612 -5.9237 -2.0763 -4.2557 -0.9424 0.1385 6.7641 3.6327 0.9140 3.3832 0.2012 0.2288 5.7570 1.4629
+#> 374: 93.0611 -5.9240 -2.0766 -4.2565 -0.9424 0.1389 6.7701 3.6341 0.9137 3.3872 0.2011 0.2293 5.7599 1.4625
+#> 375: 93.0615 -5.9247 -2.0770 -4.2573 -0.9424 0.1393 6.7729 3.6362 0.9134 3.3912 0.2009 0.2296 5.7629 1.4620
+#> 376: 93.0621 -5.9248 -2.0772 -4.2578 -0.9425 0.1397 6.7732 3.6371 0.9132 3.3931 0.2008 0.2298 5.7654 1.4613
+#> 377: 93.0622 -5.9255 -2.0774 -4.2582 -0.9426 0.1401 6.7681 3.6389 0.9130 3.3953 0.2007 0.2300 5.7678 1.4607
+#> 378: 93.0609 -5.9256 -2.0775 -4.2585 -0.9426 0.1402 6.7705 3.6381 0.9128 3.3972 0.2006 0.2301 5.7673 1.4602
+#> 379: 93.0590 -5.9262 -2.0776 -4.2589 -0.9426 0.1404 6.7777 3.6382 0.9127 3.3991 0.2005 0.2303 5.7668 1.4599
+#> 380: 93.0607 -5.9258 -2.0777 -4.2595 -0.9427 0.1407 6.7836 3.6350 0.9127 3.4031 0.2004 0.2305 5.7665 1.4598
+#> 381: 93.0617 -5.9251 -2.0777 -4.2596 -0.9427 0.1410 6.7880 3.6294 0.9125 3.4030 0.2003 0.2307 5.7651 1.4601
+#> 382: 93.0631 -5.9252 -2.0777 -4.2599 -0.9428 0.1413 6.7912 3.6278 0.9123 3.4038 0.2002 0.2310 5.7649 1.4606
+#> 383: 93.0621 -5.9253 -2.0778 -4.2602 -0.9429 0.1415 6.7834 3.6279 0.9119 3.4053 0.2000 0.2312 5.7657 1.4607
+#> 384: 93.0614 -5.9254 -2.0779 -4.2604 -0.9430 0.1416 6.7853 3.6280 0.9115 3.4066 0.1999 0.2313 5.7662 1.4608
+#> 385: 93.0613 -5.9259 -2.0780 -4.2605 -0.9430 0.1418 6.7757 3.6301 0.9112 3.4066 0.1997 0.2315 5.7678 1.4609
+#> 386: 93.0614 -5.9264 -2.0780 -4.2607 -0.9431 0.1418 6.7610 3.6331 0.9110 3.4073 0.1995 0.2317 5.7696 1.4612
+#> 387: 93.0631 -5.9276 -2.0780 -4.2610 -0.9432 0.1420 6.7595 3.6397 0.9108 3.4085 0.1993 0.2318 5.7716 1.4612
+#> 388: 93.0650 -5.9282 -2.0779 -4.2613 -0.9433 0.1421 6.7552 3.6445 0.9106 3.4092 0.1992 0.2318 5.7731 1.4612
+#> 389: 93.0644 -5.9286 -2.0779 -4.2616 -0.9434 0.1422 6.7488 3.6471 0.9104 3.4098 0.1991 0.2317 5.7724 1.4614
+#> 390: 93.0653 -5.9297 -2.0778 -4.2619 -0.9435 0.1423 6.7412 3.6524 0.9101 3.4103 0.1990 0.2317 5.7722 1.4615
+#> 391: 93.0647 -5.9297 -2.0778 -4.2623 -0.9435 0.1425 6.7508 3.6524 0.9101 3.4115 0.1989 0.2317 5.7729 1.4621
+#> 392: 93.0637 -5.9293 -2.0778 -4.2624 -0.9436 0.1427 6.7572 3.6498 0.9102 3.4109 0.1988 0.2317 5.7727 1.4623
+#> 393: 93.0657 -5.9294 -2.0778 -4.2632 -0.9436 0.1429 6.7607 3.6496 0.9104 3.4148 0.1987 0.2318 5.7719 1.4621
+#> 394: 93.0689 -5.9293 -2.0779 -4.2635 -0.9438 0.1431 6.7635 3.6489 0.9108 3.4141 0.1987 0.2318 5.7724 1.4623
+#> 395: 93.0705 -5.9295 -2.0780 -4.2640 -0.9438 0.1433 6.7753 3.6500 0.9110 3.4145 0.1986 0.2319 5.7724 1.4622
+#> 396: 93.0704 -5.9296 -2.0780 -4.2648 -0.9438 0.1435 6.7793 3.6511 0.9112 3.4175 0.1985 0.2319 5.7720 1.4618
+#> 397: 93.0715 -5.9302 -2.0781 -4.2656 -0.9438 0.1437 6.7782 3.6530 0.9114 3.4206 0.1985 0.2320 5.7706 1.4617
+#> 398: 93.0719 -5.9297 -2.0781 -4.2666 -0.9438 0.1439 6.7774 3.6510 0.9120 3.4258 0.1984 0.2319 5.7709 1.4616
+#> 399: 93.0720 -5.9296 -2.0781 -4.2678 -0.9438 0.1441 6.7819 3.6526 0.9126 3.4317 0.1984 0.2319 5.7717 1.4615
+#> 400: 93.0730 -5.9296 -2.0783 -4.2691 -0.9438 0.1443 6.7786 3.6538 0.9129 3.4389 0.1983 0.2319 5.7716 1.4614
+#> 401: 93.0728 -5.9292 -2.0783 -4.2706 -0.9437 0.1445 6.7731 3.6521 0.9133 3.4478 0.1982 0.2319 5.7701 1.4615
+#> 402: 93.0732 -5.9289 -2.0784 -4.2718 -0.9438 0.1447 6.7698 3.6517 0.9137 3.4542 0.1981 0.2319 5.7689 1.4618
+#> 403: 93.0732 -5.9301 -2.0785 -4.2730 -0.9438 0.1450 6.7640 3.6576 0.9142 3.4593 0.1980 0.2320 5.7693 1.4615
+#> 404: 93.0710 -5.9316 -2.0787 -4.2740 -0.9439 0.1453 6.7544 3.6647 0.9147 3.4644 0.1979 0.2320 5.7708 1.4611
+#> 405: 93.0687 -5.9322 -2.0788 -4.2750 -0.9440 0.1454 6.7547 3.6663 0.9153 3.4693 0.1978 0.2322 5.7714 1.4608
+#> 406: 93.0673 -5.9337 -2.0789 -4.2760 -0.9440 0.1456 6.7563 3.6726 0.9163 3.4742 0.1977 0.2324 5.7718 1.4603
+#> 407: 93.0653 -5.9345 -2.0791 -4.2769 -0.9440 0.1456 6.7601 3.6756 0.9169 3.4786 0.1976 0.2327 5.7732 1.4598
+#> 408: 93.0640 -5.9357 -2.0793 -4.2779 -0.9440 0.1455 6.7547 3.6821 0.9177 3.4838 0.1974 0.2329 5.7751 1.4592
+#> 409: 93.0646 -5.9371 -2.0795 -4.2784 -0.9440 0.1456 6.7486 3.6915 0.9184 3.4863 0.1973 0.2330 5.7766 1.4588
+#> 410: 93.0639 -5.9391 -2.0797 -4.2791 -0.9441 0.1457 6.7523 3.7048 0.9192 3.4889 0.1972 0.2329 5.7770 1.4582
+#> 411: 93.0628 -5.9401 -2.0799 -4.2799 -0.9442 0.1457 6.7529 3.7113 0.9199 3.4929 0.1972 0.2329 5.7761 1.4580
+#> 412: 93.0620 -5.9402 -2.0801 -4.2808 -0.9443 0.1458 6.7502 3.7099 0.9207 3.4972 0.1971 0.2328 5.7767 1.4577
+#> 413: 93.0628 -5.9403 -2.0804 -4.2816 -0.9443 0.1461 6.7466 3.7091 0.9214 3.5007 0.1970 0.2326 5.7771 1.4572
+#> 414: 93.0627 -5.9405 -2.0807 -4.2825 -0.9443 0.1463 6.7480 3.7089 0.9221 3.5048 0.1969 0.2325 5.7774 1.4567
+#> 415: 93.0614 -5.9402 -2.0810 -4.2836 -0.9443 0.1465 6.7474 3.7066 0.9226 3.5098 0.1969 0.2323 5.7780 1.4564
+#> 416: 93.0610 -5.9408 -2.0813 -4.2848 -0.9443 0.1469 6.7544 3.7116 0.9229 3.5157 0.1968 0.2321 5.7786 1.4559
+#> 417: 93.0601 -5.9413 -2.0815 -4.2860 -0.9443 0.1471 6.7592 3.7158 0.9234 3.5206 0.1967 0.2319 5.7793 1.4556
+#> 418: 93.0606 -5.9424 -2.0817 -4.2868 -0.9444 0.1473 6.7589 3.7214 0.9238 3.5237 0.1966 0.2318 5.7787 1.4553
+#> 419: 93.0605 -5.9433 -2.0818 -4.2877 -0.9444 0.1476 6.7641 3.7253 0.9242 3.5274 0.1965 0.2316 5.7780 1.4552
+#> 420: 93.0623 -5.9427 -2.0819 -4.2886 -0.9445 0.1478 6.7593 3.7216 0.9246 3.5310 0.1965 0.2314 5.7772 1.4551
+#> 421: 93.0630 -5.9418 -2.0819 -4.2895 -0.9445 0.1480 6.7489 3.7166 0.9250 3.5337 0.1964 0.2312 5.7764 1.4552
+#> 422: 93.0626 -5.9410 -2.0820 -4.2900 -0.9445 0.1482 6.7452 3.7124 0.9253 3.5350 0.1963 0.2311 5.7758 1.4549
+#> 423: 93.0629 -5.9407 -2.0822 -4.2906 -0.9446 0.1484 6.7409 3.7095 0.9256 3.5360 0.1963 0.2309 5.7753 1.4546
+#> 424: 93.0637 -5.9404 -2.0821 -4.2912 -0.9446 0.1485 6.7387 3.7073 0.9258 3.5370 0.1962 0.2308 5.7733 1.4546
+#> 425: 93.0625 -5.9402 -2.0821 -4.2917 -0.9447 0.1486 6.7330 3.7061 0.9258 3.5381 0.1961 0.2306 5.7722 1.4548
+#> 426: 93.0624 -5.9399 -2.0820 -4.2921 -0.9447 0.1487 6.7256 3.7034 0.9259 3.5387 0.1961 0.2304 5.7719 1.4545
+#> 427: 93.0606 -5.9397 -2.0821 -4.2925 -0.9447 0.1488 6.7139 3.7010 0.9257 3.5394 0.1961 0.2301 5.7730 1.4545
+#> 428: 93.0601 -5.9394 -2.0822 -4.2929 -0.9447 0.1489 6.7062 3.6984 0.9256 3.5405 0.1961 0.2298 5.7723 1.4543
+#> 429: 93.0615 -5.9391 -2.0821 -4.2933 -0.9447 0.1490 6.7040 3.6956 0.9254 3.5412 0.1960 0.2297 5.7714 1.4544
+#> 430: 93.0654 -5.9389 -2.0820 -4.2934 -0.9448 0.1491 6.7016 3.6934 0.9253 3.5412 0.1960 0.2295 5.7710 1.4546
+#> 431: 93.0674 -5.9392 -2.0819 -4.2936 -0.9449 0.1491 6.6946 3.6935 0.9252 3.5414 0.1960 0.2294 5.7699 1.4547
+#> 432: 93.0683 -5.9401 -2.0818 -4.2938 -0.9450 0.1491 6.6895 3.6960 0.9250 3.5417 0.1961 0.2292 5.7687 1.4549
+#> 433: 93.0693 -5.9411 -2.0815 -4.2942 -0.9451 0.1491 6.6826 3.7003 0.9254 3.5433 0.1961 0.2291 5.7679 1.4549
+#> 434: 93.0720 -5.9410 -2.0813 -4.2945 -0.9452 0.1491 6.6842 3.6998 0.9258 3.5440 0.1960 0.2290 5.7662 1.4548
+#> 435: 93.0735 -5.9417 -2.0811 -4.2947 -0.9453 0.1490 6.6907 3.7029 0.9261 3.5446 0.1960 0.2290 5.7651 1.4548
+#> 436: 93.0752 -5.9430 -2.0809 -4.2949 -0.9454 0.1489 6.6939 3.7083 0.9266 3.5459 0.1959 0.2290 5.7638 1.4547
+#> 437: 93.0774 -5.9442 -2.0807 -4.2952 -0.9455 0.1487 6.7016 3.7147 0.9270 3.5474 0.1960 0.2290 5.7624 1.4550
+#> 438: 93.0795 -5.9453 -2.0805 -4.2954 -0.9456 0.1485 6.7089 3.7212 0.9275 3.5491 0.1959 0.2291 5.7614 1.4551
+#> 439: 93.0816 -5.9467 -2.0802 -4.2956 -0.9457 0.1484 6.7230 3.7291 0.9281 3.5503 0.1959 0.2293 5.7616 1.4551
+#> 440: 93.0834 -5.9475 -2.0800 -4.2957 -0.9458 0.1480 6.7306 3.7340 0.9287 3.5512 0.1960 0.2295 5.7631 1.4551
+#> 441: 93.0855 -5.9480 -2.0797 -4.2961 -0.9459 0.1478 6.7436 3.7373 0.9292 3.5534 0.1960 0.2299 5.7642 1.4553
+#> 442: 93.0885 -5.9488 -2.0793 -4.2963 -0.9460 0.1474 6.7533 3.7419 0.9297 3.5546 0.1960 0.2304 5.7630 1.4554
+#> 443: 93.0907 -5.9497 -2.0789 -4.2967 -0.9461 0.1471 6.7641 3.7469 0.9304 3.5570 0.1960 0.2308 5.7616 1.4554
+#> 444: 93.0905 -5.9504 -2.0785 -4.2972 -0.9462 0.1467 6.7570 3.7486 0.9312 3.5601 0.1960 0.2311 5.7604 1.4553
+#> 445: 93.0903 -5.9515 -2.0782 -4.2977 -0.9462 0.1462 6.7547 3.7543 0.9319 3.5635 0.1960 0.2314 5.7595 1.4550
+#> 446: 93.0902 -5.9530 -2.0778 -4.2982 -0.9462 0.1459 6.7562 3.7615 0.9325 3.5664 0.1960 0.2316 5.7580 1.4548
+#> 447: 93.0905 -5.9541 -2.0775 -4.2990 -0.9463 0.1455 6.7639 3.7668 0.9333 3.5719 0.1960 0.2318 5.7574 1.4543
+#> 448: 93.0912 -5.9555 -2.0772 -4.2999 -0.9463 0.1452 6.7671 3.7736 0.9340 3.5783 0.1960 0.2322 5.7572 1.4540
+#> 449: 93.0918 -5.9570 -2.0769 -4.3004 -0.9464 0.1448 6.7824 3.7802 0.9345 3.5809 0.1960 0.2326 5.7561 1.4537
+#> 450: 93.0901 -5.9579 -2.0766 -4.3011 -0.9464 0.1444 6.7866 3.7829 0.9351 3.5853 0.1959 0.2329 5.7551 1.4536
+#> 451: 93.0899 -5.9594 -2.0763 -4.3016 -0.9465 0.1439 6.7875 3.7896 0.9356 3.5888 0.1959 0.2332 5.7550 1.4537
+#> 452: 93.0902 -5.9603 -2.0759 -4.3023 -0.9465 0.1435 6.7953 3.7926 0.9363 3.5927 0.1958 0.2335 5.7537 1.4538
+#> 453: 93.0906 -5.9615 -2.0755 -4.3026 -0.9465 0.1430 6.7996 3.7982 0.9372 3.5950 0.1958 0.2338 5.7531 1.4539
+#> 454: 93.0909 -5.9614 -2.0751 -4.3029 -0.9465 0.1425 6.8016 3.7969 0.9381 3.5976 0.1958 0.2340 5.7532 1.4540
+#> 455: 93.0909 -5.9610 -2.0749 -4.3035 -0.9464 0.1420 6.8022 3.7940 0.9391 3.6022 0.1957 0.2342 5.7532 1.4539
+#> 456: 93.0916 -5.9600 -2.0746 -4.3045 -0.9463 0.1416 6.7942 3.7893 0.9398 3.6104 0.1957 0.2344 5.7540 1.4537
+#> 457: 93.0905 -5.9595 -2.0744 -4.3058 -0.9463 0.1411 6.7931 3.7866 0.9407 3.6210 0.1956 0.2345 5.7551 1.4534
+#> 458: 93.0905 -5.9597 -2.0742 -4.3071 -0.9462 0.1407 6.7877 3.7882 0.9416 3.6327 0.1955 0.2347 5.7566 1.4532
+#> 459: 93.0895 -5.9598 -2.0741 -4.3078 -0.9461 0.1402 6.7884 3.7889 0.9425 3.6383 0.1955 0.2349 5.7601 1.4527
+#> 460: 93.0871 -5.9602 -2.0741 -4.3086 -0.9460 0.1398 6.7889 3.7912 0.9434 3.6439 0.1954 0.2350 5.7619 1.4522
+#> 461: 93.0854 -5.9613 -2.0739 -4.3091 -0.9459 0.1393 6.7813 3.7973 0.9440 3.6481 0.1953 0.2351 5.7620 1.4520
+#> 462: 93.0838 -5.9623 -2.0737 -4.3093 -0.9458 0.1388 6.7791 3.8037 0.9445 3.6498 0.1953 0.2353 5.7616 1.4518
+#> 463: 93.0816 -5.9629 -2.0734 -4.3095 -0.9457 0.1384 6.7733 3.8070 0.9451 3.6508 0.1952 0.2355 5.7626 1.4519
+#> 464: 93.0792 -5.9631 -2.0731 -4.3095 -0.9457 0.1379 6.7697 3.8081 0.9460 3.6507 0.1951 0.2358 5.7638 1.4518
+#> 465: 93.0775 -5.9633 -2.0728 -4.3095 -0.9456 0.1374 6.7717 3.8095 0.9466 3.6506 0.1950 0.2361 5.7647 1.4519
+#> 466: 93.0774 -5.9640 -2.0725 -4.3097 -0.9455 0.1368 6.7686 3.8141 0.9473 3.6516 0.1949 0.2363 5.7662 1.4516
+#> 467: 93.0773 -5.9646 -2.0722 -4.3100 -0.9454 0.1364 6.7668 3.8172 0.9480 3.6535 0.1948 0.2366 5.7671 1.4516
+#> 468: 93.0777 -5.9653 -2.0719 -4.3106 -0.9453 0.1358 6.7648 3.8226 0.9487 3.6566 0.1947 0.2371 5.7681 1.4514
+#> 469: 93.0778 -5.9657 -2.0717 -4.3112 -0.9453 0.1353 6.7617 3.8253 0.9495 3.6588 0.1947 0.2375 5.7686 1.4510
+#> 470: 93.0769 -5.9663 -2.0715 -4.3117 -0.9452 0.1347 6.7650 3.8278 0.9503 3.6613 0.1947 0.2379 5.7688 1.4506
+#> 471: 93.0749 -5.9664 -2.0714 -4.3123 -0.9451 0.1342 6.7708 3.8280 0.9510 3.6643 0.1947 0.2383 5.7699 1.4505
+#> 472: 93.0721 -5.9668 -2.0713 -4.3127 -0.9450 0.1337 6.7756 3.8284 0.9517 3.6665 0.1947 0.2386 5.7710 1.4501
+#> 473: 93.0696 -5.9670 -2.0713 -4.3133 -0.9449 0.1333 6.7784 3.8280 0.9522 3.6698 0.1947 0.2388 5.7716 1.4498
+#> 474: 93.0674 -5.9673 -2.0714 -4.3138 -0.9448 0.1329 6.7761 3.8281 0.9527 3.6731 0.1947 0.2390 5.7729 1.4496
+#> 475: 93.0655 -5.9679 -2.0714 -4.3143 -0.9447 0.1324 6.7779 3.8302 0.9531 3.6762 0.1947 0.2391 5.7743 1.4493
+#> 476: 93.0643 -5.9682 -2.0713 -4.3144 -0.9447 0.1321 6.7776 3.8314 0.9536 3.6768 0.1946 0.2391 5.7762 1.4492
+#> 477: 93.0631 -5.9684 -2.0714 -4.3146 -0.9446 0.1317 6.7725 3.8326 0.9540 3.6787 0.1945 0.2392 5.7768 1.4492
+#> 478: 93.0630 -5.9693 -2.0715 -4.3148 -0.9447 0.1314 6.7626 3.8365 0.9543 3.6788 0.1944 0.2395 5.7785 1.4492
+#> 479: 93.0634 -5.9710 -2.0714 -4.3148 -0.9447 0.1310 6.7499 3.8462 0.9547 3.6778 0.1943 0.2399 5.7798 1.4490
+#> 480: 93.0651 -5.9732 -2.0715 -4.3147 -0.9447 0.1307 6.7463 3.8616 0.9548 3.6770 0.1943 0.2403 5.7810 1.4488
+#> 481: 93.0664 -5.9747 -2.0715 -4.3149 -0.9447 0.1304 6.7442 3.8722 0.9550 3.6780 0.1941 0.2409 5.7811 1.4487
+#> 482: 93.0647 -5.9762 -2.0714 -4.3151 -0.9447 0.1300 6.7389 3.8834 0.9554 3.6784 0.1941 0.2414 5.7816 1.4484
+#> 483: 93.0628 -5.9778 -2.0714 -4.3153 -0.9447 0.1295 6.7352 3.8943 0.9557 3.6783 0.1940 0.2419 5.7820 1.4483
+#> 484: 93.0614 -5.9787 -2.0715 -4.3153 -0.9447 0.1291 6.7314 3.8999 0.9559 3.6774 0.1939 0.2424 5.7819 1.4481
+#> 485: 93.0593 -5.9789 -2.0715 -4.3153 -0.9447 0.1288 6.7293 3.9007 0.9561 3.6765 0.1938 0.2430 5.7815 1.4480
+#> 486: 93.0575 -5.9793 -2.0716 -4.3152 -0.9447 0.1284 6.7331 3.9021 0.9563 3.6753 0.1938 0.2434 5.7806 1.4480
+#> 487: 93.0555 -5.9796 -2.0716 -4.3152 -0.9447 0.1281 6.7342 3.9036 0.9566 3.6741 0.1937 0.2439 5.7805 1.4479
+#> 488: 93.0545 -5.9795 -2.0716 -4.3152 -0.9447 0.1277 6.7365 3.9024 0.9569 3.6729 0.1937 0.2444 5.7795 1.4480
+#> 489: 93.0550 -5.9800 -2.0716 -4.3152 -0.9447 0.1274 6.7336 3.9046 0.9571 3.6719 0.1937 0.2448 5.7778 1.4481
+#> 490: 93.0571 -5.9793 -2.0715 -4.3152 -0.9447 0.1272 6.7331 3.9009 0.9573 3.6704 0.1936 0.2450 5.7767 1.4484
+#> 491: 93.0584 -5.9787 -2.0714 -4.3151 -0.9447 0.1270 6.7280 3.8980 0.9575 3.6688 0.1936 0.2452 5.7764 1.4487
+#> 492: 93.0589 -5.9786 -2.0714 -4.3150 -0.9447 0.1267 6.7264 3.8971 0.9578 3.6675 0.1936 0.2455 5.7759 1.4489
+#> 493: 93.0593 -5.9790 -2.0711 -4.3149 -0.9447 0.1265 6.7273 3.8982 0.9584 3.6660 0.1935 0.2456 5.7759 1.4490
+#> 494: 93.0594 -5.9805 -2.0710 -4.3149 -0.9448 0.1263 6.7291 3.9066 0.9590 3.6650 0.1935 0.2457 5.7758 1.4489
+#> 495: 93.0596 -5.9816 -2.0709 -4.3148 -0.9448 0.1261 6.7281 3.9123 0.9593 3.6639 0.1936 0.2459 5.7745 1.4490
+#> 496: 93.0590 -5.9829 -2.0707 -4.3148 -0.9448 0.1259 6.7319 3.9227 0.9597 3.6628 0.1936 0.2461 5.7740 1.4491
+#> 497: 93.0580 -5.9842 -2.0706 -4.3148 -0.9448 0.1257 6.7388 3.9326 0.9600 3.6623 0.1936 0.2463 5.7732 1.4492
+#> 498: 93.0578 -5.9848 -2.0705 -4.3148 -0.9448 0.1255 6.7447 3.9368 0.9605 3.6618 0.1936 0.2464 5.7726 1.4494
+#> 499: 93.0568 -5.9843 -2.0704 -4.3147 -0.9447 0.1253 6.7475 3.9341 0.9609 3.6612 0.1937 0.2467 5.7718 1.4495
+#> 500: 93.0563 -5.9831 -2.0703 -4.3147 -0.9447 0.1251 6.7500 3.9292 0.9614 3.6607 0.1937 0.2469 5.7712 1.4496
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
+#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 92.2740 -5.2361 0.2113 1.9393 -2.0029 2.8805 1.6298 0.7279 0.7192 0.4382 6.7264 0.4769 7.2363 0.6178
-#> 2: 93.1532 -5.3060 0.0602 2.0735 -2.0177 2.7365 1.5483 0.6915 0.8577 0.4163 7.5229 0.0003 8.5494 0.0006
-#> 3: 9.3232e+01 -5.5491e+00 5.1555e-02 2.4627e+00 -1.4981e+00 2.5997e+00 1.4709e+00 6.5697e-01 8.1480e-01 3.9549e-01 4.6581e+00 4.3492e-05 5.3112e+00 1.7818e-04
-#> 4: 9.3109e+01 -5.6749e+00 3.7928e-02 2.4274e+00 -1.3355e+00 2.4697e+00 1.3973e+00 6.2412e-01 7.7406e-01 3.7572e-01 3.5252e+00 9.5643e-05 4.0990e+00 4.6584e-05
-#> 5: 9.3327e+01 -5.8341e+00 -1.6798e-02 2.4024e+00 -1.2129e+00 2.3462e+00 1.3274e+00 5.9292e-01 7.3536e-01 3.5693e-01 3.3259e+00 1.6901e-05 3.5218e+00 4.0075e-05
-#> 6: 9.3449e+01 -6.0745e+00 -6.1031e-02 2.3458e+00 -1.2034e+00 2.2289e+00 1.8700e+00 5.6327e-01 6.9859e-01 3.3908e-01 2.9533e+00 6.5587e-07 3.1056e+00 2.1346e-02
-#> 7: 93.2519 -6.0564 -0.0590 2.3588 -1.1293 2.1174 1.8910 0.5351 0.6637 0.3221 2.8211 0.0082 2.8507 0.0251
-#> 8: 93.0343 -5.9362 -0.0851 2.2949 -1.0760 2.0116 1.7964 0.5084 0.6305 0.3060 2.5340 0.0181 2.6368 0.0243
-#> 9: 93.1444 -6.1910 -0.1199 2.2709 -1.1077 1.9110 1.8664 0.4829 0.5990 0.2907 2.3768 0.0191 2.3601 0.0284
-#> 10: 93.2748 -6.4970 -0.1598 2.2235 -1.1034 2.1024 3.1968 0.4588 0.5690 0.2762 2.1991 0.0255 2.2790 0.0316
-#> 11: 93.4141 -6.4463 -0.1698 2.1876 -1.0890 1.9973 3.0370 0.4358 0.5406 0.2624 2.1469 0.0266 2.1681 0.0325
-#> 12: 93.4935 -6.5467 -0.1715 2.1666 -1.0952 1.8974 3.7848 0.4141 0.5135 0.2493 1.9137 0.0292 2.0701 0.0331
-#> 13: 93.6730 -6.4173 -0.1752 2.1387 -1.0753 1.8026 3.7278 0.3934 0.4879 0.2368 1.9084 0.0272 2.0289 0.0369
-#> 14: 93.5721 -6.2146 -0.1738 2.1854 -1.0740 2.0902 3.5415 0.3737 0.4635 0.2250 1.9861 0.0239 2.0052 0.0347
-#> 15: 93.6638 -6.3103 -0.1693 2.1828 -1.0327 2.0702 3.3644 0.3720 0.4403 0.2137 1.8947 0.0247 1.9865 0.0375
-#> 16: 93.4156 -6.0957 -0.1666 2.1755 -1.0737 2.6391 3.1962 0.3691 0.4183 0.2030 1.9089 0.0241 2.0159 0.0360
-#> 17: 93.4257 -6.1494 -0.1705 2.1664 -1.0589 2.5072 3.0714 0.3697 0.3974 0.1929 1.8253 0.0268 2.0391 0.0301
-#> 18: 93.5593 -6.1696 -0.1780 2.1670 -1.0129 2.3818 3.7604 0.3725 0.3775 0.1832 1.8529 0.0304 1.8784 0.0298
-#> 19: 93.5027 -6.2960 -0.1791 2.1543 -1.0325 2.6052 4.5501 0.3942 0.3586 0.1741 1.8082 0.0328 1.8654 0.0335
-#> 20: 93.4480 -6.4389 -0.1776 2.1772 -1.0485 2.6607 5.1881 0.3894 0.3554 0.1654 1.8032 0.0322 1.9018 0.0312
-#> 21: 93.6411 -6.2893 -0.1750 2.1759 -1.0350 2.5276 4.9287 0.3817 0.3386 0.1605 1.8533 0.0264 1.9317 0.0301
-#> 22: 93.9320 -6.1469 -0.1750 2.1910 -1.0527 2.4013 4.6823 0.3720 0.3642 0.1525 1.8949 0.0273 1.8977 0.0310
-#> 23: 93.6074 -6.3097 -0.1502 2.2111 -1.0155 2.2812 4.6643 0.3832 0.4236 0.1449 1.7075 0.0340 1.7367 0.0337
-#> 24: 93.7425 -6.4598 -0.1446 2.2249 -1.0011 2.7056 6.0597 0.3949 0.4075 0.1479 1.7180 0.0360 1.7786 0.0302
-#> 25: 94.1822 -6.3674 -0.1496 2.1917 -1.0011 3.4724 5.7567 0.3897 0.4355 0.1465 1.6977 0.0356 1.8373 0.0328
-#> 26: 94.0446 -6.3235 -0.1496 2.2004 -1.0414 3.5912 5.4688 0.3897 0.4438 0.1405 1.6765 0.0344 1.8262 0.0355
-#> 27: 94.4454 -6.2148 -0.1370 2.2360 -1.0220 4.6238 5.1954 0.3702 0.4216 0.1335 1.7209 0.0349 1.7702 0.0336
-#> 28: 94.1837 -6.1301 -0.1376 2.2253 -1.0261 4.3926 4.9356 0.3644 0.4005 0.1345 1.6968 0.0290 1.8540 0.0316
-#> 29: 94.0681 -5.8726 -0.1440 2.2237 -1.0400 4.1730 4.6889 0.3750 0.4055 0.1464 1.7084 0.0329 1.7379 0.0407
-#> 30: 94.5866 -5.9141 -0.1416 2.2045 -1.0350 3.9896 4.4544 0.3770 0.3852 0.1769 1.6009 0.0326 1.8718 0.0350
-#> 31: 94.1640 -6.0370 -0.1382 2.2140 -1.0189 5.4942 4.2317 0.3759 0.3809 0.1680 1.5887 0.0386 1.8918 0.0286
-#> 32: 94.5952 -5.8349 -0.1373 2.2374 -1.0283 5.2195 4.0201 0.3745 0.3835 0.1636 1.6451 0.0375 1.7459 0.0382
-#> 33: 95.0936 -5.8145 -0.1356 2.2325 -1.0037 4.9634 3.8191 0.3614 0.3644 0.1677 1.6313 0.0414 1.6809 0.0399
-#> 34: 94.7033 -5.8916 -0.1208 2.2687 -0.9896 5.4935 3.6281 0.3741 0.3536 0.1701 1.5923 0.0376 1.2962 0.0644
-#> 35: 94.8127 -5.9839 -0.1122 2.2615 -0.9983 5.2188 3.7348 0.3817 0.3661 0.1712 1.5848 0.0313 1.1651 0.0752
-#> 36: 94.6798 -5.8938 -0.1203 2.2441 -1.0009 4.9578 3.5480 0.3835 0.3478 0.1708 1.5525 0.0313 1.1527 0.0712
-#> 37: 93.9759 -5.8017 -0.1274 2.2346 -1.0021 4.7100 3.3706 0.3868 0.3350 0.1622 1.6278 0.0256 1.7263 0.0372
-#> 38: 94.2013 -5.8617 -0.1206 2.2570 -1.0125 4.4745 3.2021 0.3754 0.3520 0.1574 1.5396 0.0290 1.0653 0.0746
-#> 39: 94.1314 -5.7645 -0.1261 2.2381 -1.0361 4.2507 3.0420 0.3804 0.3521 0.1543 1.6280 0.0267 1.1461 0.0755
-#> 40: 93.7934 -5.8654 -0.1206 2.2417 -1.0503 4.0382 2.8899 0.3624 0.3413 0.1747 1.6231 0.0239 1.5698 0.0513
-#> 41: 93.8756 -6.0150 -0.1171 2.2581 -1.0313 3.8363 3.3629 0.3809 0.3369 0.1944 1.6461 0.0217 1.7762 0.0345
-#> 42: 94.0644 -5.9723 -0.1136 2.2769 -1.0295 3.6445 3.2171 0.3702 0.3394 0.1920 1.5035 0.0416 1.5148 0.0475
-#> 43: 93.7394 -5.9927 -0.1233 2.2650 -1.0374 3.4622 3.0562 0.3735 0.3370 0.1824 1.6022 0.0379 1.5080 0.0468
-#> 44: 93.5428 -5.9784 -0.1187 2.2780 -1.0279 3.2891 2.9495 0.3732 0.3289 0.1742 1.5456 0.0471 1.4361 0.0517
-#> 45: 93.2885 -5.9836 -0.1273 2.2650 -1.0100 3.1247 3.2884 0.3768 0.3719 0.1655 1.6579 0.0336 1.4031 0.0585
-#> 46: 93.4080 -5.9261 -0.1371 2.2513 -1.0159 3.4180 3.1630 0.3709 0.3762 0.1711 1.7365 0.0269 1.4612 0.0530
-#> 47: 93.4548 -5.8101 -0.1372 2.2650 -1.0058 3.2471 3.0049 0.3703 0.3921 0.1797 1.7161 0.0300 1.4813 0.0524
-#> 48: 93.1829 -5.6877 -0.1391 2.2594 -1.0035 3.0848 2.8546 0.3690 0.3901 0.1707 1.7558 0.0292 1.5856 0.0487
-#> 49: 93.1860 -5.8153 -0.1349 2.2793 -0.9905 2.9305 2.7119 0.3619 0.3877 0.1690 1.7255 0.0299 1.6143 0.0465
-#> 50: 93.5597 -5.7551 -0.1334 2.2669 -0.9808 2.7840 2.5763 0.3652 0.3795 0.1716 1.6690 0.0290 1.4895 0.0536
-#> 51: 93.5952 -5.8089 -0.1358 2.2626 -1.0100 2.6448 2.4475 0.3640 0.4246 0.1630 1.5892 0.0344 1.3958 0.0604
-#> 52: 93.3111 -5.9181 -0.1323 2.2489 -0.9909 2.5126 2.8739 0.3695 0.4337 0.1549 1.5200 0.0329 1.2246 0.0685
-#> 53: 93.4921 -6.0837 -0.1307 2.2513 -1.0031 2.3869 3.6029 0.3678 0.4363 0.1682 1.4683 0.0336 1.2917 0.0665
-#> 54: 93.4808 -6.2019 -0.1488 2.2068 -1.0207 2.2676 4.1833 0.3952 0.4145 0.1598 1.6478 0.0325 1.2418 0.0659
-#> 55: 93.5453 -6.2747 -0.1411 2.2297 -1.0122 2.1542 4.5107 0.3941 0.4044 0.1556 1.5685 0.0358 1.3236 0.0654
-#> 56: 94.0212 -6.2713 -0.1355 2.2228 -1.0205 2.0465 5.1718 0.3901 0.4101 0.1516 1.5568 0.0341 1.1952 0.0736
-#> 57: 93.7155 -6.2511 -0.1574 2.1899 -1.0374 1.9442 4.9132 0.3991 0.3974 0.1442 1.5528 0.0364 1.5497 0.0485
-#> 58: 93.9064 -6.2021 -0.1543 2.1935 -1.0277 1.8470 4.6676 0.3935 0.3944 0.1458 1.5590 0.0354 1.3512 0.0613
-#> 59: 93.9059 -6.3971 -0.1550 2.1899 -1.0124 1.7546 5.8885 0.3925 0.3943 0.1446 1.5641 0.0373 1.4293 0.0550
-#> 60: 93.8600 -6.2474 -0.1552 2.1978 -0.9930 1.7661 5.5941 0.3905 0.4078 0.1532 1.5235 0.0364 1.5442 0.0477
-#> 61: 93.8936 -6.3077 -0.1568 2.2022 -1.0084 1.7122 5.3507 0.3946 0.4146 0.1455 1.5154 0.0342 1.3664 0.0587
-#> 62: 93.6133 -6.1446 -0.1473 2.2277 -1.0195 1.6266 5.0832 0.3794 0.4254 0.1383 1.5586 0.0330 1.1663 0.0705
-#> 63: 93.5549 -6.3005 -0.1437 2.2302 -1.0096 1.5452 5.0969 0.3651 0.4262 0.1349 1.5730 0.0323 1.2501 0.0668
-#> 64: 93.3212 -6.1190 -0.1428 2.2309 -1.0005 1.4826 4.8421 0.3661 0.4181 0.1443 1.6657 0.0259 1.3409 0.0627
-#> 65: 93.2534 -5.9614 -0.1492 2.2310 -0.9865 1.4084 4.6000 0.3735 0.4186 0.1695 1.6883 0.0235 1.4446 0.0563
-#> 66: 93.3429 -5.9786 -0.1401 2.2198 -0.9934 1.3380 4.3700 0.3807 0.4094 0.1610 1.6697 0.0270 1.1164 0.0778
-#> 67: 93.5657 -6.2158 -0.1405 2.2326 -0.9891 1.2711 4.4653 0.3827 0.4063 0.1530 1.5851 0.0316 1.3581 0.0590
-#> 68: 93.4898 -5.9763 -0.1375 2.2431 -0.9837 1.2076 4.2420 0.3771 0.4127 0.1453 1.6134 0.0325 1.1459 0.0744
-#> 69: 93.4995 -6.1375 -0.1412 2.2423 -1.0003 1.3178 4.3907 0.3746 0.4202 0.1403 1.6223 0.0304 1.3354 0.0608
-#> 70: 93.4369 -6.1690 -0.1395 2.2472 -1.0047 1.6239 4.5654 0.3793 0.4087 0.1400 1.6317 0.0349 1.4812 0.0494
-#> 71: 93.4041 -6.3637 -0.1489 2.2348 -1.0125 1.5427 5.3897 0.3603 0.3883 0.1330 1.5954 0.0303 1.3502 0.0612
-#> 72: 93.1755 -6.4067 -0.1441 2.2492 -0.9859 1.4656 6.3554 0.3423 0.3688 0.1388 1.6135 0.0287 1.6402 0.0435
-#> 73: 93.0023 -6.7319 -0.1526 2.2550 -0.9800 1.3923 7.6438 0.3341 0.3504 0.1462 1.5491 0.0312 1.3997 0.0554
-#> 74: 92.8952 -6.7189 -0.1530 2.2393 -0.9936 1.5478 7.2616 0.3344 0.3329 0.1503 1.5626 0.0326 1.3340 0.0634
-#> 75: 93.0812 -6.8015 -0.1546 2.2265 -0.9751 1.4704 8.9537 0.3501 0.3162 0.1438 1.6019 0.0268 1.1663 0.0715
-#> 76: 93.1080 -6.1728 -0.1515 2.2259 -1.0010 1.3969 8.5060 0.3407 0.3015 0.1398 1.6484 0.0279 1.3118 0.0637
-#> 77: 92.9248 -6.3432 -0.1573 2.2221 -0.9819 1.4456 8.0807 0.3506 0.3002 0.1442 1.5947 0.0294 1.6368 0.0407
-#> 78: 93.0194 -6.1448 -0.1611 2.2228 -0.9831 1.3733 7.6767 0.3487 0.3046 0.1369 1.6471 0.0254 1.4261 0.0529
-#> 79: 92.9378 -6.6970 -0.1593 2.2313 -0.9910 1.3046 10.0158 0.3460 0.2999 0.1386 1.6108 0.0267 1.5818 0.0420
-#> 80: 93.0293 -6.3275 -0.1579 2.2290 -0.9753 1.3191 9.5150 0.3543 0.2960 0.1490 1.6570 0.0259 1.5435 0.0431
-#> 81: 93.1417 -6.2258 -0.1607 2.2285 -0.9399 1.4131 9.0393 0.3514 0.3020 0.1415 1.6990 0.0236 1.6875 0.0364
-#> 82: 92.9115 -6.1764 -0.1555 2.2204 -0.9471 1.3424 8.5873 0.3502 0.2954 0.1540 1.6780 0.0216 1.2280 0.0687
-#> 83: 93.0528 -6.3505 -0.1559 2.2391 -0.9651 1.2753 8.1579 0.3499 0.2903 0.1706 1.6924 0.0242 1.6807 0.0465
-#> 84: 93.0032 -6.2300 -0.1596 2.2300 -0.9232 1.2115 7.9391 0.3470 0.2995 0.1858 1.7153 0.0259 1.7160 0.0406
-#> 85: 93.0518 -6.3704 -0.1434 2.2696 -0.9330 1.1510 8.3071 0.3504 0.2916 0.1765 1.7072 0.0275 1.5494 0.0490
-#> 86: 93.1344 -6.3566 -0.1424 2.2595 -0.9512 1.0934 9.2972 0.3520 0.2869 0.1677 1.6609 0.0253 1.5022 0.0508
-#> 87: 93.2468 -6.3860 -0.1449 2.2505 -0.9601 1.0387 8.8323 0.3474 0.3046 0.1593 1.6326 0.0262 1.3048 0.0626
-#> 88: 93.2286 -6.3886 -0.1466 2.2452 -0.9870 0.9868 8.3907 0.3474 0.2894 0.1513 1.6554 0.0245 1.6330 0.0376
-#> 89: 93.2892 -6.0277 -0.1469 2.2403 -0.9694 0.9375 7.9712 0.3451 0.2904 0.1438 1.6795 0.0251 1.6691 0.0365
-#> 90: 93.1766 -6.1076 -0.1460 2.2502 -0.9729 0.8906 7.5726 0.3458 0.2932 0.1481 1.6182 0.0331 1.5854 0.0401
-#> 91: 93.3300 -6.0932 -0.1559 2.2356 -0.9551 0.8461 7.1940 0.3771 0.2883 0.1512 1.6728 0.0272 1.6098 0.0401
-#> 92: 93.2470 -6.4839 -0.1592 2.2265 -1.0016 0.8038 6.8343 0.3813 0.2923 0.1597 1.7017 0.0300 1.6084 0.0423
-#> 93: 93.2272 -6.2819 -0.1612 2.2356 -1.0073 0.7636 6.4926 0.3849 0.2816 0.1722 1.5422 0.0420 1.4772 0.0493
-#> 94: 93.1441 -6.1805 -0.1571 2.2274 -1.0106 0.7254 6.1680 0.3878 0.2811 0.1636 1.5998 0.0403 1.4386 0.0535
-#> 95: 92.7747 -6.2274 -0.1709 2.2191 -1.0042 0.6891 5.8596 0.3909 0.2905 0.1591 1.7184 0.0282 1.6086 0.0519
-#> 96: 92.9830 -6.3291 -0.1603 2.2297 -1.0053 0.6547 5.5666 0.3774 0.2850 0.1512 1.7427 0.0284 1.7548 0.0384
-#> 97: 92.9302 -6.3943 -0.1608 2.2211 -0.9643 0.6219 5.2882 0.3817 0.2828 0.1589 1.7080 0.0295 1.7102 0.0398
-#> 98: 92.7704 -6.3554 -0.1679 2.1894 -0.9736 0.5908 5.4196 0.3864 0.2813 0.1560 1.7234 0.0240 1.2269 0.0685
-#> 99: 92.7596 -6.2138 -0.1687 2.2088 -0.9744 0.5613 5.1486 0.3939 0.2983 0.1482 1.6732 0.0250 1.5718 0.0497
-#> 100: 92.6608 -6.2662 -0.1687 2.2180 -1.0107 0.5332 5.1471 0.3939 0.2927 0.1408 1.8434 0.0232 1.7316 0.0413
-#> 101: 92.7024 -6.1288 -0.1643 2.2096 -1.0032 0.5066 4.8898 0.3934 0.2807 0.1349 1.7055 0.0253 1.5883 0.0439
-#> 102: 92.8885 -6.3175 -0.1697 2.2208 -0.9967 0.4812 4.9699 0.3888 0.2912 0.1371 1.7311 0.0284 1.6455 0.0402
-#> 103: 92.9487 -6.2493 -0.1677 2.1861 -0.9874 0.4572 4.9605 0.3907 0.2844 0.1626 1.6898 0.0279 1.6252 0.0409
-#> 104: 92.9633 -6.2534 -0.1731 2.1797 -0.9790 0.4343 4.8675 0.4015 0.2784 0.1758 1.6516 0.0268 1.6901 0.0360
-#> 105: 93.0513 -6.0656 -0.1748 2.1802 -0.9876 0.4126 4.6241 0.4041 0.2801 0.1670 1.6863 0.0269 1.6208 0.0366
-#> 106: 93.0600 -6.2162 -0.1860 2.1783 -0.9702 0.4570 4.5504 0.4451 0.2761 0.1586 1.6859 0.0274 1.5273 0.0437
-#> 107: 93.1856 -6.1826 -0.1801 2.1796 -0.9813 0.4341 4.7286 0.4517 0.2807 0.1575 1.6268 0.0341 1.2548 0.0630
-#> 108: 93.2401 -6.2943 -0.1783 2.1808 -0.9806 0.4124 5.3114 0.4502 0.2786 0.1496 1.6676 0.0291 1.4627 0.0484
-#> 109: 93.0988 -6.1669 -0.1655 2.2018 -0.9682 0.4036 5.0458 0.4302 0.3195 0.1435 1.6524 0.0295 1.5759 0.0447
-#> 110: 93.2129 -6.3104 -0.1748 2.1876 -0.9837 0.4825 5.6408 0.4430 0.3306 0.1595 1.6068 0.0326 1.6295 0.0388
-#> 111: 93.1292 -5.9096 -0.1740 2.1932 -0.9674 0.5262 5.3587 0.4444 0.3233 0.1646 1.5777 0.0334 1.6590 0.0374
-#> 112: 93.2723 -5.8153 -0.1706 2.1920 -0.9761 0.5109 5.0908 0.4486 0.3180 0.1634 1.6128 0.0321 1.6551 0.0396
-#> 113: 93.3171 -6.0458 -0.1666 2.1879 -0.9740 0.5530 4.8362 0.4508 0.3303 0.1607 1.5862 0.0325 1.2705 0.0643
-#> 114: 93.1717 -5.9615 -0.1655 2.1638 -0.9773 0.5254 4.5944 0.4472 0.3283 0.1657 1.6307 0.0287 1.2995 0.0677
-#> 115: 93.1917 -6.0856 -0.1592 2.1576 -1.0269 0.4991 4.3647 0.4349 0.3464 0.1574 1.6430 0.0354 1.2812 0.0714
-#> 116: 93.1287 -5.9635 -0.1609 2.1640 -0.9985 0.4741 4.1465 0.4237 0.3408 0.1495 1.6910 0.0269 1.2338 0.0738
-#> 117: 93.1184 -5.8768 -0.1603 2.1842 -0.9557 0.4504 3.9392 0.4211 0.3293 0.1420 1.6447 0.0257 1.2680 0.0705
-#> 118: 93.2207 -5.7436 -0.1654 2.1709 -0.9816 0.4279 3.7422 0.4158 0.3298 0.1349 1.6860 0.0238 1.1436 0.0780
-#> 119: 93.3064 -5.8397 -0.1713 2.1722 -1.0093 0.4065 3.5551 0.4100 0.3429 0.1384 1.6612 0.0262 1.6491 0.0458
-#> 120: 93.2749 -5.8221 -0.1737 2.1643 -1.0166 0.3862 3.3773 0.4044 0.3305 0.1527 1.6516 0.0232 1.7832 0.0410
-#> 121: 93.1620 -5.9756 -0.1579 2.2018 -1.0007 0.3818 3.2992 0.3841 0.3433 0.1620 1.6648 0.0251 1.3408 0.0665
-#> 122: 93.2070 -6.0164 -0.1540 2.2154 -1.0196 0.4217 3.5598 0.3649 0.3436 0.1539 1.6757 0.0287 1.3019 0.0652
-#> 123: 93.1588 -5.7424 -0.1581 2.2142 -0.9985 0.5270 3.3818 0.3491 0.3584 0.1655 1.6321 0.0237 1.3494 0.0644
-#> 124: 93.1496 -5.6257 -0.1463 2.2264 -0.9767 0.5914 3.2127 0.3347 0.3738 0.1573 1.6553 0.0226 1.5964 0.0544
-#> 125: 93.0224 -5.8536 -0.1742 2.1859 -0.9939 0.6381 3.0521 0.3840 0.3692 0.1664 1.6009 0.0246 1.4169 0.0652
-#> 126: 93.0788 -5.6973 -0.1778 2.1772 -0.9574 0.6062 2.8995 0.3710 0.3630 0.1839 1.5256 0.0312 1.5566 0.0518
-#> 127: 93.1613 -5.5833 -0.1729 2.1806 -0.9588 0.5759 2.7545 0.3532 0.3464 0.1878 1.5708 0.0307 1.6405 0.0476
-#> 128: 93.2043 -5.6742 -0.1746 2.1919 -0.9814 0.7099 2.6168 0.3569 0.3422 0.1848 1.6236 0.0312 1.5066 0.0517
-#> 129: 93.1963 -5.7026 -0.1770 2.1853 -0.9814 0.6744 2.4859 0.3544 0.3390 0.1774 1.6150 0.0293 1.5712 0.0479
-#> 130: 93.1669 -5.7260 -0.1826 2.1565 -0.9959 0.6407 2.3616 0.3750 0.3249 0.1685 1.6347 0.0215 1.5556 0.0535
-#> 131: 93.0792 -5.7201 -0.1971 2.1339 -1.0057 0.7376 2.2436 0.3901 0.3086 0.1616 1.7653 0.0206 1.6640 0.0458
-#> 132: 92.8580 -5.8266 -0.1877 2.1512 -0.9940 0.7008 2.3272 0.3895 0.3161 0.1863 1.6050 0.0231 1.5123 0.0558
-#> 133: 92.8479 -5.8397 -0.1834 2.1637 -0.9815 0.7195 2.4732 0.3875 0.3060 0.1877 1.6197 0.0217 1.4131 0.0617
-#> 134: 92.9218 -5.8317 -0.1903 2.1709 -0.9903 0.6835 2.5070 0.3808 0.3147 0.1857 1.7298 0.0225 1.5493 0.0521
-#> 135: 92.7533 -5.7287 -0.1909 2.1670 -0.9674 0.6493 2.3817 0.3792 0.3156 0.1981 1.7074 0.0222 1.2776 0.0718
-#> 136: 92.7255 -5.9071 -0.1787 2.1826 -0.9826 0.6169 2.8147 0.3603 0.3172 0.1882 1.6242 0.0288 1.2313 0.0682
-#> 137: 92.7882 -5.9574 -0.1847 2.1549 -0.9848 0.5860 3.0538 0.3651 0.3206 0.1787 1.5640 0.0277 1.1609 0.0716
-#> 138: 92.8155 -5.9445 -0.1719 2.1750 -0.9838 0.5567 3.3525 0.3568 0.3390 0.1698 1.5507 0.0259 1.0634 0.0816
-#> 139: 92.9393 -6.0638 -0.1726 2.1840 -0.9888 0.5289 4.1627 0.3562 0.3453 0.1613 1.5792 0.0259 1.5189 0.0533
-#> 140: 93.0330 -6.1823 -0.1726 2.1984 -0.9850 0.5024 4.3153 0.3562 0.3506 0.1533 1.6467 0.0248 1.5734 0.0459
-#> 141: 93.0651 -6.1847 -0.1702 2.2183 -0.9749 0.4773 4.1656 0.3604 0.3626 0.1527 1.5887 0.0272 1.5613 0.0433
-#> 142: 93.0350 -5.9581 -0.1641 2.2133 -0.9707 0.4535 3.9574 0.3642 0.3541 0.1662 1.5904 0.0246 1.4665 0.0556
-#> 143: 92.9215 -5.7798 -0.1642 2.2269 -0.9665 0.5015 3.7595 0.3665 0.3626 0.1667 1.6019 0.0275 1.3379 0.0563
-#> 144: 93.0132 -5.6752 -0.1629 2.2273 -0.9468 0.4764 3.5715 0.3648 0.3555 0.1648 1.5218 0.0320 1.1736 0.0695
-#> 145: 92.9596 -5.8104 -0.1449 2.2498 -0.9730 0.4526 3.3929 0.3465 0.3524 0.1670 1.5918 0.0284 1.3067 0.0630
-#> 146: 92.7925 -5.7223 -0.1458 2.2463 -0.9569 0.5591 3.2233 0.3443 0.3492 0.1587 1.6175 0.0260 1.0691 0.0729
-#> 147: 92.8399 -5.8322 -0.1478 2.2485 -0.9474 0.5312 3.2015 0.3422 0.3536 0.1507 1.6257 0.0255 1.2184 0.0622
-#> 148: 92.8390 -5.9554 -0.1498 2.2490 -0.9550 0.5046 3.6305 0.3387 0.3597 0.1615 1.5994 0.0263 1.2274 0.0638
-#> 149: 92.8158 -5.9697 -0.1511 2.2337 -0.9812 0.4794 3.8244 0.3386 0.3894 0.1559 1.5723 0.0255 1.0661 0.0760
-#> 150: 92.8379 -6.0841 -0.1532 2.2323 -0.9832 0.4554 4.3416 0.3340 0.3840 0.1575 1.5375 0.0272 1.1589 0.0677
-#> 151: 92.6741 -6.3268 -0.1572 2.2252 -0.9782 0.4327 5.9395 0.3389 0.3859 0.1584 1.5384 0.0252 1.2809 0.0638
-#> 152: 92.7165 -6.3594 -0.1527 2.2233 -1.0007 0.4210 5.8433 0.3384 0.3915 0.1324 1.5861 0.0254 1.0728 0.0756
-#> 153: 92.6823 -6.2114 -0.1640 2.2160 -0.9861 0.5285 5.4117 0.3473 0.3878 0.1376 1.6150 0.0255 1.2105 0.0659
-#> 154: 92.4787 -6.1829 -0.1622 2.2055 -0.9571 0.5031 5.7087 0.3490 0.3748 0.1345 1.5749 0.0250 1.0579 0.0741
-#> 155: 92.4780 -6.4925 -0.1675 2.2190 -0.9301 0.4020 7.4764 0.3587 0.3785 0.1287 1.5959 0.0258 1.1342 0.0709
-#> 156: 92.5151 -6.2825 -0.1673 2.2194 -0.9174 0.3603 5.6463 0.3589 0.3848 0.1202 1.5413 0.0301 1.1866 0.0674
-#> 157: 92.5140 -6.0058 -0.1644 2.2312 -0.9298 0.3857 4.2481 0.3610 0.3706 0.1281 1.5944 0.0292 1.2712 0.0631
-#> 158: 92.5669 -5.8692 -0.1673 2.2493 -0.9413 0.4751 3.7632 0.3600 0.3572 0.1383 1.6202 0.0323 1.4797 0.0499
-#> 159: 92.4844 -6.0078 -0.1540 2.2464 -0.9423 0.4626 4.6774 0.3587 0.3603 0.1450 1.6404 0.0280 1.3577 0.0587
-#> 160: 92.5182 -6.1231 -0.1504 2.2518 -0.9274 0.4153 5.0466 0.3616 0.3633 0.1373 1.5891 0.0297 1.2392 0.0653
-#> 161: 92.5665 -5.9062 -0.1569 2.2563 -0.9412 0.3989 4.3594 0.3541 0.3719 0.1433 1.6242 0.0314 1.2822 0.0627
-#> 162: 92.5749 -6.0936 -0.1507 2.2752 -0.9474 0.3140 4.4065 0.3438 0.3921 0.1320 1.5013 0.0378 1.1647 0.0662
-#> 163: 92.6248 -6.1392 -0.1565 2.2499 -0.9499 0.2129 4.6022 0.3512 0.3890 0.1425 1.4936 0.0336 1.4339 0.0494
-#> 164: 92.6486 -6.3898 -0.1590 2.2519 -0.9574 0.1948 5.7817 0.3564 0.3925 0.1308 1.5218 0.0326 1.2197 0.0630
-#> 165: 92.6600 -6.3261 -0.1606 2.2464 -0.9815 0.3054 5.9162 0.3611 0.3979 0.1433 1.5747 0.0316 1.2062 0.0632
-#> 166: 92.7951 -6.3068 -0.1630 2.2428 -0.9542 0.3144 5.7041 0.3597 0.3766 0.1612 1.5464 0.0317 1.2649 0.0617
-#> 167: 92.8541 -6.4919 -0.1642 2.2275 -0.9505 0.3509 6.3858 0.3639 0.3713 0.1581 1.5543 0.0315 1.3546 0.0574
-#> 168: 92.6848 -6.3299 -0.1618 2.2329 -0.9494 0.4645 5.7127 0.3700 0.3698 0.1544 1.5058 0.0340 1.1747 0.0685
-#> 169: 92.5817 -6.0236 -0.1572 2.2583 -0.9510 0.6725 3.9864 0.3672 0.3812 0.1763 1.4445 0.0386 1.3230 0.0583
-#> 170: 92.7223 -5.9170 -0.1609 2.2456 -0.9485 0.5137 3.7991 0.3712 0.3714 0.1601 1.5502 0.0385 1.3393 0.0547
-#> 171: 92.6532 -5.9417 -0.1544 2.2294 -0.9448 0.6206 3.9052 0.3789 0.3634 0.1487 1.5809 0.0314 1.1226 0.0711
-#> 172: 92.4803 -5.7302 -0.1414 2.2679 -0.9255 0.7853 2.7901 0.3598 0.3666 0.1508 1.5531 0.0341 1.1785 0.0667
-#> 173: 92.3172 -5.7462 -0.1405 2.2823 -0.9193 1.2505 2.9155 0.3579 0.3678 0.1480 1.4894 0.0434 1.2288 0.0618
-#> 174: 92.4674 -5.6638 -0.1415 2.2775 -0.9054 1.0653 2.8138 0.3623 0.3740 0.1371 1.5301 0.0393 1.0790 0.0669
-#> 175: 92.5581 -5.6388 -0.1338 2.2878 -0.9154 0.6617 2.5216 0.3471 0.3719 0.1546 1.5231 0.0361 1.0672 0.0723
-#> 176: 92.7218 -5.7548 -0.1249 2.3099 -0.9203 0.4464 2.8226 0.3570 0.3978 0.1570 1.4938 0.0354 1.1125 0.0655
-#> 177: 92.7655 -5.6769 -0.1232 2.3114 -0.9257 0.5291 2.5249 0.3571 0.4023 0.1657 1.4392 0.0386 1.1149 0.0663
-#> 178: 92.7966 -5.6766 -0.1219 2.3202 -0.9142 0.4897 2.3359 0.3605 0.3944 0.1720 1.4792 0.0401 1.1665 0.0637
-#> 179: 92.8304 -5.7678 -0.1133 2.3352 -0.9262 0.5428 2.8512 0.3552 0.4191 0.1716 1.4994 0.0410 1.0651 0.0701
-#> 180: 92.8413 -5.7485 -0.1124 2.3452 -0.9494 0.5179 2.6552 0.3555 0.4025 0.1778 1.5102 0.0383 1.1541 0.0670
-#> 181: 92.7078 -5.7437 -0.1145 2.3257 -0.9482 0.6237 2.5673 0.3564 0.3851 0.1897 1.5373 0.0335 1.1413 0.0698
-#> 182: 92.6278 -5.7965 -0.1115 2.3341 -0.9763 0.7558 2.7421 0.3541 0.3850 0.1625 1.5720 0.0309 1.1164 0.0758
-#> 183: 92.4359 -5.7826 -0.1211 2.3204 -0.9481 1.2089 3.0954 0.3598 0.3813 0.1384 1.6391 0.0333 1.2142 0.0646
-#> 184: 92.4840 -5.9143 -0.1218 2.2965 -0.9330 1.2610 4.0248 0.3752 0.3549 0.1597 1.6019 0.0292 1.0945 0.0767
-#> 185: 92.5659 -5.8333 -0.1223 2.2914 -0.9090 1.0578 3.9752 0.3706 0.3640 0.1769 1.5858 0.0287 1.7070 0.0404
-#> 186: 92.5157 -5.9540 -0.1274 2.2967 -0.9678 1.0199 3.7413 0.3625 0.3766 0.1354 1.5905 0.0321 1.2521 0.0660
-#> 187: 92.6988 -5.8607 -0.1193 2.2922 -0.9685 1.1721 2.9764 0.3511 0.3823 0.1347 1.5790 0.0352 1.1477 0.0746
-#> 188: 92.7427 -5.9073 -0.1166 2.3166 -0.9529 1.3606 2.9747 0.3487 0.3981 0.1322 1.5315 0.0344 1.3014 0.0594
-#> 189: 92.6288 -5.8326 -0.1075 2.3268 -0.9543 1.3459 3.2341 0.3388 0.3983 0.1622 1.5374 0.0334 1.5390 0.0504
-#> 190: 92.8047 -5.6198 -0.1064 2.3212 -0.9148 1.6280 2.5774 0.3319 0.4086 0.1656 1.5159 0.0321 1.5423 0.0515
-#> 191: 92.7642 -5.5780 -0.1105 2.3041 -0.9414 1.5723 2.6038 0.3402 0.4111 0.1612 1.5254 0.0321 1.1206 0.0792
-#> 192: 92.7137 -5.5650 -0.1087 2.3014 -0.9399 1.1968 2.0552 0.3412 0.4267 0.1418 1.4910 0.0332 0.9683 0.0834
-#> 193: 93.0503 -5.6414 -0.1060 2.3050 -0.9563 1.0067 2.2362 0.3434 0.4179 0.1371 1.5947 0.0279 1.0349 0.0813
-#> 194: 93.1071 -5.6349 -0.1048 2.3170 -0.9613 1.1495 2.6224 0.3451 0.4086 0.1419 1.6235 0.0276 1.0558 0.0792
-#> 195: 93.0741 -5.7863 -0.1052 2.3293 -0.9605 1.1597 3.0814 0.3440 0.4342 0.1394 1.5248 0.0348 1.0554 0.0771
-#> 196: 93.0768 -5.6986 -0.0911 2.3395 -0.9537 1.1388 2.7165 0.3463 0.4303 0.1467 1.5960 0.0324 1.1195 0.0755
-#> 197: 92.8638 -5.7840 -0.1009 2.3420 -0.9699 1.0231 2.8293 0.3625 0.4272 0.1849 1.5366 0.0360 1.3691 0.0602
-#> 198: 92.8979 -5.8328 -0.0905 2.3497 -0.9668 0.8847 2.7469 0.3509 0.4357 0.1842 1.5501 0.0361 1.1744 0.0715
-#> 199: 92.7817 -6.0173 -0.0946 2.3477 -0.9729 0.8131 3.4886 0.3517 0.4471 0.1906 1.4350 0.0393 1.2311 0.0693
-#> 200: 92.6353 -6.0362 -0.0924 2.3396 -0.9621 0.8259 3.3916 0.3556 0.4569 0.1867 1.4397 0.0350 1.0910 0.0793
-#> 201: 92.6908 -6.0423 -0.0917 2.3400 -0.9564 0.6766 3.6159 0.3552 0.4565 0.1735 1.4506 0.0362 1.0646 0.0794
-#> 202: 92.6302 -6.0238 -0.0919 2.3443 -0.9546 0.5824 3.6723 0.3555 0.4576 0.1716 1.4800 0.0363 1.0519 0.0791
-#> 203: 92.6040 -6.0387 -0.0944 2.3405 -0.9579 0.5710 3.9080 0.3583 0.4476 0.1752 1.4934 0.0373 1.0842 0.0762
-#> 204: 92.6042 -6.0088 -0.0965 2.3351 -0.9580 0.6145 3.8412 0.3608 0.4413 0.1720 1.5047 0.0374 1.0694 0.0760
-#> 205: 92.5887 -6.0107 -0.0968 2.3362 -0.9576 0.6432 3.8854 0.3606 0.4405 0.1711 1.4896 0.0380 1.0615 0.0750
-#> 206: 92.6452 -5.9990 -0.0992 2.3311 -0.9581 0.6728 3.8231 0.3636 0.4339 0.1683 1.4904 0.0379 1.0630 0.0747
-#> 207: 92.6867 -5.9760 -0.1012 2.3283 -0.9606 0.6907 3.6867 0.3665 0.4303 0.1665 1.4908 0.0376 1.0656 0.0739
-#> 208: 92.6867 -5.9652 -0.1033 2.3252 -0.9611 0.6656 3.6185 0.3680 0.4271 0.1656 1.4972 0.0369 1.0944 0.0724
-#> 209: 92.6807 -5.9535 -0.1051 2.3225 -0.9621 0.6532 3.5653 0.3669 0.4249 0.1641 1.4992 0.0366 1.1029 0.0721
-#> 210: 92.6772 -5.9392 -0.1067 2.3185 -0.9611 0.6492 3.4774 0.3661 0.4220 0.1620 1.5034 0.0360 1.0982 0.0723
-#> 211: 92.6803 -5.9099 -0.1089 2.3129 -0.9619 0.6462 3.3783 0.3656 0.4218 0.1622 1.5094 0.0354 1.1060 0.0725
-#> 212: 92.7033 -5.9046 -0.1110 2.3085 -0.9606 0.6467 3.3879 0.3653 0.4222 0.1602 1.5099 0.0350 1.1004 0.0726
-#> 213: 92.7143 -5.9026 -0.1135 2.3046 -0.9594 0.6326 3.3887 0.3646 0.4214 0.1585 1.5139 0.0347 1.1050 0.0722
-#> 214: 92.7156 -5.9151 -0.1157 2.3011 -0.9590 0.6186 3.4587 0.3637 0.4205 0.1571 1.5149 0.0344 1.1060 0.0720
-#> 215: 92.7185 -5.9240 -0.1177 2.2984 -0.9585 0.6226 3.5192 0.3630 0.4190 0.1564 1.5155 0.0342 1.1159 0.0713
-#> 216: 92.7133 -5.9331 -0.1197 2.2953 -0.9575 0.6253 3.5505 0.3630 0.4179 0.1552 1.5199 0.0338 1.1276 0.0708
-#> 217: 92.7111 -5.9341 -0.1215 2.2924 -0.9579 0.6200 3.5565 0.3627 0.4170 0.1542 1.5238 0.0337 1.1409 0.0702
-#> 218: 92.7142 -5.9390 -0.1226 2.2901 -0.9588 0.6110 3.5792 0.3623 0.4162 0.1541 1.5236 0.0335 1.1378 0.0704
-#> 219: 92.7121 -5.9351 -0.1233 2.2891 -0.9587 0.6083 3.5562 0.3617 0.4154 0.1535 1.5280 0.0335 1.1518 0.0697
-#> 220: 92.7133 -5.9467 -0.1244 2.2876 -0.9591 0.6158 3.6036 0.3614 0.4147 0.1542 1.5273 0.0334 1.1572 0.0693
-#> 221: 92.7206 -5.9543 -0.1253 2.2856 -0.9602 0.6252 3.6357 0.3610 0.4131 0.1540 1.5272 0.0335 1.1591 0.0692
-#> 222: 92.7267 -5.9436 -0.1262 2.2840 -0.9608 0.6377 3.5725 0.3608 0.4118 0.1540 1.5302 0.0334 1.1735 0.0683
-#> 223: 92.7364 -5.9346 -0.1268 2.2825 -0.9619 0.6430 3.5288 0.3606 0.4117 0.1542 1.5327 0.0332 1.1883 0.0676
-#> 224: 92.7464 -5.9269 -0.1274 2.2822 -0.9621 0.6394 3.4906 0.3604 0.4107 0.1541 1.5342 0.0334 1.2022 0.0667
-#> 225: 92.7572 -5.9244 -0.1278 2.2813 -0.9616 0.6340 3.4677 0.3603 0.4100 0.1535 1.5345 0.0334 1.2129 0.0661
-#> 226: 92.7662 -5.9237 -0.1282 2.2803 -0.9615 0.6336 3.4532 0.3603 0.4101 0.1532 1.5326 0.0334 1.2151 0.0661
-#> 227: 92.7778 -5.9193 -0.1286 2.2792 -0.9628 0.6280 3.4339 0.3604 0.4096 0.1527 1.5323 0.0334 1.2217 0.0658
-#> 228: 92.7824 -5.9112 -0.1289 2.2782 -0.9636 0.6217 3.3964 0.3607 0.4091 0.1525 1.5316 0.0335 1.2255 0.0658
-#> 229: 92.7895 -5.9077 -0.1291 2.2770 -0.9646 0.6178 3.3717 0.3607 0.4096 0.1521 1.5326 0.0334 1.2247 0.0660
-#> 230: 92.7987 -5.9153 -0.1297 2.2758 -0.9648 0.6177 3.4004 0.3603 0.4098 0.1517 1.5333 0.0334 1.2321 0.0656
-#> 231: 92.8081 -5.9176 -0.1308 2.2735 -0.9654 0.6185 3.4195 0.3596 0.4086 0.1513 1.5361 0.0331 1.2359 0.0656
-#> 232: 92.8119 -5.9161 -0.1318 2.2715 -0.9658 0.6140 3.4221 0.3590 0.4075 0.1513 1.5387 0.0330 1.2434 0.0653
-#> 233: 92.8117 -5.9111 -0.1329 2.2694 -0.9662 0.6096 3.4008 0.3586 0.4065 0.1511 1.5410 0.0328 1.2426 0.0654
-#> 234: 92.8132 -5.9040 -0.1339 2.2672 -0.9660 0.6097 3.3787 0.3583 0.4059 0.1506 1.5425 0.0325 1.2463 0.0654
-#> 235: 92.8117 -5.8978 -0.1347 2.2653 -0.9661 0.6020 3.3558 0.3579 0.4051 0.1502 1.5443 0.0324 1.2439 0.0657
-#> 236: 92.8050 -5.8967 -0.1355 2.2638 -0.9663 0.5963 3.3466 0.3575 0.4046 0.1495 1.5453 0.0322 1.2377 0.0661
-#> 237: 92.7975 -5.9004 -0.1362 2.2625 -0.9668 0.5891 3.3624 0.3571 0.4043 0.1491 1.5460 0.0321 1.2334 0.0664
-#> 238: 92.7965 -5.9036 -0.1371 2.2613 -0.9670 0.5828 3.3683 0.3569 0.4037 0.1488 1.5486 0.0320 1.2405 0.0662
-#> 239: 92.8006 -5.9067 -0.1376 2.2607 -0.9677 0.5767 3.3801 0.3568 0.4027 0.1490 1.5487 0.0319 1.2478 0.0658
-#> 240: 92.8061 -5.9102 -0.1382 2.2597 -0.9678 0.5697 3.3876 0.3566 0.4014 0.1489 1.5499 0.0319 1.2545 0.0654
-#> 241: 92.8111 -5.9132 -0.1388 2.2589 -0.9684 0.5647 3.3986 0.3567 0.4004 0.1489 1.5507 0.0319 1.2607 0.0651
-#> 242: 92.8157 -5.9119 -0.1395 2.2577 -0.9686 0.5610 3.3902 0.3568 0.3995 0.1490 1.5524 0.0319 1.2673 0.0647
-#> 243: 92.8204 -5.9142 -0.1401 2.2567 -0.9689 0.5597 3.3991 0.3570 0.3983 0.1492 1.5526 0.0319 1.2728 0.0646
-#> 244: 92.8272 -5.9129 -0.1408 2.2558 -0.9689 0.5598 3.3989 0.3574 0.3972 0.1493 1.5542 0.0319 1.2805 0.0642
-#> 245: 92.8361 -5.9152 -0.1414 2.2548 -0.9693 0.5617 3.4133 0.3580 0.3959 0.1500 1.5541 0.0318 1.2876 0.0638
-#> 246: 92.8432 -5.9122 -0.1420 2.2536 -0.9695 0.5627 3.4039 0.3584 0.3946 0.1507 1.5546 0.0318 1.2944 0.0633
-#> 247: 92.8481 -5.9125 -0.1426 2.2524 -0.9695 0.5574 3.4087 0.3588 0.3931 0.1515 1.5556 0.0318 1.3003 0.0629
-#> 248: 92.8486 -5.9123 -0.1433 2.2515 -0.9693 0.5545 3.4095 0.3594 0.3916 0.1519 1.5583 0.0317 1.3043 0.0626
-#> 249: 92.8515 -5.9123 -0.1439 2.2505 -0.9694 0.5547 3.4088 0.3600 0.3904 0.1523 1.5605 0.0316 1.3087 0.0623
-#> 250: 92.8521 -5.9139 -0.1443 2.2493 -0.9691 0.5589 3.4212 0.3604 0.3894 0.1525 1.5617 0.0316 1.3081 0.0624
-#> 251: 92.8530 -5.9118 -0.1450 2.2484 -0.9683 0.5562 3.4138 0.3612 0.3884 0.1528 1.5615 0.0316 1.3066 0.0625
-#> 252: 92.8568 -5.9075 -0.1457 2.2474 -0.9681 0.5506 3.3889 0.3619 0.3875 0.1531 1.5620 0.0315 1.3067 0.0625
-#> 253: 92.8603 -5.9070 -0.1464 2.2467 -0.9682 0.5476 3.3746 0.3622 0.3867 0.1539 1.5640 0.0314 1.3122 0.0622
-#> 254: 92.8653 -5.9077 -0.1470 2.2457 -0.9688 0.5448 3.3656 0.3626 0.3858 0.1546 1.5641 0.0314 1.3147 0.0620
-#> 255: 92.8686 -5.9059 -0.1477 2.2445 -0.9688 0.5406 3.3533 0.3630 0.3850 0.1549 1.5637 0.0314 1.3155 0.0619
-#> 256: 92.8706 -5.9011 -0.1483 2.2435 -0.9685 0.5384 3.3300 0.3634 0.3841 0.1550 1.5644 0.0313 1.3161 0.0617
-#> 257: 92.8721 -5.8957 -0.1488 2.2426 -0.9683 0.5398 3.3084 0.3638 0.3833 0.1552 1.5647 0.0313 1.3158 0.0617
-#> 258: 92.8725 -5.8928 -0.1493 2.2419 -0.9680 0.5392 3.2921 0.3641 0.3822 0.1552 1.5665 0.0312 1.3184 0.0614
-#> 259: 92.8718 -5.8915 -0.1498 2.2411 -0.9680 0.5367 3.2850 0.3644 0.3815 0.1553 1.5668 0.0312 1.3202 0.0613
-#> 260: 92.8701 -5.8928 -0.1499 2.2409 -0.9679 0.5339 3.2888 0.3652 0.3802 0.1552 1.5675 0.0312 1.3215 0.0612
-#> 261: 92.8700 -5.8961 -0.1499 2.2407 -0.9679 0.5302 3.2976 0.3659 0.3789 0.1551 1.5677 0.0312 1.3197 0.0613
-#> 262: 92.8683 -5.9013 -0.1500 2.2407 -0.9678 0.5282 3.3236 0.3666 0.3778 0.1549 1.5684 0.0312 1.3184 0.0613
-#> 263: 92.8662 -5.9021 -0.1498 2.2407 -0.9677 0.5271 3.3285 0.3670 0.3767 0.1547 1.5682 0.0313 1.3156 0.0615
-#> 264: 92.8631 -5.9059 -0.1495 2.2409 -0.9675 0.5244 3.3527 0.3673 0.3755 0.1547 1.5677 0.0313 1.3139 0.0616
-#> 265: 92.8635 -5.9042 -0.1492 2.2411 -0.9675 0.5220 3.3541 0.3675 0.3745 0.1545 1.5676 0.0313 1.3098 0.0618
-#> 266: 92.8636 -5.9033 -0.1490 2.2411 -0.9673 0.5208 3.3523 0.3680 0.3735 0.1546 1.5679 0.0312 1.3087 0.0619
-#> 267: 92.8639 -5.9035 -0.1489 2.2413 -0.9673 0.5208 3.3566 0.3685 0.3726 0.1546 1.5676 0.0312 1.3072 0.0621
-#> 268: 92.8620 -5.9065 -0.1487 2.2413 -0.9674 0.5191 3.3797 0.3689 0.3717 0.1545 1.5676 0.0312 1.3103 0.0620
-#> 269: 92.8593 -5.9073 -0.1486 2.2416 -0.9672 0.5192 3.3885 0.3693 0.3710 0.1545 1.5685 0.0312 1.3136 0.0618
-#> 270: 92.8549 -5.9087 -0.1487 2.2418 -0.9672 0.5209 3.4007 0.3695 0.3703 0.1544 1.5703 0.0312 1.3177 0.0615
-#> 271: 92.8519 -5.9089 -0.1487 2.2416 -0.9671 0.5227 3.4043 0.3696 0.3697 0.1545 1.5705 0.0312 1.3216 0.0613
-#> 272: 92.8493 -5.9084 -0.1488 2.2416 -0.9669 0.5223 3.3999 0.3698 0.3693 0.1543 1.5707 0.0311 1.3206 0.0614
-#> 273: 92.8479 -5.9090 -0.1486 2.2416 -0.9667 0.5230 3.3980 0.3701 0.3689 0.1544 1.5699 0.0311 1.3192 0.0615
-#> 274: 92.8456 -5.9108 -0.1485 2.2417 -0.9667 0.5249 3.4024 0.3705 0.3684 0.1544 1.5688 0.0311 1.3169 0.0617
-#> 275: 92.8440 -5.9131 -0.1483 2.2422 -0.9666 0.5253 3.4117 0.3707 0.3677 0.1542 1.5690 0.0311 1.3166 0.0616
-#> 276: 92.8425 -5.9132 -0.1482 2.2426 -0.9662 0.5241 3.4171 0.3709 0.3670 0.1540 1.5689 0.0311 1.3142 0.0617
-#> 277: 92.8412 -5.9139 -0.1481 2.2430 -0.9660 0.5214 3.4228 0.3711 0.3663 0.1540 1.5687 0.0311 1.3173 0.0615
-#> 278: 92.8398 -5.9139 -0.1479 2.2432 -0.9659 0.5184 3.4254 0.3712 0.3654 0.1540 1.5684 0.0311 1.3148 0.0617
-#> 279: 92.8386 -5.9156 -0.1478 2.2433 -0.9661 0.5157 3.4338 0.3713 0.3649 0.1539 1.5682 0.0311 1.3136 0.0618
-#> 280: 92.8378 -5.9173 -0.1478 2.2428 -0.9663 0.5127 3.4381 0.3714 0.3643 0.1537 1.5679 0.0311 1.3104 0.0621
-#> 281: 92.8364 -5.9188 -0.1479 2.2423 -0.9666 0.5089 3.4418 0.3716 0.3634 0.1533 1.5674 0.0311 1.3071 0.0623
-#> 282: 92.8377 -5.9179 -0.1481 2.2418 -0.9668 0.5045 3.4355 0.3717 0.3626 0.1530 1.5686 0.0311 1.3055 0.0624
-#> 283: 92.8385 -5.9157 -0.1485 2.2410 -0.9667 0.5014 3.4260 0.3720 0.3616 0.1527 1.5699 0.0311 1.3072 0.0622
-#> 284: 92.8388 -5.9156 -0.1489 2.2403 -0.9666 0.4977 3.4274 0.3723 0.3605 0.1525 1.5705 0.0310 1.3081 0.0621
-#> 285: 92.8374 -5.9156 -0.1492 2.2395 -0.9668 0.4944 3.4215 0.3727 0.3594 0.1525 1.5716 0.0310 1.3103 0.0619
-#> 286: 92.8376 -5.9168 -0.1496 2.2388 -0.9672 0.4915 3.4197 0.3731 0.3583 0.1526 1.5724 0.0310 1.3141 0.0617
-#> 287: 92.8393 -5.9176 -0.1498 2.2380 -0.9673 0.4886 3.4177 0.3735 0.3572 0.1523 1.5737 0.0309 1.3155 0.0615
-#> 288: 92.8400 -5.9206 -0.1502 2.2372 -0.9675 0.4873 3.4259 0.3739 0.3562 0.1523 1.5739 0.0309 1.3160 0.0614
-#> 289: 92.8404 -5.9217 -0.1506 2.2362 -0.9678 0.4845 3.4269 0.3744 0.3552 0.1524 1.5735 0.0309 1.3165 0.0614
-#> 290: 92.8395 -5.9255 -0.1510 2.2354 -0.9680 0.4830 3.4395 0.3748 0.3543 0.1521 1.5737 0.0308 1.3159 0.0615
-#> 291: 92.8384 -5.9274 -0.1513 2.2345 -0.9680 0.4841 3.4460 0.3752 0.3533 0.1518 1.5742 0.0309 1.3173 0.0613
-#> 292: 92.8384 -5.9276 -0.1515 2.2342 -0.9681 0.4865 3.4437 0.3755 0.3525 0.1516 1.5738 0.0309 1.3163 0.0614
-#> 293: 92.8385 -5.9281 -0.1517 2.2338 -0.9681 0.4882 3.4446 0.3757 0.3516 0.1513 1.5738 0.0308 1.3143 0.0614
-#> 294: 92.8400 -5.9277 -0.1519 2.2335 -0.9680 0.4871 3.4449 0.3758 0.3508 0.1512 1.5736 0.0308 1.3149 0.0614
-#> 295: 92.8414 -5.9279 -0.1520 2.2331 -0.9680 0.4842 3.4523 0.3760 0.3502 0.1510 1.5740 0.0308 1.3153 0.0614
-#> 296: 92.8424 -5.9282 -0.1521 2.2329 -0.9681 0.4835 3.4589 0.3760 0.3496 0.1509 1.5743 0.0307 1.3180 0.0613
-#> 297: 92.8409 -5.9281 -0.1522 2.2325 -0.9683 0.4827 3.4636 0.3760 0.3491 0.1509 1.5745 0.0307 1.3216 0.0611
-#> 298: 92.8395 -5.9276 -0.1522 2.2322 -0.9684 0.4819 3.4641 0.3761 0.3486 0.1508 1.5744 0.0307 1.3226 0.0612
-#> 299: 92.8388 -5.9305 -0.1524 2.2321 -0.9686 0.4800 3.4829 0.3761 0.3481 0.1507 1.5745 0.0307 1.3218 0.0612
-#> 300: 92.8375 -5.9329 -0.1524 2.2321 -0.9683 0.4792 3.4982 0.3761 0.3477 0.1505 1.5745 0.0307 1.3205 0.0613
-#> 301: 92.8359 -5.9337 -0.1524 2.2321 -0.9680 0.4788 3.5056 0.3762 0.3473 0.1503 1.5746 0.0306 1.3182 0.0614
-#> 302: 92.8346 -5.9360 -0.1524 2.2322 -0.9678 0.4800 3.5237 0.3763 0.3470 0.1500 1.5744 0.0306 1.3174 0.0614
-#> 303: 92.8338 -5.9387 -0.1524 2.2324 -0.9674 0.4795 3.5444 0.3764 0.3467 0.1501 1.5738 0.0307 1.3181 0.0613
-#> 304: 92.8318 -5.9436 -0.1524 2.2327 -0.9673 0.4787 3.5819 0.3766 0.3464 0.1502 1.5735 0.0307 1.3191 0.0612
-#> 305: 92.8300 -5.9486 -0.1524 2.2327 -0.9673 0.4794 3.6200 0.3766 0.3460 0.1502 1.5726 0.0308 1.3198 0.0611
-#> 306: 92.8294 -5.9540 -0.1524 2.2328 -0.9673 0.4788 3.6681 0.3766 0.3456 0.1502 1.5723 0.0309 1.3214 0.0610
-#> 307: 92.8287 -5.9579 -0.1525 2.2330 -0.9669 0.4779 3.7052 0.3766 0.3452 0.1498 1.5735 0.0309 1.3235 0.0609
-#> 308: 92.8290 -5.9624 -0.1524 2.2332 -0.9669 0.4775 3.7470 0.3766 0.3448 0.1500 1.5737 0.0309 1.3265 0.0607
-#> 309: 92.8293 -5.9653 -0.1524 2.2333 -0.9668 0.4774 3.7756 0.3766 0.3443 0.1499 1.5736 0.0309 1.3290 0.0605
-#> 310: 92.8289 -5.9672 -0.1523 2.2335 -0.9669 0.4762 3.7957 0.3767 0.3438 0.1499 1.5736 0.0309 1.3316 0.0603
-#> 311: 92.8301 -5.9702 -0.1521 2.2337 -0.9670 0.4755 3.8172 0.3767 0.3432 0.1498 1.5737 0.0309 1.3324 0.0603
-#> 312: 92.8322 -5.9715 -0.1520 2.2341 -0.9670 0.4742 3.8229 0.3767 0.3427 0.1496 1.5734 0.0309 1.3309 0.0603
-#> 313: 92.8338 -5.9713 -0.1517 2.2342 -0.9672 0.4737 3.8202 0.3766 0.3422 0.1494 1.5733 0.0309 1.3306 0.0604
-#> 314: 92.8360 -5.9711 -0.1515 2.2343 -0.9675 0.4725 3.8154 0.3767 0.3417 0.1493 1.5733 0.0309 1.3322 0.0603
-#> 315: 92.8378 -5.9694 -0.1514 2.2343 -0.9680 0.4714 3.8051 0.3767 0.3414 0.1494 1.5734 0.0309 1.3352 0.0601
-#> 316: 92.8400 -5.9683 -0.1514 2.2343 -0.9682 0.4705 3.7984 0.3767 0.3410 0.1495 1.5735 0.0309 1.3354 0.0602
-#> 317: 92.8422 -5.9689 -0.1513 2.2344 -0.9686 0.4695 3.7961 0.3768 0.3406 0.1497 1.5735 0.0309 1.3362 0.0602
-#> 318: 92.8440 -5.9696 -0.1510 2.2347 -0.9689 0.4681 3.7934 0.3769 0.3403 0.1499 1.5731 0.0309 1.3381 0.0601
-#> 319: 92.8458 -5.9710 -0.1508 2.2350 -0.9692 0.4668 3.7913 0.3769 0.3401 0.1500 1.5723 0.0309 1.3403 0.0599
-#> 320: 92.8474 -5.9719 -0.1506 2.2353 -0.9695 0.4667 3.7876 0.3769 0.3400 0.1502 1.5714 0.0309 1.3423 0.0598
-#> 321: 92.8494 -5.9710 -0.1503 2.2355 -0.9696 0.4673 3.7790 0.3769 0.3397 0.1503 1.5709 0.0309 1.3439 0.0597
-#> 322: 92.8511 -5.9693 -0.1501 2.2359 -0.9698 0.4690 3.7674 0.3769 0.3395 0.1503 1.5708 0.0309 1.3451 0.0596
-#> 323: 92.8528 -5.9700 -0.1498 2.2364 -0.9699 0.4696 3.7641 0.3768 0.3394 0.1504 1.5701 0.0310 1.3470 0.0594
-#> 324: 92.8547 -5.9695 -0.1495 2.2369 -0.9699 0.4703 3.7567 0.3767 0.3392 0.1505 1.5698 0.0310 1.3485 0.0593
-#> 325: 92.8563 -5.9678 -0.1490 2.2376 -0.9702 0.4701 3.7473 0.3769 0.3395 0.1505 1.5702 0.0311 1.3494 0.0592
-#> 326: 92.8582 -5.9676 -0.1486 2.2382 -0.9703 0.4709 3.7434 0.3771 0.3397 0.1506 1.5700 0.0311 1.3479 0.0593
-#> 327: 92.8603 -5.9665 -0.1481 2.2389 -0.9704 0.4716 3.7361 0.3769 0.3399 0.1507 1.5699 0.0311 1.3471 0.0594
-#> 328: 92.8622 -5.9671 -0.1477 2.2397 -0.9704 0.4726 3.7379 0.3767 0.3398 0.1507 1.5698 0.0311 1.3481 0.0593
-#> 329: 92.8639 -5.9667 -0.1473 2.2405 -0.9707 0.4735 3.7366 0.3766 0.3398 0.1506 1.5696 0.0311 1.3482 0.0593
-#> 330: 92.8663 -5.9673 -0.1469 2.2413 -0.9708 0.4736 3.7382 0.3765 0.3397 0.1506 1.5691 0.0312 1.3492 0.0592
-#> 331: 92.8674 -5.9670 -0.1464 2.2420 -0.9710 0.4740 3.7350 0.3763 0.3397 0.1507 1.5689 0.0312 1.3512 0.0591
-#> 332: 92.8681 -5.9664 -0.1460 2.2428 -0.9710 0.4737 3.7311 0.3762 0.3396 0.1509 1.5687 0.0312 1.3527 0.0590
-#> 333: 92.8683 -5.9649 -0.1456 2.2436 -0.9708 0.4727 3.7232 0.3760 0.3397 0.1509 1.5686 0.0312 1.3505 0.0591
-#> 334: 92.8690 -5.9642 -0.1452 2.2444 -0.9707 0.4723 3.7194 0.3758 0.3399 0.1511 1.5682 0.0312 1.3490 0.0592
-#> 335: 92.8698 -5.9656 -0.1447 2.2454 -0.9707 0.4722 3.7289 0.3756 0.3400 0.1512 1.5674 0.0313 1.3476 0.0592
-#> 336: 92.8691 -5.9664 -0.1443 2.2463 -0.9706 0.4724 3.7333 0.3753 0.3401 0.1511 1.5669 0.0313 1.3455 0.0593
-#> 337: 92.8687 -5.9670 -0.1440 2.2471 -0.9705 0.4742 3.7378 0.3749 0.3402 0.1510 1.5665 0.0314 1.3433 0.0594
-#> 338: 92.8683 -5.9663 -0.1435 2.2480 -0.9703 0.4747 3.7370 0.3746 0.3405 0.1510 1.5663 0.0313 1.3402 0.0595
-#> 339: 92.8682 -5.9650 -0.1431 2.2488 -0.9701 0.4760 3.7332 0.3743 0.3408 0.1509 1.5661 0.0313 1.3374 0.0597
-#> 340: 92.8684 -5.9639 -0.1427 2.2496 -0.9699 0.4774 3.7283 0.3739 0.3411 0.1510 1.5658 0.0313 1.3358 0.0597
-#> 341: 92.8685 -5.9610 -0.1423 2.2504 -0.9696 0.4782 3.7169 0.3735 0.3413 0.1510 1.5661 0.0313 1.3338 0.0598
-#> 342: 92.8681 -5.9581 -0.1419 2.2512 -0.9696 0.4802 3.7060 0.3731 0.3416 0.1511 1.5661 0.0313 1.3316 0.0599
-#> 343: 92.8671 -5.9557 -0.1414 2.2521 -0.9697 0.4821 3.6971 0.3726 0.3419 0.1510 1.5667 0.0313 1.3292 0.0601
-#> 344: 92.8662 -5.9550 -0.1409 2.2531 -0.9696 0.4825 3.6931 0.3722 0.3424 0.1509 1.5660 0.0314 1.3269 0.0602
-#> 345: 92.8651 -5.9542 -0.1405 2.2542 -0.9696 0.4825 3.6886 0.3717 0.3429 0.1511 1.5645 0.0315 1.3252 0.0602
-#> 346: 92.8636 -5.9534 -0.1401 2.2549 -0.9696 0.4822 3.6821 0.3714 0.3432 0.1510 1.5638 0.0315 1.3231 0.0603
-#> 347: 92.8622 -5.9532 -0.1397 2.2557 -0.9696 0.4815 3.6782 0.3712 0.3435 0.1509 1.5636 0.0315 1.3220 0.0604
-#> 348: 92.8593 -5.9538 -0.1394 2.2566 -0.9697 0.4813 3.6787 0.3709 0.3438 0.1508 1.5634 0.0315 1.3202 0.0605
-#> 349: 92.8574 -5.9532 -0.1389 2.2574 -0.9697 0.4808 3.6739 0.3706 0.3440 0.1506 1.5630 0.0316 1.3179 0.0606
-#> 350: 92.8561 -5.9528 -0.1385 2.2583 -0.9697 0.4801 3.6705 0.3703 0.3443 0.1505 1.5625 0.0316 1.3161 0.0607
-#> 351: 92.8541 -5.9518 -0.1381 2.2591 -0.9697 0.4804 3.6650 0.3700 0.3446 0.1505 1.5619 0.0316 1.3141 0.0608
-#> 352: 92.8528 -5.9516 -0.1377 2.2599 -0.9700 0.4818 3.6626 0.3698 0.3449 0.1504 1.5614 0.0316 1.3122 0.0609
-#> 353: 92.8506 -5.9518 -0.1373 2.2607 -0.9700 0.4836 3.6601 0.3697 0.3451 0.1506 1.5604 0.0317 1.3116 0.0610
-#> 354: 92.8482 -5.9507 -0.1369 2.2615 -0.9700 0.4852 3.6520 0.3696 0.3451 0.1506 1.5595 0.0317 1.3099 0.0611
-#> 355: 92.8459 -5.9500 -0.1365 2.2624 -0.9699 0.4873 3.6467 0.3695 0.3454 0.1505 1.5589 0.0318 1.3090 0.0611
-#> 356: 92.8441 -5.9494 -0.1361 2.2632 -0.9700 0.4893 3.6407 0.3696 0.3456 0.1505 1.5581 0.0319 1.3083 0.0612
-#> 357: 92.8425 -5.9492 -0.1356 2.2641 -0.9700 0.4906 3.6359 0.3696 0.3459 0.1506 1.5568 0.0320 1.3082 0.0612
-#> 358: 92.8414 -5.9487 -0.1351 2.2649 -0.9700 0.4914 3.6300 0.3697 0.3460 0.1506 1.5559 0.0321 1.3064 0.0613
-#> 359: 92.8395 -5.9487 -0.1346 2.2657 -0.9700 0.4923 3.6262 0.3699 0.3462 0.1507 1.5558 0.0321 1.3050 0.0614
-#> 360: 92.8373 -5.9478 -0.1341 2.2666 -0.9700 0.4922 3.6206 0.3700 0.3465 0.1509 1.5553 0.0322 1.3061 0.0614
-#> 361: 92.8353 -5.9475 -0.1337 2.2673 -0.9699 0.4912 3.6183 0.3700 0.3469 0.1510 1.5549 0.0322 1.3051 0.0614
-#> 362: 92.8339 -5.9474 -0.1333 2.2681 -0.9699 0.4896 3.6164 0.3700 0.3472 0.1510 1.5549 0.0322 1.3041 0.0616
-#> 363: 92.8318 -5.9470 -0.1328 2.2690 -0.9696 0.4882 3.6136 0.3700 0.3476 0.1510 1.5541 0.0323 1.3035 0.0616
-#> 364: 92.8305 -5.9460 -0.1325 2.2697 -0.9695 0.4863 3.6099 0.3701 0.3477 0.1510 1.5533 0.0324 1.3028 0.0616
-#> 365: 92.8300 -5.9451 -0.1320 2.2705 -0.9693 0.4851 3.6083 0.3703 0.3479 0.1511 1.5535 0.0324 1.3017 0.0617
-#> 366: 92.8290 -5.9444 -0.1317 2.2710 -0.9691 0.4841 3.6062 0.3707 0.3476 0.1512 1.5534 0.0325 1.3013 0.0617
-#> 367: 92.8279 -5.9438 -0.1313 2.2715 -0.9688 0.4829 3.6026 0.3711 0.3473 0.1513 1.5537 0.0325 1.2996 0.0618
-#> 368: 92.8270 -5.9437 -0.1310 2.2721 -0.9687 0.4824 3.6015 0.3715 0.3471 0.1513 1.5535 0.0325 1.2984 0.0619
-#> 369: 92.8268 -5.9444 -0.1306 2.2726 -0.9686 0.4829 3.6042 0.3718 0.3469 0.1514 1.5530 0.0325 1.2983 0.0619
-#> 370: 92.8268 -5.9455 -0.1303 2.2732 -0.9686 0.4833 3.6099 0.3721 0.3466 0.1513 1.5526 0.0326 1.2971 0.0619
-#> 371: 92.8269 -5.9462 -0.1300 2.2737 -0.9686 0.4842 3.6169 0.3723 0.3465 0.1512 1.5516 0.0326 1.2961 0.0619
-#> 372: 92.8272 -5.9465 -0.1297 2.2741 -0.9685 0.4852 3.6242 0.3726 0.3463 0.1512 1.5507 0.0327 1.2950 0.0620
-#> 373: 92.8275 -5.9456 -0.1294 2.2746 -0.9686 0.4861 3.6219 0.3729 0.3461 0.1511 1.5501 0.0328 1.2946 0.0620
-#> 374: 92.8278 -5.9445 -0.1291 2.2750 -0.9687 0.4867 3.6175 0.3730 0.3461 0.1509 1.5496 0.0328 1.2942 0.0620
-#> 375: 92.8285 -5.9438 -0.1289 2.2753 -0.9689 0.4874 3.6118 0.3731 0.3459 0.1509 1.5491 0.0329 1.2938 0.0620
-#> 376: 92.8286 -5.9439 -0.1287 2.2755 -0.9689 0.4876 3.6100 0.3733 0.3458 0.1508 1.5488 0.0329 1.2930 0.0621
-#> 377: 92.8289 -5.9431 -0.1285 2.2758 -0.9690 0.4870 3.6054 0.3735 0.3456 0.1508 1.5487 0.0329 1.2921 0.0621
-#> 378: 92.8293 -5.9428 -0.1284 2.2760 -0.9689 0.4865 3.6019 0.3737 0.3454 0.1508 1.5484 0.0329 1.2910 0.0622
-#> 379: 92.8294 -5.9441 -0.1282 2.2763 -0.9688 0.4857 3.6077 0.3739 0.3451 0.1507 1.5480 0.0329 1.2907 0.0622
-#> 380: 92.8296 -5.9448 -0.1281 2.2766 -0.9688 0.4844 3.6104 0.3741 0.3448 0.1506 1.5475 0.0329 1.2901 0.0622
-#> 381: 92.8301 -5.9461 -0.1280 2.2767 -0.9689 0.4833 3.6194 0.3743 0.3444 0.1505 1.5476 0.0329 1.2893 0.0622
-#> 382: 92.8312 -5.9464 -0.1278 2.2768 -0.9689 0.4823 3.6237 0.3745 0.3441 0.1505 1.5476 0.0329 1.2881 0.0622
-#> 383: 92.8317 -5.9459 -0.1277 2.2770 -0.9687 0.4817 3.6282 0.3747 0.3438 0.1504 1.5479 0.0329 1.2875 0.0622
-#> 384: 92.8325 -5.9458 -0.1276 2.2772 -0.9686 0.4818 3.6293 0.3749 0.3434 0.1503 1.5481 0.0329 1.2863 0.0623
-#> 385: 92.8337 -5.9449 -0.1275 2.2773 -0.9685 0.4832 3.6263 0.3751 0.3431 0.1503 1.5481 0.0330 1.2860 0.0622
-#> 386: 92.8346 -5.9455 -0.1274 2.2773 -0.9682 0.4834 3.6283 0.3754 0.3427 0.1501 1.5483 0.0330 1.2851 0.0623
-#> 387: 92.8353 -5.9460 -0.1273 2.2775 -0.9681 0.4831 3.6303 0.3756 0.3424 0.1499 1.5486 0.0330 1.2836 0.0623
-#> 388: 92.8365 -5.9462 -0.1272 2.2777 -0.9680 0.4831 3.6294 0.3759 0.3420 0.1498 1.5486 0.0330 1.2830 0.0624
-#> 389: 92.8378 -5.9456 -0.1271 2.2779 -0.9678 0.4830 3.6260 0.3762 0.3416 0.1497 1.5486 0.0330 1.2816 0.0624
-#> 390: 92.8397 -5.9454 -0.1270 2.2779 -0.9678 0.4835 3.6245 0.3765 0.3413 0.1496 1.5488 0.0330 1.2805 0.0625
-#> 391: 92.8416 -5.9461 -0.1269 2.2780 -0.9679 0.4841 3.6273 0.3768 0.3409 0.1497 1.5486 0.0330 1.2816 0.0624
-#> 392: 92.8430 -5.9471 -0.1269 2.2779 -0.9679 0.4844 3.6293 0.3771 0.3408 0.1498 1.5483 0.0330 1.2830 0.0623
-#> 393: 92.8444 -5.9478 -0.1269 2.2779 -0.9680 0.4841 3.6310 0.3774 0.3407 0.1500 1.5485 0.0330 1.2842 0.0623
-#> 394: 92.8458 -5.9492 -0.1268 2.2779 -0.9680 0.4839 3.6370 0.3775 0.3407 0.1502 1.5484 0.0330 1.2847 0.0622
-#> 395: 92.8474 -5.9501 -0.1268 2.2780 -0.9681 0.4830 3.6391 0.3777 0.3406 0.1503 1.5485 0.0330 1.2849 0.0622
-#> 396: 92.8484 -5.9500 -0.1267 2.2781 -0.9682 0.4820 3.6369 0.3778 0.3406 0.1504 1.5490 0.0330 1.2850 0.0622
-#> 397: 92.8497 -5.9490 -0.1267 2.2782 -0.9680 0.4813 3.6308 0.3779 0.3407 0.1504 1.5494 0.0330 1.2848 0.0622
-#> 398: 92.8511 -5.9478 -0.1267 2.2782 -0.9679 0.4811 3.6256 0.3780 0.3407 0.1505 1.5498 0.0330 1.2844 0.0622
-#> 399: 92.8531 -5.9467 -0.1266 2.2782 -0.9680 0.4804 3.6208 0.3781 0.3407 0.1505 1.5505 0.0330 1.2842 0.0623
-#> 400: 92.8545 -5.9465 -0.1266 2.2782 -0.9679 0.4793 3.6175 0.3783 0.3406 0.1505 1.5506 0.0329 1.2833 0.0623
-#> 401: 92.8558 -5.9458 -0.1266 2.2781 -0.9679 0.4787 3.6135 0.3784 0.3406 0.1506 1.5506 0.0329 1.2836 0.0623
-#> 402: 92.8571 -5.9454 -0.1266 2.2780 -0.9678 0.4788 3.6122 0.3786 0.3405 0.1506 1.5508 0.0329 1.2841 0.0623
-#> 403: 92.8583 -5.9454 -0.1267 2.2778 -0.9679 0.4794 3.6115 0.3790 0.3402 0.1507 1.5508 0.0330 1.2859 0.0622
-#> 404: 92.8593 -5.9466 -0.1268 2.2776 -0.9681 0.4787 3.6149 0.3793 0.3401 0.1508 1.5507 0.0330 1.2875 0.0621
-#> 405: 92.8598 -5.9475 -0.1269 2.2774 -0.9681 0.4781 3.6208 0.3796 0.3399 0.1509 1.5507 0.0330 1.2888 0.0620
-#> 406: 92.8596 -5.9480 -0.1269 2.2773 -0.9680 0.4776 3.6238 0.3798 0.3397 0.1509 1.5508 0.0330 1.2895 0.0619
-#> 407: 92.8588 -5.9487 -0.1270 2.2773 -0.9679 0.4773 3.6289 0.3801 0.3395 0.1508 1.5510 0.0331 1.2887 0.0619
-#> 408: 92.8587 -5.9489 -0.1271 2.2771 -0.9677 0.4777 3.6323 0.3804 0.3391 0.1508 1.5513 0.0331 1.2878 0.0620
-#> 409: 92.8585 -5.9498 -0.1272 2.2770 -0.9677 0.4791 3.6383 0.3806 0.3389 0.1506 1.5512 0.0331 1.2865 0.0621
-#> 410: 92.8574 -5.9522 -0.1272 2.2769 -0.9676 0.4810 3.6538 0.3809 0.3387 0.1507 1.5509 0.0331 1.2855 0.0621
-#> 411: 92.8568 -5.9532 -0.1272 2.2767 -0.9675 0.4817 3.6651 0.3811 0.3385 0.1507 1.5508 0.0332 1.2842 0.0622
-#> 412: 92.8562 -5.9535 -0.1273 2.2767 -0.9674 0.4819 3.6756 0.3812 0.3383 0.1507 1.5509 0.0332 1.2851 0.0621
-#> 413: 92.8559 -5.9542 -0.1274 2.2766 -0.9672 0.4824 3.6881 0.3814 0.3381 0.1507 1.5514 0.0332 1.2848 0.0621
-#> 414: 92.8556 -5.9550 -0.1274 2.2765 -0.9670 0.4835 3.6990 0.3815 0.3379 0.1507 1.5519 0.0332 1.2838 0.0622
-#> 415: 92.8551 -5.9566 -0.1274 2.2764 -0.9669 0.4838 3.7133 0.3816 0.3377 0.1506 1.5522 0.0332 1.2828 0.0623
-#> 416: 92.8547 -5.9581 -0.1275 2.2764 -0.9668 0.4848 3.7276 0.3818 0.3374 0.1504 1.5526 0.0332 1.2814 0.0623
-#> 417: 92.8538 -5.9581 -0.1274 2.2764 -0.9667 0.4856 3.7321 0.3818 0.3372 0.1503 1.5532 0.0332 1.2800 0.0624
-#> 418: 92.8527 -5.9590 -0.1273 2.2766 -0.9665 0.4869 3.7398 0.3817 0.3372 0.1502 1.5532 0.0332 1.2787 0.0625
-#> 419: 92.8524 -5.9596 -0.1272 2.2768 -0.9663 0.4869 3.7467 0.3817 0.3372 0.1501 1.5531 0.0332 1.2779 0.0625
-#> 420: 92.8520 -5.9598 -0.1271 2.2771 -0.9662 0.4863 3.7494 0.3817 0.3372 0.1501 1.5528 0.0332 1.2774 0.0625
-#> 421: 92.8516 -5.9601 -0.1270 2.2772 -0.9661 0.4855 3.7541 0.3817 0.3372 0.1500 1.5527 0.0333 1.2763 0.0625
-#> 422: 92.8509 -5.9602 -0.1270 2.2775 -0.9659 0.4855 3.7554 0.3818 0.3371 0.1499 1.5525 0.0333 1.2753 0.0626
-#> 423: 92.8497 -5.9608 -0.1269 2.2777 -0.9658 0.4855 3.7590 0.3819 0.3371 0.1499 1.5524 0.0334 1.2746 0.0626
-#> 424: 92.8490 -5.9620 -0.1269 2.2779 -0.9658 0.4852 3.7657 0.3820 0.3370 0.1498 1.5521 0.0334 1.2740 0.0626
-#> 425: 92.8481 -5.9615 -0.1268 2.2780 -0.9657 0.4852 3.7639 0.3819 0.3369 0.1497 1.5520 0.0334 1.2741 0.0625
-#> 426: 92.8471 -5.9611 -0.1267 2.2783 -0.9656 0.4859 3.7632 0.3819 0.3369 0.1495 1.5520 0.0335 1.2744 0.0625
-#> 427: 92.8470 -5.9605 -0.1266 2.2784 -0.9655 0.4856 3.7616 0.3819 0.3368 0.1494 1.5522 0.0335 1.2739 0.0625
-#> 428: 92.8464 -5.9602 -0.1266 2.2786 -0.9653 0.4851 3.7603 0.3820 0.3367 0.1493 1.5522 0.0335 1.2731 0.0625
-#> 429: 92.8450 -5.9593 -0.1265 2.2788 -0.9652 0.4852 3.7573 0.3820 0.3366 0.1493 1.5525 0.0335 1.2720 0.0626
-#> 430: 92.8440 -5.9590 -0.1264 2.2789 -0.9651 0.4862 3.7586 0.3821 0.3365 0.1493 1.5524 0.0335 1.2710 0.0627
-#> 431: 92.8428 -5.9583 -0.1263 2.2791 -0.9649 0.4868 3.7575 0.3821 0.3365 0.1493 1.5522 0.0335 1.2698 0.0627
-#> 432: 92.8417 -5.9583 -0.1262 2.2793 -0.9649 0.4881 3.7580 0.3821 0.3365 0.1493 1.5518 0.0335 1.2683 0.0628
-#> 433: 92.8404 -5.9589 -0.1261 2.2796 -0.9648 0.4888 3.7614 0.3821 0.3364 0.1494 1.5513 0.0335 1.2681 0.0628
-#> 434: 92.8392 -5.9585 -0.1260 2.2798 -0.9646 0.4900 3.7602 0.3821 0.3363 0.1494 1.5509 0.0336 1.2686 0.0627
-#> 435: 92.8376 -5.9587 -0.1260 2.2801 -0.9645 0.4913 3.7622 0.3822 0.3362 0.1494 1.5506 0.0336 1.2677 0.0627
-#> 436: 92.8367 -5.9581 -0.1259 2.2802 -0.9646 0.4912 3.7594 0.3821 0.3361 0.1494 1.5504 0.0336 1.2684 0.0627
-#> 437: 92.8352 -5.9588 -0.1259 2.2803 -0.9647 0.4910 3.7634 0.3821 0.3360 0.1494 1.5501 0.0337 1.2695 0.0626
-#> 438: 92.8332 -5.9592 -0.1259 2.2804 -0.9648 0.4913 3.7649 0.3821 0.3358 0.1494 1.5498 0.0337 1.2705 0.0625
-#> 439: 92.8310 -5.9589 -0.1258 2.2805 -0.9648 0.4916 3.7630 0.3821 0.3357 0.1494 1.5497 0.0337 1.2713 0.0625
-#> 440: 92.8292 -5.9590 -0.1258 2.2806 -0.9649 0.4915 3.7620 0.3821 0.3355 0.1493 1.5494 0.0338 1.2712 0.0625
-#> 441: 92.8276 -5.9590 -0.1258 2.2808 -0.9650 0.4915 3.7619 0.3822 0.3353 0.1493 1.5493 0.0338 1.2712 0.0625
-#> 442: 92.8258 -5.9587 -0.1257 2.2809 -0.9650 0.4927 3.7592 0.3822 0.3351 0.1493 1.5493 0.0338 1.2707 0.0625
-#> 443: 92.8241 -5.9586 -0.1256 2.2811 -0.9651 0.4941 3.7563 0.3822 0.3350 0.1493 1.5491 0.0338 1.2704 0.0625
-#> 444: 92.8228 -5.9591 -0.1256 2.2812 -0.9651 0.4954 3.7566 0.3822 0.3349 0.1493 1.5488 0.0339 1.2703 0.0625
-#> 445: 92.8210 -5.9596 -0.1256 2.2813 -0.9652 0.4972 3.7573 0.3821 0.3348 0.1493 1.5484 0.0339 1.2702 0.0625
-#> 446: 92.8193 -5.9595 -0.1255 2.2815 -0.9652 0.4989 3.7551 0.3821 0.3348 0.1494 1.5482 0.0339 1.2708 0.0624
-#> 447: 92.8183 -5.9598 -0.1255 2.2817 -0.9652 0.5002 3.7548 0.3820 0.3347 0.1494 1.5478 0.0339 1.2710 0.0624
-#> 448: 92.8177 -5.9607 -0.1255 2.2818 -0.9653 0.5019 3.7585 0.3819 0.3347 0.1495 1.5475 0.0340 1.2711 0.0624
-#> 449: 92.8171 -5.9613 -0.1254 2.2819 -0.9654 0.5040 3.7592 0.3819 0.3347 0.1495 1.5474 0.0340 1.2711 0.0624
-#> 450: 92.8164 -5.9621 -0.1253 2.2821 -0.9655 0.5060 3.7632 0.3818 0.3346 0.1495 1.5470 0.0340 1.2704 0.0624
-#> 451: 92.8157 -5.9628 -0.1253 2.2822 -0.9655 0.5082 3.7655 0.3816 0.3346 0.1495 1.5469 0.0340 1.2699 0.0625
-#> 452: 92.8157 -5.9633 -0.1252 2.2824 -0.9656 0.5092 3.7657 0.3815 0.3346 0.1495 1.5468 0.0340 1.2691 0.0625
-#> 453: 92.8155 -5.9631 -0.1252 2.2823 -0.9657 0.5099 3.7646 0.3815 0.3347 0.1494 1.5470 0.0340 1.2684 0.0625
-#> 454: 92.8149 -5.9627 -0.1252 2.2823 -0.9656 0.5110 3.7623 0.3815 0.3347 0.1495 1.5470 0.0340 1.2678 0.0626
-#> 455: 92.8147 -5.9626 -0.1253 2.2822 -0.9656 0.5118 3.7610 0.3816 0.3347 0.1495 1.5471 0.0340 1.2675 0.0626
-#> 456: 92.8146 -5.9631 -0.1253 2.2821 -0.9657 0.5124 3.7612 0.3817 0.3348 0.1495 1.5473 0.0340 1.2684 0.0625
-#> 457: 92.8146 -5.9639 -0.1253 2.2820 -0.9658 0.5131 3.7636 0.3817 0.3347 0.1494 1.5471 0.0340 1.2683 0.0625
-#> 458: 92.8142 -5.9641 -0.1254 2.2818 -0.9658 0.5143 3.7637 0.3817 0.3347 0.1493 1.5472 0.0340 1.2679 0.0626
-#> 459: 92.8129 -5.9636 -0.1254 2.2818 -0.9660 0.5155 3.7609 0.3817 0.3347 0.1493 1.5474 0.0340 1.2692 0.0625
-#> 460: 92.8118 -5.9630 -0.1254 2.2817 -0.9660 0.5155 3.7563 0.3818 0.3347 0.1493 1.5476 0.0340 1.2703 0.0624
-#> 461: 92.8102 -5.9625 -0.1255 2.2816 -0.9661 0.5159 3.7525 0.3818 0.3347 0.1493 1.5478 0.0340 1.2711 0.0624
-#> 462: 92.8090 -5.9628 -0.1255 2.2814 -0.9661 0.5163 3.7520 0.3819 0.3347 0.1492 1.5481 0.0340 1.2708 0.0624
-#> 463: 92.8075 -5.9633 -0.1256 2.2813 -0.9660 0.5180 3.7534 0.3819 0.3347 0.1491 1.5484 0.0340 1.2705 0.0624
-#> 464: 92.8066 -5.9628 -0.1256 2.2812 -0.9659 0.5194 3.7507 0.3820 0.3347 0.1490 1.5485 0.0340 1.2702 0.0624
-#> 465: 92.8058 -5.9627 -0.1257 2.2811 -0.9658 0.5212 3.7506 0.3820 0.3347 0.1490 1.5484 0.0340 1.2696 0.0625
-#> 466: 92.8055 -5.9624 -0.1258 2.2808 -0.9656 0.5227 3.7510 0.3821 0.3347 0.1489 1.5487 0.0340 1.2704 0.0624
-#> 467: 92.8052 -5.9624 -0.1260 2.2805 -0.9656 0.5242 3.7518 0.3822 0.3346 0.1488 1.5488 0.0340 1.2715 0.0623
-#> 468: 92.8054 -5.9623 -0.1261 2.2803 -0.9654 0.5260 3.7545 0.3823 0.3346 0.1487 1.5493 0.0340 1.2730 0.0623
-#> 469: 92.8052 -5.9629 -0.1262 2.2803 -0.9654 0.5278 3.7617 0.3824 0.3346 0.1486 1.5495 0.0340 1.2737 0.0622
-#> 470: 92.8055 -5.9638 -0.1263 2.2802 -0.9653 0.5290 3.7667 0.3825 0.3347 0.1486 1.5494 0.0341 1.2729 0.0623
-#> 471: 92.8061 -5.9645 -0.1263 2.2801 -0.9653 0.5293 3.7702 0.3825 0.3347 0.1485 1.5494 0.0341 1.2724 0.0623
-#> 472: 92.8057 -5.9645 -0.1264 2.2800 -0.9653 0.5288 3.7699 0.3826 0.3347 0.1484 1.5495 0.0341 1.2728 0.0623
-#> 473: 92.8053 -5.9643 -0.1265 2.2799 -0.9652 0.5282 3.7701 0.3827 0.3347 0.1483 1.5494 0.0341 1.2721 0.0623
-#> 474: 92.8049 -5.9638 -0.1266 2.2798 -0.9653 0.5273 3.7676 0.3828 0.3347 0.1483 1.5495 0.0341 1.2722 0.0623
-#> 475: 92.8041 -5.9639 -0.1267 2.2796 -0.9654 0.5269 3.7668 0.3829 0.3347 0.1482 1.5495 0.0341 1.2721 0.0623
-#> 476: 92.8032 -5.9641 -0.1269 2.2794 -0.9653 0.5260 3.7681 0.3830 0.3347 0.1481 1.5496 0.0341 1.2716 0.0623
-#> 477: 92.8026 -5.9634 -0.1270 2.2792 -0.9653 0.5249 3.7647 0.3831 0.3347 0.1480 1.5500 0.0341 1.2716 0.0623
-#> 478: 92.8021 -5.9627 -0.1271 2.2789 -0.9653 0.5241 3.7606 0.3832 0.3346 0.1480 1.5500 0.0341 1.2718 0.0623
-#> 479: 92.8019 -5.9623 -0.1272 2.2787 -0.9654 0.5241 3.7581 0.3833 0.3345 0.1480 1.5502 0.0342 1.2714 0.0624
-#> 480: 92.8017 -5.9631 -0.1274 2.2784 -0.9654 0.5241 3.7606 0.3835 0.3344 0.1479 1.5503 0.0342 1.2711 0.0624
-#> 481: 92.8020 -5.9638 -0.1275 2.2781 -0.9654 0.5237 3.7659 0.3837 0.3343 0.1478 1.5508 0.0342 1.2720 0.0624
-#> 482: 92.8024 -5.9640 -0.1278 2.2777 -0.9654 0.5228 3.7668 0.3838 0.3342 0.1478 1.5512 0.0342 1.2729 0.0623
-#> 483: 92.8017 -5.9645 -0.1280 2.2773 -0.9654 0.5224 3.7676 0.3840 0.3341 0.1478 1.5515 0.0342 1.2741 0.0622
-#> 484: 92.8012 -5.9642 -0.1281 2.2771 -0.9653 0.5221 3.7649 0.3841 0.3340 0.1478 1.5521 0.0341 1.2747 0.0622
-#> 485: 92.8009 -5.9642 -0.1283 2.2769 -0.9653 0.5214 3.7635 0.3842 0.3339 0.1479 1.5523 0.0341 1.2752 0.0622
-#> 486: 92.8002 -5.9639 -0.1284 2.2767 -0.9652 0.5213 3.7609 0.3842 0.3339 0.1480 1.5523 0.0341 1.2760 0.0621
-#> 487: 92.7998 -5.9636 -0.1285 2.2767 -0.9652 0.5212 3.7603 0.3842 0.3339 0.1480 1.5525 0.0341 1.2762 0.0621
-#> 488: 92.7995 -5.9634 -0.1285 2.2766 -0.9652 0.5218 3.7592 0.3841 0.3339 0.1480 1.5530 0.0341 1.2773 0.0621
-#> 489: 92.7996 -5.9630 -0.1286 2.2765 -0.9653 0.5220 3.7578 0.3841 0.3339 0.1480 1.5532 0.0341 1.2778 0.0621
-#> 490: 92.8001 -5.9629 -0.1287 2.2764 -0.9652 0.5226 3.7573 0.3841 0.3339 0.1479 1.5533 0.0341 1.2788 0.0620
-#> 491: 92.8001 -5.9629 -0.1287 2.2762 -0.9651 0.5225 3.7568 0.3841 0.3338 0.1479 1.5533 0.0341 1.2790 0.0620
-#> 492: 92.8005 -5.9625 -0.1288 2.2761 -0.9651 0.5228 3.7544 0.3840 0.3339 0.1479 1.5536 0.0341 1.2797 0.0619
-#> 493: 92.8010 -5.9626 -0.1289 2.2759 -0.9651 0.5228 3.7544 0.3840 0.3339 0.1479 1.5537 0.0340 1.2795 0.0620
-#> 494: 92.8014 -5.9623 -0.1290 2.2757 -0.9651 0.5239 3.7523 0.3839 0.3340 0.1479 1.5540 0.0340 1.2790 0.0620
-#> 495: 92.8017 -5.9617 -0.1291 2.2755 -0.9652 0.5244 3.7491 0.3838 0.3341 0.1480 1.5540 0.0340 1.2787 0.0621
-#> 496: 92.8019 -5.9613 -0.1291 2.2754 -0.9652 0.5246 3.7459 0.3837 0.3341 0.1481 1.5539 0.0340 1.2802 0.0620
-#> 497: 92.8023 -5.9611 -0.1292 2.2753 -0.9653 0.5252 3.7447 0.3836 0.3340 0.1482 1.5539 0.0340 1.2814 0.0620
-#> 498: 92.8025 -5.9615 -0.1292 2.2752 -0.9653 0.5254 3.7446 0.3836 0.3339 0.1483 1.5539 0.0340 1.2825 0.0619
-#> 499: 92.8033 -5.9616 -0.1292 2.2751 -0.9654 0.5254 3.7447 0.3836 0.3338 0.1483 1.5538 0.0340 1.2834 0.0619
-#> 500: 92.8041 -5.9630 -0.1292 2.2752 -0.9655 0.5248 3.7529 0.3836 0.3337 0.1484 1.5538 0.0340 1.2841 0.0619
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 92.0624 -5.2854 0.1952 1.9494 -1.9431 2.8500 1.6150 0.7315 0.7220 0.4370 6.8425 0.4265 7.3797 0.5659
+#> 2: 92.7371 -5.3819 0.0345 2.0839 -2.0310 2.7075 1.5342 0.6949 0.8358 0.4151 7.2043 0.0003 8.1096 0.0003
+#> 3: 9.2941e+01 -5.7880e+00 1.0336e-01 2.5772e+00 -1.5152e+00 2.5721e+00 1.4575e+00 6.6018e-01 7.9403e-01 3.9439e-01 4.5749e+00 1.5986e-05 5.1354e+00 2.8796e-05
+#> 4: 92.6277 -5.8599 0.0858 2.5068 -1.3253 2.4435 1.3847 0.6272 0.7543 0.3747 3.4165 0.0001 3.9071 0.0016
+#> 5: 93.0289 -6.0258 0.0528 2.4932 -1.1961 2.3213 1.3154 0.5958 0.7166 0.3559 3.2552 0.0069 3.3744 0.0170
+#> 6: 93.2107 -6.2881 0.0143 2.4052 -1.1930 2.2053 2.2853 0.5660 0.6808 0.3381 2.8020 0.0086 3.1436 0.0256
+#> 7: 93.0563 -6.3624 -0.0104 2.3989 -1.1521 2.0950 2.4414 0.5377 0.6467 0.3212 2.6528 0.0209 2.8462 0.0289
+#> 8: 93.0567 -6.2699 -0.0303 2.3700 -1.0941 1.9903 2.5004 0.5204 0.6144 0.3052 2.3448 0.0314 2.5026 0.0349
+#> 9: 92.8366 -6.2013 -0.0507 2.3798 -1.0963 1.8907 2.6552 0.4943 0.5837 0.2899 2.2219 0.0368 2.2604 0.0448
+#> 10: 92.9069 -6.2499 -0.1116 2.3100 -1.0557 1.9625 3.9231 0.4696 0.5545 0.2754 2.0980 0.0359 2.1413 0.0325
+#> 11: 92.9942 -6.2134 -0.1037 2.3109 -1.0441 1.8643 3.7270 0.4755 0.5268 0.2616 1.9711 0.0372 1.9901 0.0355
+#> 12: 92.9262 -6.2511 -0.1133 2.2707 -1.0465 1.8430 4.3304 0.4697 0.5004 0.2486 1.8083 0.0346 1.9184 0.0356
+#> 13: 93.0761 -6.3559 -0.1106 2.2534 -1.0162 2.4826 5.2857 0.4685 0.4754 0.2361 1.7896 0.0331 1.9865 0.0342
+#> 14: 93.0929 -6.1852 -0.1058 2.2972 -1.0175 2.9964 5.0214 0.4451 0.4516 0.2243 1.8316 0.0309 1.9112 0.0348
+#> 15: 93.3343 -6.3408 -0.1025 2.2905 -0.9962 3.1132 4.9630 0.4594 0.4291 0.2131 1.8198 0.0338 1.9154 0.0372
+#> 16: 92.9959 -6.2227 -0.1016 2.2869 -1.0103 3.3338 4.7149 0.4598 0.4076 0.2025 1.8726 0.0327 1.9617 0.0361
+#> 17: 93.0394 -6.2586 -0.1027 2.2932 -0.9991 3.1671 4.8730 0.4591 0.3872 0.1923 1.8405 0.0336 2.0192 0.0242
+#> 18: 93.2374 -6.3410 -0.1110 2.2965 -0.9689 3.0087 5.4325 0.4632 0.3679 0.1827 1.9051 0.0351 1.9247 0.0277
+#> 19: 93.0557 -6.4503 -0.1011 2.2941 -0.9884 2.8583 6.2872 0.4742 0.3495 0.1736 1.8054 0.0345 1.9173 0.0260
+#> 20: 92.9280 -6.4945 -0.1018 2.2902 -0.9864 3.5934 6.8737 0.4751 0.3320 0.1649 1.7097 0.0372 1.9483 0.0225
+#> 21: 93.2023 -6.3418 -0.1033 2.2846 -0.9863 3.4138 6.5300 0.4710 0.3154 0.1567 1.7507 0.0318 1.9030 0.0249
+#> 22: 93.5494 -6.1985 -0.1078 2.2991 -1.0171 3.2431 6.2035 0.4475 0.2996 0.1488 1.7370 0.0342 1.8124 0.0282
+#> 23: 93.3588 -6.2577 -0.1084 2.2654 -0.9956 3.0809 5.8933 0.4393 0.2869 0.1481 1.6928 0.0380 1.8288 0.0254
+#> 24: 93.5705 -6.4876 -0.1083 2.2606 -1.0062 3.7095 6.7801 0.4459 0.2726 0.1684 1.7001 0.0377 1.9012 0.0249
+#> 25: 93.9726 -6.5638 -0.1239 2.2374 -1.0071 5.1357 6.6571 0.4608 0.2755 0.1600 1.6615 0.0382 1.8846 0.0213
+#> 26: 93.8894 -6.5073 -0.1120 2.2645 -1.0327 4.8789 6.3243 0.4473 0.3014 0.1520 1.7152 0.0340 1.8990 0.0254
+#> 27: 94.5348 -6.3868 -0.0891 2.3139 -1.0361 5.3856 6.0081 0.4250 0.3080 0.1453 1.7028 0.0385 1.7853 0.0304
+#> 28: 93.9221 -6.1747 -0.1039 2.3013 -1.0087 5.1163 5.7077 0.4214 0.3136 0.1634 1.6823 0.0340 1.7487 0.0353
+#> 29: 93.4946 -6.0264 -0.0940 2.3124 -1.0166 5.3744 5.4223 0.4404 0.3114 0.1813 1.6310 0.0370 1.7646 0.0367
+#> 30: 93.9287 -5.9114 -0.0967 2.3078 -1.0090 5.2017 5.1512 0.4381 0.3048 0.2091 1.5825 0.0393 1.7431 0.0312
+#> 31: 93.7065 -6.0174 -0.0928 2.2917 -0.9880 5.1935 4.8936 0.4352 0.3109 0.1986 1.5876 0.0392 1.8465 0.0280
+#> 32: 93.7675 -5.6444 -0.0918 2.3145 -0.9664 4.9338 4.6489 0.4332 0.3090 0.1918 1.6874 0.0332 1.7501 0.0331
+#> 33: 94.2589 -5.7637 -0.0865 2.3130 -0.9733 4.6871 4.4165 0.4235 0.2935 0.1865 1.7173 0.0355 1.7365 0.0334
+#> 34: 94.0788 -5.7432 -0.1022 2.3049 -0.9681 4.4528 4.1957 0.4319 0.2962 0.1772 1.6357 0.0361 1.4755 0.0574
+#> 35: 94.0798 -5.8549 -0.0929 2.2856 -0.9849 4.2301 3.9859 0.4391 0.2937 0.1734 1.6460 0.0275 1.7739 0.0379
+#> 36: 93.9997 -5.8708 -0.0890 2.2870 -1.0134 4.0186 3.7866 0.4268 0.2819 0.1840 1.5830 0.0258 1.8922 0.0320
+#> 37: 93.8186 -5.8979 -0.0973 2.2807 -1.0197 3.8177 3.5973 0.4280 0.2778 0.1799 1.5783 0.0282 1.7697 0.0404
+#> 38: 94.0728 -5.9601 -0.0936 2.3011 -1.0381 3.6268 3.4174 0.4186 0.2944 0.1864 1.5780 0.0294 1.5210 0.0558
+#> 39: 94.0504 -5.8302 -0.0995 2.2847 -1.0418 3.4455 3.2465 0.4240 0.2796 0.1771 1.6888 0.0242 1.7744 0.0366
+#> 40: 93.8918 -5.9418 -0.0988 2.2925 -1.0613 3.2732 3.0842 0.4144 0.2672 0.1837 1.7275 0.0232 1.7840 0.0357
+#> 41: 93.7961 -6.0741 -0.0896 2.2932 -1.0359 3.1095 3.2890 0.4236 0.2606 0.1782 1.7591 0.0212 1.8920 0.0273
+#> 42: 93.9458 -6.0319 -0.0909 2.3114 -1.0281 3.0544 3.1246 0.4196 0.2598 0.1839 1.6854 0.0310 1.7586 0.0308
+#> 43: 93.7623 -6.0165 -0.1056 2.2837 -1.0378 3.9092 3.2100 0.4298 0.2468 0.1747 1.7064 0.0286 1.6676 0.0397
+#> 44: 93.4300 -5.9019 -0.1114 2.2716 -1.0167 4.4100 3.0495 0.4476 0.2345 0.1687 1.7989 0.0253 1.7741 0.0299
+#> 45: 93.3475 -5.9962 -0.1231 2.2546 -1.0007 6.4879 3.3965 0.4528 0.2452 0.1602 1.7283 0.0276 1.7219 0.0379
+#> 46: 93.3100 -6.0073 -0.1255 2.2483 -0.9962 6.6009 3.5942 0.4520 0.2533 0.1568 1.6991 0.0258 1.1783 0.0706
+#> 47: 93.4422 -5.8442 -0.1286 2.2578 -0.9819 6.2709 3.4145 0.4492 0.2637 0.1694 1.6754 0.0317 1.3442 0.0599
+#> 48: 93.0996 -5.5881 -0.1307 2.2541 -0.9882 5.9573 3.2438 0.4480 0.2665 0.1695 1.7040 0.0285 1.6825 0.0426
+#> 49: 93.3649 -5.8011 -0.1260 2.2595 -0.9704 5.7230 3.0816 0.4399 0.2646 0.1715 1.6544 0.0297 1.6414 0.0418
+#> 50: 93.9331 -5.8731 -0.1195 2.2615 -0.9837 5.4368 2.9275 0.4453 0.2735 0.1940 1.6316 0.0289 1.6885 0.0392
+#> 51: 93.6092 -5.8721 -0.1237 2.2599 -1.0015 5.1650 2.7811 0.4413 0.2865 0.1939 1.6492 0.0272 1.7686 0.0358
+#> 52: 93.3008 -5.9775 -0.1277 2.2628 -0.9962 4.9067 3.1139 0.4438 0.2946 0.1963 1.5642 0.0337 1.7391 0.0335
+#> 53: 93.6347 -6.0805 -0.1189 2.2663 -1.0177 4.6614 3.5169 0.4335 0.2962 0.2043 1.5275 0.0343 1.7417 0.0366
+#> 54: 93.5781 -6.0412 -0.1166 2.2573 -1.0015 4.4283 3.3411 0.4395 0.2912 0.2080 1.5464 0.0346 1.7584 0.0359
+#> 55: 93.9675 -6.0867 -0.0952 2.2970 -0.9987 4.2069 3.6762 0.4550 0.2780 0.1988 1.5138 0.0405 1.6251 0.0472
+#> 56: 94.4069 -6.1375 -0.0943 2.2975 -1.0190 3.9966 4.2280 0.4550 0.2806 0.1945 1.5294 0.0425 1.6443 0.0468
+#> 57: 93.8076 -6.1618 -0.0936 2.2687 -1.0237 3.7967 4.3085 0.4524 0.2666 0.1897 1.5227 0.0414 1.6955 0.0438
+#> 58: 93.9188 -6.2272 -0.0947 2.2767 -1.0408 3.6069 4.6707 0.4536 0.2676 0.1873 1.5201 0.0425 1.5336 0.0550
+#> 59: 93.9572 -6.3460 -0.1074 2.2746 -1.0069 3.4266 5.8058 0.4614 0.2718 0.1919 1.5533 0.0417 1.6227 0.0460
+#> 60: 93.5430 -6.1622 -0.1048 2.2861 -0.9959 3.2552 5.5155 0.4535 0.2848 0.1823 1.4745 0.0431 1.5242 0.0522
+#> 61: 93.8016 -6.4079 -0.1065 2.2897 -1.0325 3.0925 5.9252 0.4583 0.2901 0.1732 1.5364 0.0365 1.4623 0.0550
+#> 62: 93.4249 -6.2284 -0.0967 2.3126 -1.0208 2.9378 5.6289 0.4429 0.2756 0.1645 1.6111 0.0325 1.3996 0.0618
+#> 63: 93.2335 -6.0996 -0.1051 2.3047 -0.9976 2.7909 5.3475 0.4292 0.2719 0.1633 1.6010 0.0326 1.5115 0.0494
+#> 64: 92.7091 -6.1109 -0.1041 2.3032 -0.9746 3.2610 5.0801 0.4301 0.2793 0.1751 1.5979 0.0302 1.3867 0.0575
+#> 65: 92.6059 -6.0049 -0.1077 2.3062 -0.9853 3.0979 4.8261 0.4316 0.2826 0.1714 1.6357 0.0272 1.3931 0.0543
+#> 66: 92.7778 -6.0856 -0.1040 2.3057 -0.9828 2.9430 4.5848 0.4362 0.2888 0.1628 1.6126 0.0316 1.4340 0.0505
+#> 67: 93.0325 -6.1775 -0.1085 2.3122 -0.9714 2.7959 4.3790 0.4464 0.2843 0.1547 1.6090 0.0354 1.4966 0.0448
+#> 68: 92.8987 -5.8741 -0.1089 2.3184 -0.9567 2.6561 4.1601 0.4389 0.2866 0.1470 1.5888 0.0347 1.4492 0.0507
+#> 69: 92.7300 -6.0473 -0.1070 2.3082 -0.9739 2.5233 4.0183 0.4371 0.3158 0.1527 1.5904 0.0298 1.5387 0.0477
+#> 70: 92.5285 -6.0962 -0.1115 2.3179 -0.9785 2.4856 4.0612 0.4380 0.3059 0.1504 1.5237 0.0402 1.4541 0.0463
+#> 71: 92.3975 -6.2090 -0.1269 2.2819 -0.9713 2.3613 4.3811 0.4173 0.2906 0.1520 1.5388 0.0316 1.3713 0.0584
+#> 72: 92.1593 -6.2214 -0.1217 2.2950 -0.9481 2.2433 5.1205 0.4227 0.2760 0.1605 1.5431 0.0312 1.5797 0.0459
+#> 73: 92.1195 -6.6667 -0.1244 2.3076 -0.9642 2.1311 7.6538 0.4124 0.2622 0.1525 1.4505 0.0375 1.2810 0.0595
+#> 74: 92.2191 -6.6665 -0.1278 2.2989 -0.9703 2.0246 7.2711 0.4098 0.2491 0.1666 1.4309 0.0384 1.2717 0.0638
+#> 75: 92.4656 -6.8881 -0.1274 2.3011 -0.9595 1.9233 8.3835 0.4147 0.2367 0.1656 1.4181 0.0424 1.2498 0.0620
+#> 76: 92.4593 -6.2323 -0.1203 2.2912 -0.9799 1.8272 7.9643 0.3967 0.2301 0.1596 1.5448 0.0336 1.6758 0.0359
+#> 77: 92.4501 -6.1123 -0.1219 2.2889 -0.9426 1.7358 7.5661 0.4049 0.2299 0.1594 1.5380 0.0327 1.6947 0.0364
+#> 78: 92.5059 -6.0339 -0.1198 2.2985 -0.9544 1.6490 7.1878 0.4007 0.2422 0.1568 1.5722 0.0302 1.5665 0.0415
+#> 79: 92.4302 -6.6428 -0.1141 2.3119 -0.9421 1.5666 9.0889 0.3986 0.2340 0.1489 1.5029 0.0306 1.1894 0.0638
+#> 80: 92.5305 -6.3036 -0.1127 2.3099 -0.9406 1.9062 8.6344 0.4091 0.2327 0.1648 1.5558 0.0308 1.0136 0.0749
+#> 81: 92.6652 -6.0832 -0.1167 2.2994 -0.9552 2.3641 8.2027 0.4142 0.2348 0.1566 1.6232 0.0300 1.1320 0.0712
+#> 82: 92.5109 -6.1524 -0.1100 2.3037 -0.9686 2.2459 7.7926 0.4145 0.2381 0.1695 1.6128 0.0306 1.6145 0.0413
+#> 83: 92.6455 -6.3979 -0.1059 2.3245 -0.9573 2.1336 8.1077 0.4060 0.2348 0.1667 1.6039 0.0304 1.6251 0.0419
+#> 84: 92.5768 -6.3469 -0.0979 2.3177 -0.9346 2.0269 8.2125 0.4141 0.2439 0.1720 1.6334 0.0302 1.5803 0.0450
+#> 85: 92.7920 -6.3536 -0.0969 2.3363 -0.9389 1.9256 8.1820 0.4035 0.2512 0.1713 1.5815 0.0338 1.1193 0.0719
+#> 86: 92.8571 -6.2567 -0.0911 2.3426 -0.9633 1.8293 8.1211 0.4008 0.2659 0.1627 1.5840 0.0356 1.2425 0.0639
+#> 87: 92.9101 -6.1557 -0.0937 2.3326 -0.9624 1.7378 7.7151 0.3950 0.2839 0.1546 1.6017 0.0354 1.0600 0.0766
+#> 88: 92.7649 -6.2151 -0.0881 2.3275 -0.9967 1.6509 7.3293 0.4046 0.2697 0.1469 1.6092 0.0302 1.1839 0.0693
+#> 89: 92.9350 -5.9222 -0.0903 2.3372 -0.9612 1.5684 6.9628 0.4058 0.2818 0.1395 1.5957 0.0335 1.5450 0.0444
+#> 90: 92.7895 -5.9348 -0.0890 2.3457 -0.9601 1.4900 6.6147 0.4070 0.2705 0.1430 1.5716 0.0378 1.4918 0.0439
+#> 91: 93.0113 -5.9302 -0.0997 2.3316 -0.9489 1.4155 6.2840 0.4424 0.2929 0.1410 1.5582 0.0377 1.2459 0.0582
+#> 92: 92.8603 -6.3366 -0.0918 2.3356 -0.9938 1.3447 5.9698 0.4287 0.2929 0.1531 1.4906 0.0398 1.2421 0.0605
+#> 93: 92.8094 -6.1097 -0.0953 2.3382 -0.9996 1.2775 5.6713 0.4309 0.2783 0.1597 1.4317 0.0468 1.2694 0.0584
+#> 94: 92.7100 -6.1043 -0.0909 2.3287 -0.9928 1.3828 5.3877 0.4337 0.2698 0.1517 1.4173 0.0489 1.4335 0.0476
+#> 95: 92.2055 -6.1792 -0.0889 2.3553 -0.9983 1.3137 5.1183 0.4209 0.3273 0.1566 1.4865 0.0417 1.2485 0.0681
+#> 96: 92.3225 -6.2710 -0.0811 2.3734 -1.0043 1.3428 4.8624 0.4121 0.3110 0.1532 1.5817 0.0374 1.5209 0.0532
+#> 97: 92.2983 -6.3023 -0.0776 2.3615 -0.9801 1.2757 4.6193 0.4221 0.3018 0.1455 1.5971 0.0337 1.2137 0.0719
+#> 98: 92.1433 -6.3114 -0.0935 2.3269 -0.9866 1.2227 4.8121 0.4327 0.2907 0.1694 1.5524 0.0303 1.1779 0.0727
+#> 99: 92.1631 -6.3090 -0.0908 2.3197 -0.9891 1.1615 4.9271 0.4169 0.2859 0.1736 1.5303 0.0334 1.6227 0.0511
+#> 100: 92.1185 -6.3603 -0.0950 2.3280 -1.0209 1.1035 5.0957 0.4213 0.2924 0.1817 1.5991 0.0330 1.7197 0.0445
+#> 101: 92.3964 -6.0447 -0.0898 2.3347 -1.0164 1.0483 4.8409 0.4251 0.2778 0.1727 1.5708 0.0422 1.6197 0.0461
+#> 102: 92.6597 -6.2545 -0.0954 2.3264 -1.0206 0.9959 4.5989 0.4218 0.2736 0.1640 1.5853 0.0408 1.5912 0.0455
+#> 103: 92.7866 -6.3292 -0.0933 2.3148 -1.0013 0.9461 4.8935 0.4234 0.2599 0.1688 1.6299 0.0399 1.5921 0.0445
+#> 104: 92.8098 -6.2608 -0.1009 2.3014 -0.9947 0.8988 4.7750 0.4306 0.2548 0.1813 1.6363 0.0378 1.6713 0.0427
+#> 105: 92.8300 -5.9827 -0.1028 2.3155 -0.9896 0.8538 4.5362 0.4339 0.2664 0.1722 1.6079 0.0397 1.3691 0.0573
+#> 106: 92.8218 -6.1138 -0.1024 2.3462 -0.9750 0.8299 4.3094 0.4494 0.2530 0.1636 1.5761 0.0389 1.2857 0.0595
+#> 107: 92.9304 -6.0063 -0.1002 2.3269 -0.9778 0.7884 4.0939 0.4600 0.2404 0.1620 1.6499 0.0373 1.2101 0.0675
+#> 108: 92.9072 -6.0928 -0.0991 2.3183 -0.9732 0.7489 4.4394 0.4584 0.2518 0.1539 1.6509 0.0332 1.2346 0.0670
+#> 109: 92.7504 -6.1545 -0.0862 2.3423 -0.9618 0.7115 4.7501 0.4371 0.2766 0.1465 1.5755 0.0349 1.1552 0.0701
+#> 110: 92.9277 -6.3786 -0.0904 2.3468 -0.9402 0.6759 5.8620 0.4328 0.2821 0.1703 1.4661 0.0439 1.3292 0.0609
+#> 111: 92.8023 -5.8686 -0.0886 2.3653 -0.9417 0.7635 5.5689 0.4288 0.2680 0.1618 1.4278 0.0502 1.4715 0.0468
+#> 112: 92.9411 -5.8095 -0.0883 2.3625 -0.9322 0.8592 5.2905 0.4562 0.2586 0.1537 1.3920 0.0513 1.1766 0.0648
+#> 113: 92.9845 -6.0499 -0.0761 2.3626 -0.9533 0.8163 5.0259 0.4403 0.2595 0.1532 1.4306 0.0450 1.1416 0.0645
+#> 114: 92.7735 -6.0605 -0.0694 2.3497 -0.9646 0.7754 4.7746 0.4394 0.2682 0.1576 1.4866 0.0344 1.1127 0.0745
+#> 115: 92.7048 -6.1327 -0.0702 2.3427 -0.9910 0.7367 4.5359 0.4257 0.2736 0.1497 1.5045 0.0413 1.2783 0.0677
+#> 116: 92.7131 -6.0115 -0.0751 2.3370 -0.9899 0.6998 4.3091 0.4187 0.2638 0.1422 1.6036 0.0325 1.1109 0.0748
+#> 117: 92.7720 -5.9163 -0.0709 2.3503 -0.9566 0.6648 4.0937 0.4185 0.2555 0.1417 1.6016 0.0297 1.0778 0.0774
+#> 118: 92.9182 -5.9312 -0.0812 2.3436 -0.9731 0.6316 3.8890 0.4084 0.2667 0.1400 1.5698 0.0320 1.2364 0.0665
+#> 119: 92.9546 -5.9622 -0.0870 2.3330 -0.9934 0.6000 3.6945 0.4035 0.2867 0.1486 1.5364 0.0343 1.5892 0.0489
+#> 120: 92.9168 -6.0966 -0.0905 2.3301 -1.0045 0.5700 3.6677 0.3988 0.2871 0.1567 1.5378 0.0349 1.0886 0.0796
+#> 121: 92.7767 -6.1038 -0.0802 2.3396 -0.9815 0.5981 4.3032 0.3803 0.2884 0.1684 1.4788 0.0335 1.0886 0.0796
+#> 122: 92.8439 -6.2425 -0.0799 2.3323 -0.9987 0.6537 4.5745 0.3884 0.2834 0.1600 1.4786 0.0346 1.2146 0.0682
+#> 123: 92.8219 -5.7869 -0.0872 2.3478 -0.9619 0.7886 4.3458 0.3951 0.2887 0.1658 1.4827 0.0341 1.3911 0.0559
+#> 124: 92.7930 -5.7551 -0.0819 2.3559 -0.9809 0.8922 4.1285 0.3907 0.2972 0.1575 1.5329 0.0330 1.3824 0.0594
+#> 125: 92.7488 -5.9406 -0.0819 2.3550 -0.9797 0.8476 3.9221 0.3907 0.2996 0.1733 1.5096 0.0333 1.3148 0.0667
+#> 126: 92.7926 -5.7106 -0.0824 2.3560 -0.9653 0.8052 3.7260 0.3918 0.3018 0.1854 1.4237 0.0381 1.2607 0.0639
+#> 127: 92.9153 -5.6682 -0.0717 2.3654 -0.9645 0.7649 3.5397 0.3722 0.2948 0.1784 1.4679 0.0415 1.2310 0.0695
+#> 128: 92.8827 -5.7984 -0.0783 2.3813 -1.0047 1.1012 3.3627 0.3802 0.2997 0.1694 1.5187 0.0442 1.2884 0.0649
+#> 129: 92.8727 -5.7191 -0.0785 2.3426 -0.9857 1.0461 3.1946 0.3784 0.2984 0.1610 1.4757 0.0398 1.1695 0.0775
+#> 130: 92.8689 -5.8036 -0.0935 2.3123 -0.9783 0.9938 3.0348 0.4184 0.2980 0.1723 1.5143 0.0319 1.2298 0.0738
+#> 131: 92.8733 -5.6707 -0.0988 2.3045 -0.9936 1.3313 2.8831 0.4277 0.2831 0.1816 1.5919 0.0329 1.5260 0.0533
+#> 132: 92.5761 -5.7773 -0.0925 2.3211 -0.9661 1.2647 2.7389 0.4216 0.2815 0.1995 1.5306 0.0321 1.5863 0.0520
+#> 133: 92.4512 -5.7800 -0.0920 2.3269 -0.9625 1.2015 2.6020 0.4242 0.2674 0.1955 1.5669 0.0288 1.4087 0.0606
+#> 134: 92.5625 -5.7968 -0.0965 2.3271 -0.9728 1.1414 2.4719 0.4201 0.2753 0.1945 1.5935 0.0311 1.5348 0.0534
+#> 135: 92.3448 -5.6624 -0.0961 2.3303 -0.9600 1.0843 2.3483 0.4193 0.2728 0.1983 1.6245 0.0305 1.6281 0.0506
+#> 136: 92.3407 -5.7523 -0.0932 2.3208 -0.9897 1.0301 2.3267 0.4107 0.2668 0.1884 1.5933 0.0358 1.2970 0.0657
+#> 137: 92.3940 -6.0148 -0.1046 2.2981 -0.9866 0.9786 3.1382 0.4166 0.3012 0.1790 1.5077 0.0385 1.1944 0.0723
+#> 138: 92.3556 -5.9912 -0.1039 2.2969 -0.9920 0.9297 3.2144 0.4208 0.3039 0.1703 1.5042 0.0378 1.2588 0.0717
+#> 139: 92.5548 -5.9253 -0.1177 2.2723 -1.0079 0.8832 3.2648 0.4049 0.3263 0.1618 1.5558 0.0382 1.2673 0.0698
+#> 140: 92.6546 -6.0596 -0.1368 2.2659 -0.9922 0.8390 3.3893 0.3846 0.3100 0.1537 1.5475 0.0355 1.3190 0.0629
+#> 141: 92.6661 -5.9744 -0.1379 2.2793 -0.9754 0.8287 3.2725 0.3800 0.3178 0.1528 1.5076 0.0361 1.4087 0.0540
+#> 142: 92.5681 -5.7650 -0.1033 2.3249 -0.9613 0.7872 3.1089 0.3610 0.3564 0.1701 1.4733 0.0332 1.2603 0.0720
+#> 143: 92.4184 -5.6070 -0.1033 2.3520 -0.9764 0.7479 2.9534 0.3591 0.3758 0.1674 1.5420 0.0390 1.3280 0.0614
+#> 144: 92.5354 -5.6144 -0.0978 2.3801 -0.9425 0.7105 2.8058 0.3538 0.3606 0.1722 1.4884 0.0400 1.3455 0.0620
+#> 145: 92.4207 -5.6541 -0.0746 2.3873 -0.9633 0.6750 2.6655 0.3361 0.3426 0.1718 1.4981 0.0416 1.2440 0.0685
+#> 146: 92.3058 -5.6608 -0.0731 2.3755 -0.9732 0.6412 2.5322 0.3193 0.3304 0.1719 1.6391 0.0348 1.1788 0.0743
+#> 147: 92.4067 -5.7615 -0.0746 2.3775 -0.9903 0.6091 2.4056 0.3148 0.3311 0.1709 1.6695 0.0314 1.2931 0.0676
+#> 148: 92.3739 -5.8812 -0.0820 2.3644 -0.9823 0.5787 2.7260 0.3332 0.3296 0.1794 1.6168 0.0303 1.3206 0.0670
+#> 149: 92.4456 -5.8277 -0.0921 2.3508 -0.9924 0.5498 2.8750 0.3368 0.3305 0.1917 1.5602 0.0302 1.3622 0.0608
+#> 150: 92.5049 -5.7964 -0.1003 2.3353 -0.9809 0.5223 2.7312 0.3291 0.3634 0.1874 1.5035 0.0301 1.4002 0.0615
+#> 151: 92.3292 -6.0377 -0.1039 2.3301 -0.9866 0.4962 3.3342 0.3348 0.3626 0.1780 1.4819 0.0298 1.3217 0.0672
+#> 152: 92.3747 -6.0460 -0.1023 2.3154 -1.0242 0.5079 3.4530 0.3371 0.3518 0.1674 1.6034 0.0296 1.2304 0.0749
+#> 153: 92.3909 -5.8707 -0.1008 2.3284 -0.9897 0.5623 2.8180 0.3480 0.3792 0.1749 1.4953 0.0291 1.3442 0.0677
+#> 154: 92.2532 -5.9313 -0.0991 2.3232 -0.9839 0.5340 3.3946 0.3502 0.3723 0.1729 1.4837 0.0280 1.1452 0.0776
+#> 155: 92.1782 -6.1012 -0.0988 2.3339 -0.9600 0.3900 3.9676 0.3593 0.3704 0.1531 1.4927 0.0286 1.1848 0.0730
+#> 156: 92.2225 -5.8387 -0.0991 2.3393 -0.9459 0.3294 3.0685 0.3598 0.3808 0.1568 1.5540 0.0318 1.3419 0.0671
+#> 157: 92.2411 -5.7045 -0.1038 2.3578 -0.9252 0.2797 2.5238 0.3716 0.3579 0.1653 1.4704 0.0373 1.1959 0.0686
+#> 158: 92.2865 -5.6692 -0.1009 2.3771 -0.9532 0.2840 2.4144 0.3592 0.3610 0.1641 1.5065 0.0389 1.1780 0.0674
+#> 159: 92.2771 -5.7526 -0.0782 2.3632 -0.9771 0.2996 2.7295 0.3357 0.3779 0.1606 1.5818 0.0366 1.1512 0.0781
+#> 160: 92.3400 -5.8039 -0.0811 2.3615 -0.9453 0.2707 2.7305 0.3373 0.3834 0.1528 1.4765 0.0370 1.1427 0.0756
+#> 161: 92.4180 -5.7448 -0.0961 2.3653 -0.9508 0.2965 2.6051 0.3666 0.3833 0.1647 1.4581 0.0364 0.9817 0.0827
+#> 162: 92.4487 -5.8952 -0.0889 2.3460 -0.9646 0.2370 3.1413 0.3460 0.3801 0.1571 1.4528 0.0346 1.0006 0.0798
+#> 163: 92.5251 -5.8567 -0.0987 2.3342 -0.9615 0.1453 2.9917 0.3535 0.3735 0.1452 1.4521 0.0330 1.0498 0.0766
+#> 164: 92.5949 -6.1580 -0.1008 2.3332 -0.9749 0.1095 4.1797 0.3586 0.3767 0.1355 1.4659 0.0310 1.0218 0.0797
+#> 165: 92.5794 -6.0542 -0.1001 2.3321 -0.9795 0.1332 4.2924 0.3588 0.3752 0.1386 1.4858 0.0313 0.9836 0.0812
+#> 166: 92.6686 -6.0065 -0.0960 2.3623 -0.9532 0.1465 4.0810 0.3439 0.3683 0.1647 1.3929 0.0372 0.9354 0.0837
+#> 167: 92.7086 -6.2096 -0.0895 2.3656 -0.9552 0.1938 4.6857 0.3325 0.3519 0.1681 1.4281 0.0362 1.0329 0.0784
+#> 168: 92.6096 -6.0709 -0.0880 2.3595 -0.9474 0.2141 4.1277 0.3379 0.3527 0.1620 1.4264 0.0347 0.9627 0.0836
+#> 169: 92.5365 -5.9418 -0.0919 2.3546 -0.9575 0.3620 3.7767 0.3489 0.3589 0.1609 1.4761 0.0360 1.1348 0.0745
+#> 170: 92.6270 -5.8404 -0.0935 2.3562 -0.9517 0.3312 3.2506 0.3552 0.3607 0.1560 1.4506 0.0383 1.0731 0.0722
+#> 171: 92.5606 -5.9213 -0.0899 2.3513 -0.9554 0.4399 3.5587 0.3599 0.3646 0.1385 1.4779 0.0349 0.9844 0.0775
+#> 172: 92.3630 -5.7066 -0.0765 2.3798 -0.9314 0.5208 2.5578 0.3458 0.3657 0.1547 1.4900 0.0348 1.0485 0.0765
+#> 173: 92.2527 -5.5811 -0.0713 2.4173 -0.9221 0.8674 2.2100 0.3448 0.3370 0.1513 1.5403 0.0445 1.4403 0.0518
+#> 174: 92.3852 -5.5348 -0.0712 2.4066 -0.9033 0.7543 2.1568 0.3457 0.3324 0.1482 1.5322 0.0407 1.2744 0.0623
+#> 175: 92.4798 -5.5494 -0.0712 2.4004 -0.9100 0.5675 2.0147 0.3457 0.3333 0.1629 1.5229 0.0383 1.2917 0.0655
+#> 176: 92.5881 -5.5613 -0.0675 2.4180 -0.9188 0.4011 2.0736 0.3413 0.3487 0.1781 1.5149 0.0389 1.1499 0.0669
+#> 177: 92.6015 -5.4951 -0.0494 2.4324 -0.9525 0.4992 1.9009 0.3629 0.3353 0.1919 1.4881 0.0393 1.2289 0.0650
+#> 178: 92.6317 -5.4943 -0.0505 2.4373 -0.9298 0.5087 1.6116 0.3631 0.3324 0.1906 1.4475 0.0454 1.0764 0.0701
+#> 179: 92.7043 -5.5326 -0.0419 2.4386 -0.9376 0.4350 1.8241 0.3577 0.3757 0.1991 1.4445 0.0424 0.9626 0.0833
+#> 180: 92.7457 -5.5591 -0.0371 2.4684 -0.9450 0.3973 1.7797 0.3507 0.3707 0.1944 1.4392 0.0415 1.0784 0.0764
+#> 181: 92.6287 -5.5741 -0.0368 2.4489 -0.9459 0.4744 1.8016 0.3502 0.3544 0.1970 1.4317 0.0392 0.9225 0.0848
+#> 182: 92.6121 -5.5593 -0.0316 2.4610 -0.9345 0.6054 1.9206 0.3492 0.3538 0.1855 1.4410 0.0367 0.8977 0.0878
+#> 183: 92.4258 -5.4737 -0.0393 2.4592 -0.9319 0.8062 1.7845 0.3528 0.3544 0.1649 1.4545 0.0409 1.0723 0.0751
+#> 184: 92.3939 -5.5961 -0.0479 2.4268 -0.9435 1.0246 2.2534 0.3497 0.3289 0.1363 1.5022 0.0370 1.1058 0.0729
+#> 185: 92.4673 -5.5415 -0.0525 2.4157 -0.9058 0.8296 2.2848 0.3406 0.3314 0.1706 1.4935 0.0367 1.1362 0.0722
+#> 186: 92.4122 -5.6594 -0.0574 2.4466 -0.9430 0.9133 2.3350 0.3327 0.3596 0.1506 1.4450 0.0404 1.2273 0.0629
+#> 187: 92.5416 -5.5472 -0.0521 2.4393 -0.9261 0.9731 1.9228 0.3208 0.3673 0.1421 1.4890 0.0409 1.2553 0.0626
+#> 188: 92.5502 -5.6425 -0.0591 2.4345 -0.9246 0.9315 2.2041 0.3184 0.3639 0.1319 1.4896 0.0392 1.0986 0.0684
+#> 189: 92.4180 -5.6737 -0.0504 2.4448 -0.9191 0.9006 2.4647 0.3102 0.3743 0.1648 1.4649 0.0397 1.1320 0.0742
+#> 190: 92.5821 -5.5823 -0.0363 2.4588 -0.9205 0.9862 2.2692 0.2820 0.4087 0.1459 1.3938 0.0412 0.9562 0.0815
+#> 191: 92.3708 -5.5825 -0.0418 2.4621 -0.9231 0.9867 2.4743 0.2890 0.4196 0.1445 1.4619 0.0403 0.9630 0.0811
+#> 192: 92.2628 -5.5337 -0.0366 2.4392 -0.9194 0.6944 2.2771 0.2909 0.4169 0.1279 1.4745 0.0363 0.8601 0.0892
+#> 193: 92.4854 -5.6303 -0.0352 2.4484 -0.9316 0.4403 2.3253 0.2928 0.4109 0.1282 1.4768 0.0399 0.8886 0.0871
+#> 194: 92.4900 -5.5824 -0.0372 2.4648 -0.9451 0.4891 2.6428 0.2899 0.4160 0.1331 1.5124 0.0412 0.9340 0.0853
+#> 195: 92.4685 -5.7658 -0.0357 2.4659 -0.9217 0.4549 3.3767 0.2921 0.4171 0.1552 1.5062 0.0396 1.0336 0.0817
+#> 196: 92.4125 -5.7544 -0.0255 2.4834 -0.9230 0.4146 3.1963 0.3000 0.4369 0.1501 1.4560 0.0430 0.9942 0.0813
+#> 197: 92.3284 -5.9347 -0.0305 2.4860 -0.9448 0.4115 3.5642 0.3129 0.4314 0.1740 1.3441 0.0473 1.0954 0.0723
+#> 198: 92.3428 -5.9255 -0.0266 2.4822 -0.9463 0.3258 3.4818 0.3185 0.4163 0.1716 1.3868 0.0447 0.9452 0.0788
+#> 199: 92.1692 -6.0683 -0.0227 2.4860 -0.9495 0.2685 4.4044 0.3149 0.4064 0.1824 1.3558 0.0478 1.0294 0.0749
+#> 200: 92.0965 -6.1541 -0.0261 2.4793 -0.9288 0.2210 4.4026 0.3265 0.4200 0.1772 1.3348 0.0441 1.0018 0.0761
+#> 201: 92.1362 -6.1170 -0.0244 2.4776 -0.9237 0.1801 4.4160 0.3276 0.4303 0.1732 1.3479 0.0418 0.9419 0.0809
+#> 202: 92.1114 -6.0898 -0.0233 2.4862 -0.9253 0.1506 4.4494 0.3286 0.4305 0.1656 1.3473 0.0440 0.9394 0.0802
+#> 203: 92.0893 -6.1307 -0.0233 2.4894 -0.9258 0.1510 4.7958 0.3310 0.4233 0.1673 1.3396 0.0457 0.9617 0.0788
+#> 204: 92.0870 -6.0914 -0.0230 2.4867 -0.9234 0.1589 4.6265 0.3316 0.4237 0.1643 1.3478 0.0456 0.9509 0.0793
+#> 205: 92.0800 -6.0960 -0.0228 2.4867 -0.9256 0.1613 4.6319 0.3321 0.4226 0.1623 1.3399 0.0463 0.9547 0.0789
+#> 206: 92.1037 -6.0869 -0.0238 2.4833 -0.9264 0.1648 4.5547 0.3341 0.4186 0.1606 1.3351 0.0466 0.9453 0.0797
+#> 207: 92.1212 -6.0561 -0.0247 2.4821 -0.9299 0.1677 4.3736 0.3363 0.4150 0.1602 1.3394 0.0467 0.9552 0.0790
+#> 208: 92.1203 -6.0351 -0.0260 2.4804 -0.9309 0.1616 4.2520 0.3369 0.4120 0.1613 1.3366 0.0466 0.9667 0.0785
+#> 209: 92.1169 -6.0133 -0.0277 2.4792 -0.9300 0.1596 4.1237 0.3352 0.4111 0.1616 1.3344 0.0464 0.9741 0.0778
+#> 210: 92.1195 -5.9866 -0.0289 2.4752 -0.9287 0.1586 3.9853 0.3352 0.4091 0.1602 1.3410 0.0461 0.9708 0.0778
+#> 211: 92.1243 -5.9458 -0.0316 2.4687 -0.9287 0.1606 3.8383 0.3366 0.4094 0.1607 1.3525 0.0455 0.9759 0.0778
+#> 212: 92.1384 -5.9338 -0.0345 2.4640 -0.9280 0.1635 3.7875 0.3375 0.4105 0.1594 1.3589 0.0454 0.9800 0.0776
+#> 213: 92.1481 -5.9191 -0.0379 2.4587 -0.9269 0.1629 3.7150 0.3375 0.4100 0.1586 1.3673 0.0449 0.9839 0.0775
+#> 214: 92.1523 -5.9189 -0.0408 2.4542 -0.9270 0.1593 3.7061 0.3375 0.4092 0.1579 1.3731 0.0446 0.9847 0.0773
+#> 215: 92.1548 -5.9183 -0.0429 2.4499 -0.9269 0.1604 3.7075 0.3369 0.4095 0.1574 1.3765 0.0442 0.9821 0.0775
+#> 216: 92.1547 -5.9171 -0.0450 2.4455 -0.9270 0.1600 3.6967 0.3368 0.4100 0.1571 1.3811 0.0438 0.9830 0.0776
+#> 217: 92.1556 -5.9141 -0.0468 2.4422 -0.9281 0.1580 3.6732 0.3361 0.4102 0.1578 1.3864 0.0435 0.9995 0.0770
+#> 218: 92.1587 -5.9173 -0.0477 2.4395 -0.9287 0.1545 3.6822 0.3351 0.4112 0.1580 1.3882 0.0432 1.0001 0.0772
+#> 219: 92.1590 -5.9188 -0.0483 2.4374 -0.9303 0.1540 3.6595 0.3341 0.4132 0.1578 1.3889 0.0430 0.9983 0.0775
+#> 220: 92.1614 -5.9303 -0.0493 2.4353 -0.9321 0.1559 3.6914 0.3336 0.4141 0.1581 1.3914 0.0427 1.0003 0.0775
+#> 221: 92.1657 -5.9455 -0.0504 2.4328 -0.9344 0.1585 3.7569 0.3329 0.4140 0.1591 1.3938 0.0424 1.0064 0.0773
+#> 222: 92.1697 -5.9320 -0.0515 2.4306 -0.9358 0.1617 3.6783 0.3321 0.4145 0.1600 1.3992 0.0421 1.0107 0.0772
+#> 223: 92.1754 -5.9205 -0.0525 2.4280 -0.9375 0.1630 3.6233 0.3313 0.4158 0.1604 1.4072 0.0416 1.0216 0.0770
+#> 224: 92.1809 -5.9149 -0.0534 2.4264 -0.9386 0.1623 3.5812 0.3306 0.4167 0.1607 1.4130 0.0413 1.0349 0.0764
+#> 225: 92.1872 -5.9099 -0.0543 2.4243 -0.9390 0.1619 3.5446 0.3299 0.4174 0.1607 1.4152 0.0411 1.0348 0.0766
+#> 226: 92.1935 -5.9046 -0.0554 2.4224 -0.9396 0.1631 3.5046 0.3299 0.4183 0.1608 1.4157 0.0409 1.0375 0.0766
+#> 227: 92.2026 -5.8964 -0.0567 2.4198 -0.9400 0.1637 3.4591 0.3303 0.4183 0.1614 1.4144 0.0408 1.0444 0.0763
+#> 228: 92.2069 -5.8852 -0.0578 2.4175 -0.9407 0.1633 3.4091 0.3308 0.4185 0.1621 1.4144 0.0407 1.0485 0.0763
+#> 229: 92.2122 -5.8844 -0.0591 2.4145 -0.9418 0.1631 3.3899 0.3314 0.4194 0.1622 1.4173 0.0404 1.0514 0.0763
+#> 230: 92.2183 -5.8907 -0.0604 2.4116 -0.9416 0.1640 3.4053 0.3319 0.4202 0.1616 1.4200 0.0401 1.0527 0.0764
+#> 231: 92.2246 -5.8895 -0.0619 2.4087 -0.9422 0.1651 3.3985 0.3323 0.4208 0.1609 1.4234 0.0400 1.0560 0.0762
+#> 232: 92.2282 -5.8840 -0.0632 2.4058 -0.9423 0.1641 3.3771 0.3327 0.4215 0.1609 1.4266 0.0398 1.0585 0.0762
+#> 233: 92.2294 -5.8775 -0.0645 2.4032 -0.9424 0.1620 3.3481 0.3335 0.4216 0.1607 1.4311 0.0395 1.0600 0.0763
+#> 234: 92.2311 -5.8709 -0.0658 2.4006 -0.9421 0.1626 3.3242 0.3343 0.4220 0.1602 1.4340 0.0393 1.0604 0.0764
+#> 235: 92.2312 -5.8656 -0.0668 2.3985 -0.9420 0.1608 3.3023 0.3350 0.4225 0.1596 1.4381 0.0391 1.0600 0.0765
+#> 236: 92.2289 -5.8633 -0.0675 2.3974 -0.9423 0.1599 3.2811 0.3352 0.4227 0.1589 1.4392 0.0390 1.0594 0.0765
+#> 237: 92.2251 -5.8641 -0.0683 2.3960 -0.9435 0.1586 3.2734 0.3351 0.4226 0.1588 1.4403 0.0389 1.0623 0.0765
+#> 238: 92.2242 -5.8633 -0.0690 2.3949 -0.9443 0.1579 3.2547 0.3349 0.4230 0.1590 1.4409 0.0389 1.0659 0.0765
+#> 239: 92.2250 -5.8612 -0.0693 2.3951 -0.9449 0.1558 3.2309 0.3346 0.4234 0.1599 1.4396 0.0389 1.0740 0.0762
+#> 240: 92.2264 -5.8597 -0.0696 2.3949 -0.9446 0.1550 3.2124 0.3342 0.4234 0.1603 1.4401 0.0388 1.0791 0.0760
+#> 241: 92.2281 -5.8562 -0.0699 2.3948 -0.9449 0.1544 3.1933 0.3339 0.4236 0.1604 1.4411 0.0388 1.0825 0.0760
+#> 242: 92.2289 -5.8512 -0.0703 2.3942 -0.9450 0.1534 3.1709 0.3338 0.4235 0.1606 1.4421 0.0388 1.0870 0.0760
+#> 243: 92.2296 -5.8489 -0.0708 2.3934 -0.9446 0.1531 3.1689 0.3342 0.4230 0.1605 1.4423 0.0387 1.0876 0.0760
+#> 244: 92.2311 -5.8446 -0.0715 2.3929 -0.9443 0.1528 3.1630 0.3349 0.4228 0.1604 1.4429 0.0387 1.0916 0.0759
+#> 245: 92.2338 -5.8421 -0.0718 2.3924 -0.9443 0.1528 3.1616 0.3352 0.4224 0.1610 1.4438 0.0387 1.0980 0.0755
+#> 246: 92.2361 -5.8389 -0.0721 2.3918 -0.9439 0.1525 3.1525 0.3354 0.4216 0.1620 1.4438 0.0388 1.1018 0.0753
+#> 247: 92.2374 -5.8388 -0.0724 2.3917 -0.9434 0.1510 3.1605 0.3356 0.4212 0.1629 1.4438 0.0389 1.1050 0.0751
+#> 248: 92.2360 -5.8367 -0.0728 2.3918 -0.9432 0.1505 3.1559 0.3360 0.4207 0.1638 1.4437 0.0389 1.1090 0.0748
+#> 249: 92.2361 -5.8351 -0.0732 2.3914 -0.9435 0.1499 3.1521 0.3363 0.4204 0.1646 1.4433 0.0389 1.1117 0.0748
+#> 250: 92.2353 -5.8349 -0.0733 2.3906 -0.9436 0.1502 3.1607 0.3365 0.4202 0.1646 1.4457 0.0388 1.1107 0.0749
+#> 251: 92.2343 -5.8318 -0.0736 2.3903 -0.9430 0.1494 3.1513 0.3367 0.4201 0.1648 1.4453 0.0387 1.1093 0.0750
+#> 252: 92.2356 -5.8244 -0.0739 2.3895 -0.9424 0.1477 3.1240 0.3369 0.4200 0.1651 1.4460 0.0386 1.1083 0.0750
+#> 253: 92.2367 -5.8188 -0.0742 2.3890 -0.9423 0.1465 3.1025 0.3369 0.4200 0.1649 1.4477 0.0385 1.1092 0.0750
+#> 254: 92.2392 -5.8154 -0.0747 2.3880 -0.9421 0.1458 3.0888 0.3372 0.4195 0.1644 1.4494 0.0384 1.1080 0.0750
+#> 255: 92.2404 -5.8131 -0.0751 2.3870 -0.9417 0.1451 3.0778 0.3375 0.4191 0.1639 1.4501 0.0383 1.1070 0.0751
+#> 256: 92.2408 -5.8109 -0.0753 2.3867 -0.9413 0.1445 3.0740 0.3376 0.4192 0.1633 1.4510 0.0382 1.1064 0.0751
+#> 257: 92.2413 -5.8066 -0.0754 2.3866 -0.9409 0.1446 3.0636 0.3376 0.4191 0.1628 1.4522 0.0382 1.1080 0.0750
+#> 258: 92.2412 -5.8035 -0.0754 2.3869 -0.9404 0.1436 3.0502 0.3372 0.4191 0.1623 1.4534 0.0381 1.1057 0.0751
+#> 259: 92.2399 -5.7996 -0.0753 2.3871 -0.9399 0.1427 3.0357 0.3370 0.4195 0.1621 1.4540 0.0380 1.1037 0.0752
+#> 260: 92.2389 -5.7955 -0.0755 2.3872 -0.9391 0.1420 3.0251 0.3366 0.4199 0.1619 1.4555 0.0380 1.1041 0.0752
+#> 261: 92.2378 -5.7941 -0.0755 2.3875 -0.9385 0.1412 3.0240 0.3362 0.4201 0.1613 1.4575 0.0380 1.1048 0.0751
+#> 262: 92.2361 -5.7920 -0.0756 2.3879 -0.9379 0.1407 3.0182 0.3358 0.4205 0.1607 1.4581 0.0381 1.1047 0.0750
+#> 263: 92.2338 -5.7891 -0.0754 2.3883 -0.9375 0.1407 3.0072 0.3356 0.4211 0.1603 1.4585 0.0381 1.1041 0.0750
+#> 264: 92.2313 -5.7882 -0.0752 2.3886 -0.9371 0.1407 3.0009 0.3355 0.4217 0.1601 1.4574 0.0381 1.1036 0.0750
+#> 265: 92.2312 -5.7843 -0.0752 2.3883 -0.9372 0.1402 2.9872 0.3358 0.4220 0.1599 1.4577 0.0381 1.1026 0.0750
+#> 266: 92.2312 -5.7800 -0.0753 2.3880 -0.9370 0.1396 2.9708 0.3363 0.4223 0.1597 1.4584 0.0381 1.1019 0.0750
+#> 267: 92.2306 -5.7785 -0.0755 2.3878 -0.9372 0.1397 2.9619 0.3368 0.4227 0.1595 1.4578 0.0381 1.1021 0.0750
+#> 268: 92.2287 -5.7803 -0.0758 2.3870 -0.9372 0.1394 2.9777 0.3375 0.4226 0.1594 1.4578 0.0380 1.1032 0.0749
+#> 269: 92.2265 -5.7804 -0.0761 2.3865 -0.9371 0.1399 2.9816 0.3382 0.4226 0.1592 1.4589 0.0380 1.1058 0.0747
+#> 270: 92.2236 -5.7811 -0.0765 2.3860 -0.9369 0.1411 2.9893 0.3386 0.4227 0.1591 1.4597 0.0380 1.1081 0.0745
+#> 271: 92.2211 -5.7793 -0.0769 2.3852 -0.9365 0.1421 2.9888 0.3390 0.4228 0.1591 1.4606 0.0379 1.1083 0.0745
+#> 272: 92.2187 -5.7773 -0.0773 2.3845 -0.9361 0.1423 2.9810 0.3396 0.4232 0.1589 1.4617 0.0378 1.1076 0.0746
+#> 273: 92.2164 -5.7769 -0.0776 2.3838 -0.9356 0.1427 2.9809 0.3402 0.4240 0.1589 1.4615 0.0378 1.1073 0.0746
+#> 274: 92.2145 -5.7763 -0.0778 2.3836 -0.9355 0.1434 2.9795 0.3407 0.4248 0.1589 1.4615 0.0378 1.1069 0.0746
+#> 275: 92.2133 -5.7762 -0.0779 2.3836 -0.9352 0.1436 2.9837 0.3410 0.4253 0.1589 1.4621 0.0378 1.1064 0.0746
+#> 276: 92.2123 -5.7764 -0.0781 2.3835 -0.9348 0.1431 2.9889 0.3414 0.4255 0.1589 1.4632 0.0378 1.1073 0.0746
+#> 277: 92.2113 -5.7771 -0.0781 2.3839 -0.9347 0.1423 2.9925 0.3423 0.4264 0.1589 1.4630 0.0378 1.1104 0.0744
+#> 278: 92.2099 -5.7774 -0.0780 2.3841 -0.9349 0.1418 2.9927 0.3429 0.4270 0.1590 1.4634 0.0378 1.1127 0.0742
+#> 279: 92.2087 -5.7798 -0.0779 2.3844 -0.9352 0.1413 2.9997 0.3437 0.4276 0.1590 1.4630 0.0378 1.1133 0.0742
+#> 280: 92.2077 -5.7802 -0.0778 2.3841 -0.9358 0.1407 2.9971 0.3445 0.4284 0.1586 1.4634 0.0378 1.1136 0.0742
+#> 281: 92.2061 -5.7814 -0.0777 2.3837 -0.9362 0.1401 3.0004 0.3452 0.4291 0.1582 1.4629 0.0378 1.1133 0.0743
+#> 282: 92.2058 -5.7802 -0.0777 2.3834 -0.9363 0.1386 2.9994 0.3459 0.4297 0.1579 1.4634 0.0378 1.1126 0.0743
+#> 283: 92.2057 -5.7780 -0.0778 2.3828 -0.9361 0.1376 2.9917 0.3469 0.4298 0.1576 1.4645 0.0378 1.1147 0.0742
+#> 284: 92.2051 -5.7788 -0.0780 2.3824 -0.9360 0.1367 2.9968 0.3479 0.4300 0.1573 1.4647 0.0378 1.1149 0.0741
+#> 285: 92.2041 -5.7793 -0.0782 2.3821 -0.9362 0.1359 2.9941 0.3487 0.4302 0.1573 1.4653 0.0378 1.1164 0.0740
+#> 286: 92.2040 -5.7803 -0.0783 2.3819 -0.9364 0.1352 2.9957 0.3495 0.4304 0.1573 1.4655 0.0378 1.1180 0.0738
+#> 287: 92.2044 -5.7809 -0.0784 2.3817 -0.9365 0.1348 2.9961 0.3502 0.4304 0.1572 1.4657 0.0379 1.1178 0.0738
+#> 288: 92.2043 -5.7835 -0.0785 2.3814 -0.9366 0.1350 3.0073 0.3509 0.4304 0.1572 1.4658 0.0379 1.1184 0.0738
+#> 289: 92.2041 -5.7845 -0.0787 2.3809 -0.9364 0.1347 3.0126 0.3516 0.4304 0.1571 1.4653 0.0379 1.1190 0.0737
+#> 290: 92.2032 -5.7852 -0.0788 2.3807 -0.9363 0.1349 3.0161 0.3521 0.4304 0.1568 1.4656 0.0379 1.1191 0.0737
+#> 291: 92.2019 -5.7848 -0.0790 2.3802 -0.9363 0.1356 3.0155 0.3528 0.4300 0.1565 1.4664 0.0380 1.1210 0.0736
+#> 292: 92.2012 -5.7846 -0.0792 2.3799 -0.9363 0.1361 3.0167 0.3535 0.4296 0.1563 1.4670 0.0380 1.1223 0.0735
+#> 293: 92.2007 -5.7845 -0.0793 2.3795 -0.9363 0.1365 3.0175 0.3542 0.4291 0.1561 1.4681 0.0380 1.1236 0.0734
+#> 294: 92.2009 -5.7850 -0.0795 2.3791 -0.9360 0.1365 3.0189 0.3550 0.4287 0.1560 1.4682 0.0380 1.1243 0.0733
+#> 295: 92.2009 -5.7865 -0.0797 2.3786 -0.9360 0.1360 3.0279 0.3556 0.4286 0.1558 1.4689 0.0380 1.1243 0.0734
+#> 296: 92.2007 -5.7878 -0.0798 2.3781 -0.9362 0.1358 3.0345 0.3562 0.4283 0.1555 1.4694 0.0379 1.1247 0.0734
+#> 297: 92.1992 -5.7891 -0.0801 2.3774 -0.9364 0.1358 3.0403 0.3568 0.4278 0.1554 1.4699 0.0379 1.1267 0.0734
+#> 298: 92.1978 -5.7892 -0.0803 2.3768 -0.9366 0.1357 3.0383 0.3573 0.4274 0.1553 1.4706 0.0378 1.1276 0.0734
+#> 299: 92.1968 -5.7906 -0.0805 2.3763 -0.9369 0.1353 3.0408 0.3579 0.4269 0.1553 1.4712 0.0378 1.1282 0.0733
+#> 300: 92.1954 -5.7929 -0.0807 2.3760 -0.9369 0.1352 3.0477 0.3583 0.4265 0.1551 1.4716 0.0379 1.1286 0.0733
+#> 301: 92.1941 -5.7934 -0.0809 2.3757 -0.9369 0.1352 3.0483 0.3588 0.4261 0.1548 1.4727 0.0378 1.1288 0.0732
+#> 302: 92.1929 -5.7949 -0.0811 2.3754 -0.9370 0.1354 3.0560 0.3592 0.4256 0.1548 1.4728 0.0379 1.1296 0.0731
+#> 303: 92.1919 -5.7972 -0.0813 2.3751 -0.9368 0.1352 3.0671 0.3597 0.4250 0.1550 1.4730 0.0379 1.1302 0.0731
+#> 304: 92.1906 -5.8018 -0.0814 2.3750 -0.9368 0.1349 3.0935 0.3602 0.4245 0.1552 1.4731 0.0379 1.1314 0.0730
+#> 305: 92.1897 -5.8063 -0.0817 2.3744 -0.9370 0.1350 3.1211 0.3606 0.4238 0.1554 1.4727 0.0379 1.1323 0.0730
+#> 306: 92.1896 -5.8116 -0.0820 2.3740 -0.9373 0.1347 3.1571 0.3610 0.4233 0.1555 1.4727 0.0379 1.1351 0.0728
+#> 307: 92.1895 -5.8156 -0.0822 2.3735 -0.9373 0.1341 3.1826 0.3613 0.4226 0.1552 1.4741 0.0379 1.1374 0.0726
+#> 308: 92.1899 -5.8202 -0.0824 2.3732 -0.9376 0.1338 3.2124 0.3617 0.4220 0.1554 1.4745 0.0379 1.1408 0.0724
+#> 309: 92.1903 -5.8232 -0.0827 2.3728 -0.9377 0.1337 3.2330 0.3620 0.4213 0.1554 1.4749 0.0379 1.1419 0.0724
+#> 310: 92.1902 -5.8249 -0.0828 2.3727 -0.9378 0.1335 3.2463 0.3621 0.4207 0.1554 1.4752 0.0379 1.1435 0.0723
+#> 311: 92.1910 -5.8267 -0.0828 2.3726 -0.9378 0.1335 3.2581 0.3623 0.4200 0.1554 1.4754 0.0379 1.1441 0.0722
+#> 312: 92.1918 -5.8271 -0.0829 2.3726 -0.9378 0.1333 3.2567 0.3624 0.4195 0.1552 1.4751 0.0380 1.1432 0.0723
+#> 313: 92.1926 -5.8260 -0.0829 2.3725 -0.9380 0.1334 3.2497 0.3626 0.4190 0.1552 1.4751 0.0380 1.1434 0.0723
+#> 314: 92.1934 -5.8256 -0.0829 2.3724 -0.9381 0.1330 3.2426 0.3628 0.4185 0.1553 1.4746 0.0380 1.1441 0.0722
+#> 315: 92.1938 -5.8237 -0.0829 2.3724 -0.9384 0.1326 3.2327 0.3630 0.4179 0.1555 1.4746 0.0380 1.1468 0.0721
+#> 316: 92.1950 -5.8235 -0.0829 2.3722 -0.9385 0.1324 3.2283 0.3631 0.4172 0.1557 1.4745 0.0380 1.1476 0.0721
+#> 317: 92.1963 -5.8239 -0.0829 2.3722 -0.9385 0.1322 3.2260 0.3633 0.4167 0.1560 1.4741 0.0380 1.1481 0.0721
+#> 318: 92.1975 -5.8242 -0.0829 2.3722 -0.9387 0.1321 3.2240 0.3634 0.4163 0.1559 1.4740 0.0380 1.1477 0.0722
+#> 319: 92.1990 -5.8250 -0.0829 2.3721 -0.9387 0.1320 3.2215 0.3634 0.4159 0.1560 1.4736 0.0381 1.1496 0.0720
+#> 320: 92.2003 -5.8256 -0.0829 2.3722 -0.9386 0.1322 3.2199 0.3635 0.4155 0.1561 1.4730 0.0381 1.1508 0.0719
+#> 321: 92.2018 -5.8249 -0.0829 2.3723 -0.9386 0.1326 3.2150 0.3635 0.4151 0.1562 1.4727 0.0381 1.1514 0.0718
+#> 322: 92.2031 -5.8239 -0.0829 2.3724 -0.9386 0.1333 3.2081 0.3635 0.4147 0.1561 1.4729 0.0381 1.1527 0.0717
+#> 323: 92.2045 -5.8244 -0.0829 2.3725 -0.9384 0.1336 3.2065 0.3635 0.4143 0.1562 1.4729 0.0381 1.1541 0.0716
+#> 324: 92.2060 -5.8228 -0.0828 2.3726 -0.9383 0.1339 3.1996 0.3635 0.4139 0.1562 1.4729 0.0382 1.1562 0.0714
+#> 325: 92.2071 -5.8212 -0.0828 2.3727 -0.9383 0.1339 3.1921 0.3636 0.4135 0.1563 1.4733 0.0382 1.1580 0.0713
+#> 326: 92.2083 -5.8201 -0.0826 2.3728 -0.9382 0.1340 3.1888 0.3639 0.4134 0.1562 1.4734 0.0382 1.1587 0.0713
+#> 327: 92.2095 -5.8185 -0.0825 2.3729 -0.9379 0.1340 3.1831 0.3641 0.4134 0.1562 1.4737 0.0382 1.1592 0.0713
+#> 328: 92.2105 -5.8188 -0.0823 2.3731 -0.9379 0.1338 3.1836 0.3643 0.4132 0.1561 1.4736 0.0383 1.1589 0.0713
+#> 329: 92.2115 -5.8182 -0.0821 2.3732 -0.9381 0.1339 3.1807 0.3646 0.4129 0.1561 1.4737 0.0383 1.1585 0.0713
+#> 330: 92.2127 -5.8181 -0.0819 2.3734 -0.9381 0.1338 3.1827 0.3648 0.4127 0.1563 1.4735 0.0383 1.1578 0.0714
+#> 331: 92.2134 -5.8180 -0.0815 2.3739 -0.9381 0.1340 3.1837 0.3647 0.4128 0.1566 1.4735 0.0383 1.1575 0.0714
+#> 332: 92.2136 -5.8184 -0.0811 2.3746 -0.9379 0.1340 3.1847 0.3647 0.4130 0.1570 1.4728 0.0384 1.1577 0.0714
+#> 333: 92.2133 -5.8180 -0.0807 2.3753 -0.9376 0.1340 3.1853 0.3646 0.4132 0.1572 1.4725 0.0384 1.1573 0.0714
+#> 334: 92.2136 -5.8173 -0.0803 2.3760 -0.9374 0.1342 3.1838 0.3645 0.4133 0.1576 1.4720 0.0385 1.1570 0.0714
+#> 335: 92.2139 -5.8187 -0.0800 2.3769 -0.9372 0.1344 3.1947 0.3643 0.4135 0.1576 1.4714 0.0386 1.1567 0.0714
+#> 336: 92.2134 -5.8198 -0.0796 2.3777 -0.9370 0.1348 3.2008 0.3641 0.4135 0.1577 1.4706 0.0387 1.1557 0.0714
+#> 337: 92.2130 -5.8201 -0.0792 2.3784 -0.9370 0.1357 3.2050 0.3640 0.4137 0.1579 1.4703 0.0388 1.1558 0.0714
+#> 338: 92.2130 -5.8190 -0.0787 2.3791 -0.9368 0.1362 3.2036 0.3638 0.4139 0.1580 1.4708 0.0388 1.1558 0.0714
+#> 339: 92.2132 -5.8177 -0.0783 2.3798 -0.9368 0.1369 3.2006 0.3637 0.4142 0.1581 1.4712 0.0388 1.1551 0.0714
+#> 340: 92.2137 -5.8167 -0.0778 2.3806 -0.9366 0.1376 3.1984 0.3636 0.4143 0.1581 1.4712 0.0388 1.1540 0.0715
+#> 341: 92.2141 -5.8145 -0.0773 2.3814 -0.9364 0.1378 3.1916 0.3635 0.4142 0.1581 1.4712 0.0389 1.1529 0.0715
+#> 342: 92.2142 -5.8123 -0.0769 2.3821 -0.9364 0.1383 3.1840 0.3634 0.4142 0.1581 1.4718 0.0389 1.1513 0.0716
+#> 343: 92.2139 -5.8109 -0.0764 2.3830 -0.9364 0.1389 3.1806 0.3632 0.4142 0.1581 1.4721 0.0389 1.1501 0.0716
+#> 344: 92.2137 -5.8117 -0.0759 2.3839 -0.9366 0.1390 3.1830 0.3631 0.4144 0.1582 1.4711 0.0390 1.1492 0.0717
+#> 345: 92.2133 -5.8118 -0.0754 2.3849 -0.9368 0.1391 3.1827 0.3630 0.4146 0.1582 1.4703 0.0391 1.1488 0.0717
+#> 346: 92.2127 -5.8113 -0.0748 2.3858 -0.9369 0.1389 3.1793 0.3629 0.4147 0.1581 1.4700 0.0391 1.1475 0.0717
+#> 347: 92.2121 -5.8107 -0.0743 2.3867 -0.9371 0.1386 3.1748 0.3628 0.4149 0.1579 1.4701 0.0392 1.1463 0.0718
+#> 348: 92.2106 -5.8109 -0.0738 2.3876 -0.9374 0.1385 3.1726 0.3626 0.4151 0.1577 1.4704 0.0392 1.1453 0.0719
+#> 349: 92.2096 -5.8111 -0.0732 2.3883 -0.9377 0.1382 3.1703 0.3626 0.4151 0.1575 1.4705 0.0392 1.1448 0.0719
+#> 350: 92.2088 -5.8108 -0.0727 2.3890 -0.9378 0.1380 3.1674 0.3625 0.4152 0.1574 1.4704 0.0392 1.1439 0.0720
+#> 351: 92.2077 -5.8103 -0.0722 2.3899 -0.9379 0.1379 3.1634 0.3623 0.4154 0.1572 1.4701 0.0393 1.1432 0.0720
+#> 352: 92.2069 -5.8103 -0.0718 2.3906 -0.9381 0.1380 3.1626 0.3623 0.4154 0.1570 1.4701 0.0393 1.1425 0.0721
+#> 353: 92.2058 -5.8107 -0.0714 2.3913 -0.9381 0.1382 3.1629 0.3624 0.4154 0.1570 1.4695 0.0394 1.1426 0.0720
+#> 354: 92.2046 -5.8102 -0.0710 2.3921 -0.9381 0.1384 3.1576 0.3624 0.4154 0.1571 1.4691 0.0394 1.1424 0.0720
+#> 355: 92.2034 -5.8084 -0.0707 2.3928 -0.9381 0.1388 3.1501 0.3624 0.4154 0.1570 1.4686 0.0395 1.1414 0.0721
+#> 356: 92.2027 -5.8079 -0.0703 2.3935 -0.9382 0.1392 3.1463 0.3626 0.4155 0.1569 1.4682 0.0396 1.1405 0.0721
+#> 357: 92.2019 -5.8084 -0.0698 2.3943 -0.9382 0.1390 3.1444 0.3628 0.4156 0.1569 1.4665 0.0397 1.1403 0.0721
+#> 358: 92.2014 -5.8085 -0.0694 2.3950 -0.9381 0.1389 3.1413 0.3630 0.4158 0.1569 1.4662 0.0398 1.1398 0.0722
+#> 359: 92.2005 -5.8091 -0.0689 2.3956 -0.9383 0.1387 3.1393 0.3633 0.4159 0.1570 1.4664 0.0398 1.1401 0.0722
+#> 360: 92.1994 -5.8091 -0.0685 2.3962 -0.9385 0.1385 3.1362 0.3635 0.4159 0.1572 1.4664 0.0398 1.1413 0.0722
+#> 361: 92.1983 -5.8094 -0.0682 2.3966 -0.9386 0.1384 3.1340 0.3638 0.4159 0.1573 1.4669 0.0398 1.1420 0.0722
+#> 362: 92.1976 -5.8086 -0.0678 2.3971 -0.9389 0.1380 3.1277 0.3639 0.4160 0.1573 1.4671 0.0398 1.1414 0.0723
+#> 363: 92.1967 -5.8081 -0.0675 2.3976 -0.9389 0.1377 3.1239 0.3641 0.4161 0.1573 1.4669 0.0399 1.1412 0.0723
+#> 364: 92.1960 -5.8073 -0.0671 2.3982 -0.9390 0.1373 3.1208 0.3643 0.4161 0.1572 1.4668 0.0399 1.1411 0.0723
+#> 365: 92.1958 -5.8066 -0.0667 2.3988 -0.9389 0.1369 3.1164 0.3645 0.4160 0.1572 1.4672 0.0399 1.1416 0.0723
+#> 366: 92.1956 -5.8063 -0.0664 2.3992 -0.9390 0.1364 3.1127 0.3650 0.4156 0.1573 1.4674 0.0399 1.1425 0.0723
+#> 367: 92.1952 -5.8056 -0.0661 2.3996 -0.9389 0.1361 3.1082 0.3652 0.4155 0.1574 1.4675 0.0399 1.1416 0.0723
+#> 368: 92.1948 -5.8059 -0.0658 2.4001 -0.9389 0.1359 3.1068 0.3655 0.4154 0.1575 1.4671 0.0399 1.1406 0.0724
+#> 369: 92.1948 -5.8064 -0.0655 2.4005 -0.9388 0.1360 3.1055 0.3658 0.4152 0.1576 1.4669 0.0399 1.1408 0.0724
+#> 370: 92.1951 -5.8072 -0.0652 2.4010 -0.9389 0.1361 3.1060 0.3660 0.4151 0.1576 1.4669 0.0399 1.1406 0.0724
+#> 371: 92.1956 -5.8080 -0.0649 2.4015 -0.9390 0.1362 3.1095 0.3662 0.4150 0.1576 1.4669 0.0400 1.1411 0.0724
+#> 372: 92.1962 -5.8096 -0.0645 2.4020 -0.9390 0.1363 3.1168 0.3665 0.4149 0.1576 1.4667 0.0400 1.1411 0.0724
+#> 373: 92.1968 -5.8098 -0.0642 2.4025 -0.9392 0.1363 3.1154 0.3666 0.4147 0.1576 1.4664 0.0400 1.1418 0.0723
+#> 374: 92.1972 -5.8098 -0.0640 2.4029 -0.9395 0.1363 3.1117 0.3667 0.4146 0.1576 1.4661 0.0401 1.1421 0.0723
+#> 375: 92.1979 -5.8101 -0.0637 2.4032 -0.9397 0.1364 3.1090 0.3668 0.4143 0.1577 1.4654 0.0401 1.1425 0.0723
+#> 376: 92.1981 -5.8106 -0.0635 2.4035 -0.9399 0.1363 3.1084 0.3669 0.4142 0.1576 1.4650 0.0401 1.1423 0.0723
+#> 377: 92.1986 -5.8104 -0.0633 2.4039 -0.9399 0.1360 3.1053 0.3670 0.4142 0.1576 1.4645 0.0402 1.1424 0.0723
+#> 378: 92.1989 -5.8104 -0.0631 2.4043 -0.9399 0.1358 3.1026 0.3671 0.4142 0.1577 1.4638 0.0402 1.1421 0.0723
+#> 379: 92.1990 -5.8114 -0.0628 2.4047 -0.9399 0.1355 3.1068 0.3671 0.4141 0.1577 1.4636 0.0402 1.1413 0.0724
+#> 380: 92.1989 -5.8119 -0.0627 2.4048 -0.9400 0.1351 3.1095 0.3673 0.4136 0.1577 1.4634 0.0402 1.1413 0.0724
+#> 381: 92.1989 -5.8127 -0.0627 2.4048 -0.9400 0.1349 3.1152 0.3676 0.4131 0.1577 1.4631 0.0403 1.1408 0.0723
+#> 382: 92.1994 -5.8126 -0.0627 2.4049 -0.9399 0.1348 3.1188 0.3678 0.4126 0.1576 1.4635 0.0403 1.1403 0.0723
+#> 383: 92.2000 -5.8129 -0.0626 2.4049 -0.9397 0.1346 3.1256 0.3681 0.4120 0.1576 1.4637 0.0403 1.1396 0.0723
+#> 384: 92.2006 -5.8133 -0.0626 2.4050 -0.9396 0.1347 3.1290 0.3683 0.4115 0.1575 1.4641 0.0402 1.1389 0.0723
+#> 385: 92.2015 -5.8131 -0.0626 2.4050 -0.9394 0.1350 3.1287 0.3686 0.4110 0.1575 1.4642 0.0402 1.1382 0.0723
+#> 386: 92.2023 -5.8140 -0.0625 2.4049 -0.9391 0.1349 3.1324 0.3690 0.4104 0.1574 1.4647 0.0402 1.1374 0.0723
+#> 387: 92.2030 -5.8147 -0.0625 2.4050 -0.9390 0.1349 3.1345 0.3693 0.4099 0.1572 1.4652 0.0402 1.1366 0.0724
+#> 388: 92.2040 -5.8157 -0.0625 2.4050 -0.9389 0.1349 3.1381 0.3696 0.4094 0.1570 1.4652 0.0402 1.1362 0.0724
+#> 389: 92.2051 -5.8156 -0.0625 2.4051 -0.9387 0.1349 3.1373 0.3699 0.4090 0.1570 1.4653 0.0402 1.1354 0.0724
+#> 390: 92.2063 -5.8152 -0.0625 2.4051 -0.9386 0.1349 3.1350 0.3702 0.4087 0.1570 1.4655 0.0402 1.1345 0.0725
+#> 391: 92.2076 -5.8160 -0.0625 2.4051 -0.9384 0.1350 3.1380 0.3705 0.4083 0.1571 1.4656 0.0402 1.1341 0.0725
+#> 392: 92.2086 -5.8166 -0.0626 2.4049 -0.9384 0.1349 3.1397 0.3707 0.4081 0.1572 1.4658 0.0402 1.1345 0.0725
+#> 393: 92.2095 -5.8168 -0.0626 2.4047 -0.9383 0.1348 3.1405 0.3708 0.4080 0.1573 1.4659 0.0402 1.1344 0.0725
+#> 394: 92.2107 -5.8174 -0.0627 2.4045 -0.9382 0.1347 3.1433 0.3710 0.4079 0.1575 1.4660 0.0401 1.1342 0.0725
+#> 395: 92.2118 -5.8174 -0.0628 2.4043 -0.9380 0.1346 3.1437 0.3711 0.4078 0.1575 1.4661 0.0401 1.1343 0.0725
+#> 396: 92.2127 -5.8170 -0.0629 2.4041 -0.9379 0.1344 3.1424 0.3712 0.4077 0.1575 1.4664 0.0401 1.1342 0.0725
+#> 397: 92.2137 -5.8161 -0.0630 2.4040 -0.9376 0.1342 3.1386 0.3713 0.4076 0.1577 1.4667 0.0401 1.1341 0.0725
+#> 398: 92.2146 -5.8152 -0.0633 2.4036 -0.9374 0.1341 3.1344 0.3713 0.4075 0.1578 1.4671 0.0401 1.1334 0.0725
+#> 399: 92.2157 -5.8138 -0.0635 2.4032 -0.9373 0.1340 3.1296 0.3714 0.4074 0.1578 1.4678 0.0401 1.1336 0.0726
+#> 400: 92.2165 -5.8131 -0.0638 2.4027 -0.9372 0.1340 3.1262 0.3715 0.4072 0.1579 1.4681 0.0400 1.1332 0.0726
+#> 401: 92.2173 -5.8118 -0.0641 2.4022 -0.9372 0.1341 3.1220 0.3716 0.4069 0.1579 1.4686 0.0400 1.1339 0.0726
+#> 402: 92.2181 -5.8107 -0.0643 2.4018 -0.9370 0.1344 3.1192 0.3718 0.4065 0.1580 1.4694 0.0400 1.1338 0.0726
+#> 403: 92.2190 -5.8099 -0.0646 2.4013 -0.9371 0.1348 3.1166 0.3720 0.4061 0.1581 1.4700 0.0400 1.1344 0.0725
+#> 404: 92.2198 -5.8104 -0.0649 2.4008 -0.9372 0.1348 3.1161 0.3723 0.4058 0.1582 1.4704 0.0399 1.1357 0.0725
+#> 405: 92.2203 -5.8107 -0.0652 2.4004 -0.9372 0.1348 3.1177 0.3725 0.4055 0.1582 1.4705 0.0400 1.1358 0.0724
+#> 406: 92.2204 -5.8103 -0.0653 2.4002 -0.9371 0.1348 3.1157 0.3724 0.4051 0.1582 1.4709 0.0400 1.1361 0.0724
+#> 407: 92.2201 -5.8094 -0.0655 2.4001 -0.9369 0.1348 3.1121 0.3724 0.4048 0.1583 1.4713 0.0400 1.1360 0.0724
+#> 408: 92.2201 -5.8087 -0.0657 2.3999 -0.9368 0.1350 3.1085 0.3724 0.4044 0.1582 1.4714 0.0400 1.1360 0.0723
+#> 409: 92.2201 -5.8083 -0.0658 2.3998 -0.9365 0.1355 3.1073 0.3724 0.4043 0.1582 1.4713 0.0401 1.1358 0.0723
+#> 410: 92.2196 -5.8094 -0.0659 2.3996 -0.9365 0.1361 3.1123 0.3724 0.4041 0.1582 1.4712 0.0401 1.1357 0.0723
+#> 411: 92.2192 -5.8099 -0.0661 2.3994 -0.9366 0.1363 3.1168 0.3724 0.4038 0.1582 1.4715 0.0401 1.1354 0.0723
+#> 412: 92.2187 -5.8105 -0.0662 2.3993 -0.9365 0.1365 3.1215 0.3725 0.4035 0.1582 1.4716 0.0401 1.1359 0.0723
+#> 413: 92.2185 -5.8109 -0.0663 2.3992 -0.9365 0.1367 3.1268 0.3725 0.4031 0.1583 1.4719 0.0401 1.1357 0.0723
+#> 414: 92.2183 -5.8111 -0.0665 2.3987 -0.9365 0.1370 3.1286 0.3727 0.4026 0.1582 1.4724 0.0400 1.1349 0.0723
+#> 415: 92.2181 -5.8122 -0.0667 2.3983 -0.9366 0.1370 3.1351 0.3729 0.4021 0.1581 1.4726 0.0400 1.1341 0.0724
+#> 416: 92.2180 -5.8133 -0.0669 2.3979 -0.9367 0.1372 3.1409 0.3731 0.4015 0.1578 1.4734 0.0400 1.1333 0.0724
+#> 417: 92.2176 -5.8138 -0.0671 2.3976 -0.9368 0.1374 3.1426 0.3733 0.4009 0.1576 1.4739 0.0400 1.1325 0.0724
+#> 418: 92.2173 -5.8150 -0.0673 2.3973 -0.9369 0.1376 3.1479 0.3735 0.4003 0.1575 1.4740 0.0400 1.1316 0.0725
+#> 419: 92.2174 -5.8154 -0.0674 2.3970 -0.9369 0.1375 3.1497 0.3736 0.3998 0.1574 1.4741 0.0400 1.1314 0.0724
+#> 420: 92.2175 -5.8154 -0.0676 2.3968 -0.9369 0.1375 3.1489 0.3737 0.3993 0.1574 1.4742 0.0400 1.1315 0.0724
+#> 421: 92.2176 -5.8154 -0.0678 2.3964 -0.9369 0.1374 3.1485 0.3739 0.3989 0.1573 1.4743 0.0400 1.1312 0.0724
+#> 422: 92.2174 -5.8155 -0.0680 2.3961 -0.9370 0.1375 3.1483 0.3741 0.3985 0.1572 1.4744 0.0400 1.1309 0.0723
+#> 423: 92.2170 -5.8156 -0.0681 2.3958 -0.9371 0.1375 3.1481 0.3742 0.3980 0.1571 1.4741 0.0400 1.1308 0.0723
+#> 424: 92.2169 -5.8168 -0.0683 2.3956 -0.9372 0.1374 3.1524 0.3744 0.3976 0.1571 1.4740 0.0400 1.1316 0.0722
+#> 425: 92.2167 -5.8171 -0.0685 2.3954 -0.9372 0.1373 3.1520 0.3744 0.3972 0.1571 1.4736 0.0401 1.1317 0.0722
+#> 426: 92.2164 -5.8170 -0.0687 2.3951 -0.9372 0.1373 3.1502 0.3745 0.3968 0.1570 1.4734 0.0401 1.1320 0.0722
+#> 427: 92.2166 -5.8169 -0.0688 2.3949 -0.9372 0.1372 3.1480 0.3745 0.3964 0.1570 1.4734 0.0401 1.1317 0.0721
+#> 428: 92.2166 -5.8170 -0.0689 2.3948 -0.9374 0.1371 3.1460 0.3745 0.3959 0.1570 1.4735 0.0401 1.1315 0.0721
+#> 429: 92.2162 -5.8171 -0.0691 2.3946 -0.9374 0.1369 3.1446 0.3745 0.3954 0.1570 1.4736 0.0401 1.1316 0.0721
+#> 430: 92.2158 -5.8178 -0.0692 2.3944 -0.9375 0.1370 3.1464 0.3745 0.3950 0.1570 1.4736 0.0401 1.1314 0.0721
+#> 431: 92.2153 -5.8180 -0.0693 2.3942 -0.9375 0.1371 3.1470 0.3745 0.3946 0.1570 1.4735 0.0401 1.1314 0.0721
+#> 432: 92.2150 -5.8182 -0.0695 2.3940 -0.9375 0.1372 3.1477 0.3746 0.3942 0.1570 1.4735 0.0401 1.1315 0.0721
+#> 433: 92.2145 -5.8189 -0.0696 2.3938 -0.9375 0.1374 3.1512 0.3746 0.3938 0.1571 1.4736 0.0400 1.1323 0.0720
+#> 434: 92.2141 -5.8186 -0.0697 2.3936 -0.9373 0.1376 3.1530 0.3746 0.3933 0.1571 1.4736 0.0400 1.1330 0.0719
+#> 435: 92.2133 -5.8187 -0.0699 2.3934 -0.9373 0.1381 3.1571 0.3747 0.3929 0.1570 1.4738 0.0400 1.1325 0.0720
+#> 436: 92.2129 -5.8180 -0.0700 2.3932 -0.9374 0.1380 3.1544 0.3746 0.3925 0.1570 1.4740 0.0400 1.1332 0.0719
+#> 437: 92.2122 -5.8186 -0.0702 2.3930 -0.9375 0.1380 3.1574 0.3746 0.3921 0.1570 1.4739 0.0400 1.1342 0.0718
+#> 438: 92.2114 -5.8187 -0.0703 2.3928 -0.9376 0.1380 3.1583 0.3745 0.3918 0.1569 1.4740 0.0400 1.1346 0.0718
+#> 439: 92.2104 -5.8181 -0.0705 2.3925 -0.9377 0.1381 3.1568 0.3744 0.3914 0.1568 1.4743 0.0400 1.1352 0.0718
+#> 440: 92.2095 -5.8178 -0.0706 2.3923 -0.9377 0.1381 3.1555 0.3743 0.3910 0.1566 1.4745 0.0400 1.1349 0.0718
+#> 441: 92.2088 -5.8176 -0.0707 2.3923 -0.9378 0.1381 3.1559 0.3742 0.3907 0.1565 1.4748 0.0400 1.1349 0.0718
+#> 442: 92.2081 -5.8172 -0.0708 2.3921 -0.9379 0.1383 3.1539 0.3741 0.3903 0.1564 1.4754 0.0400 1.1350 0.0717
+#> 443: 92.2074 -5.8171 -0.0709 2.3920 -0.9380 0.1387 3.1526 0.3740 0.3901 0.1563 1.4756 0.0400 1.1349 0.0717
+#> 444: 92.2068 -5.8175 -0.0711 2.3918 -0.9380 0.1390 3.1533 0.3739 0.3898 0.1562 1.4758 0.0400 1.1353 0.0717
+#> 445: 92.2061 -5.8180 -0.0712 2.3915 -0.9382 0.1394 3.1529 0.3737 0.3896 0.1562 1.4758 0.0400 1.1355 0.0717
+#> 446: 92.2054 -5.8177 -0.0714 2.3912 -0.9384 0.1398 3.1496 0.3735 0.3894 0.1562 1.4760 0.0399 1.1367 0.0716
+#> 447: 92.2051 -5.8180 -0.0716 2.3910 -0.9385 0.1400 3.1484 0.3734 0.3891 0.1563 1.4762 0.0399 1.1370 0.0715
+#> 448: 92.2053 -5.8189 -0.0717 2.3909 -0.9387 0.1405 3.1499 0.3732 0.3889 0.1563 1.4764 0.0399 1.1377 0.0715
+#> 449: 92.2054 -5.8195 -0.0718 2.3908 -0.9388 0.1411 3.1497 0.3730 0.3887 0.1562 1.4768 0.0399 1.1382 0.0715
+#> 450: 92.2054 -5.8205 -0.0719 2.3906 -0.9390 0.1417 3.1528 0.3728 0.3885 0.1562 1.4769 0.0399 1.1378 0.0715
+#> 451: 92.2053 -5.8213 -0.0720 2.3905 -0.9391 0.1423 3.1544 0.3725 0.3883 0.1561 1.4774 0.0399 1.1379 0.0715
+#> 452: 92.2054 -5.8218 -0.0720 2.3905 -0.9393 0.1426 3.1541 0.3722 0.3882 0.1560 1.4779 0.0398 1.1378 0.0715
+#> 453: 92.2054 -5.8217 -0.0721 2.3903 -0.9395 0.1428 3.1530 0.3721 0.3880 0.1559 1.4785 0.0398 1.1378 0.0715
+#> 454: 92.2053 -5.8214 -0.0722 2.3901 -0.9395 0.1431 3.1508 0.3720 0.3878 0.1559 1.4786 0.0398 1.1375 0.0715
+#> 455: 92.2052 -5.8220 -0.0724 2.3898 -0.9396 0.1433 3.1519 0.3720 0.3875 0.1559 1.4791 0.0398 1.1379 0.0715
+#> 456: 92.2053 -5.8230 -0.0727 2.3894 -0.9397 0.1434 3.1544 0.3720 0.3873 0.1560 1.4793 0.0398 1.1384 0.0714
+#> 457: 92.2053 -5.8240 -0.0729 2.3889 -0.9398 0.1437 3.1568 0.3720 0.3869 0.1559 1.4793 0.0398 1.1393 0.0714
+#> 458: 92.2051 -5.8245 -0.0731 2.3885 -0.9399 0.1440 3.1571 0.3721 0.3865 0.1558 1.4797 0.0397 1.1404 0.0713
+#> 459: 92.2045 -5.8246 -0.0732 2.3882 -0.9402 0.1442 3.1562 0.3721 0.3862 0.1558 1.4801 0.0397 1.1407 0.0713
+#> 460: 92.2040 -5.8244 -0.0734 2.3878 -0.9403 0.1442 3.1536 0.3722 0.3859 0.1558 1.4806 0.0397 1.1406 0.0713
+#> 461: 92.2030 -5.8245 -0.0736 2.3874 -0.9404 0.1444 3.1517 0.3722 0.3856 0.1557 1.4811 0.0397 1.1412 0.0713
+#> 462: 92.2022 -5.8253 -0.0738 2.3870 -0.9405 0.1445 3.1531 0.3723 0.3853 0.1556 1.4817 0.0396 1.1425 0.0712
+#> 463: 92.2014 -5.8260 -0.0740 2.3866 -0.9405 0.1449 3.1545 0.3724 0.3849 0.1556 1.4823 0.0396 1.1441 0.0711
+#> 464: 92.2008 -5.8257 -0.0742 2.3862 -0.9405 0.1453 3.1522 0.3726 0.3845 0.1555 1.4828 0.0396 1.1451 0.0711
+#> 465: 92.2002 -5.8256 -0.0744 2.3859 -0.9404 0.1458 3.1511 0.3727 0.3842 0.1555 1.4830 0.0396 1.1459 0.0710
+#> 466: 92.1997 -5.8256 -0.0747 2.3855 -0.9403 0.1463 3.1516 0.3728 0.3839 0.1555 1.4834 0.0396 1.1476 0.0709
+#> 467: 92.1993 -5.8258 -0.0749 2.3850 -0.9404 0.1468 3.1521 0.3730 0.3836 0.1555 1.4835 0.0395 1.1490 0.0708
+#> 468: 92.1990 -5.8259 -0.0752 2.3846 -0.9404 0.1473 3.1546 0.3731 0.3834 0.1555 1.4837 0.0395 1.1500 0.0708
+#> 469: 92.1987 -5.8263 -0.0753 2.3844 -0.9403 0.1479 3.1598 0.3731 0.3831 0.1555 1.4839 0.0395 1.1504 0.0707
+#> 470: 92.1987 -5.8267 -0.0755 2.3841 -0.9403 0.1482 3.1611 0.3730 0.3829 0.1555 1.4839 0.0395 1.1496 0.0708
+#> 471: 92.1987 -5.8269 -0.0756 2.3839 -0.9404 0.1482 3.1627 0.3730 0.3826 0.1555 1.4839 0.0395 1.1492 0.0708
+#> 472: 92.1983 -5.8269 -0.0758 2.3838 -0.9403 0.1480 3.1618 0.3729 0.3823 0.1555 1.4839 0.0395 1.1493 0.0708
+#> 473: 92.1980 -5.8264 -0.0760 2.3836 -0.9402 0.1478 3.1602 0.3728 0.3820 0.1554 1.4839 0.0395 1.1489 0.0708
+#> 474: 92.1976 -5.8256 -0.0762 2.3834 -0.9402 0.1475 3.1565 0.3727 0.3818 0.1554 1.4842 0.0395 1.1487 0.0708
+#> 475: 92.1971 -5.8252 -0.0763 2.3832 -0.9402 0.1473 3.1543 0.3726 0.3816 0.1553 1.4845 0.0395 1.1487 0.0707
+#> 476: 92.1965 -5.8250 -0.0765 2.3830 -0.9402 0.1469 3.1523 0.3725 0.3814 0.1552 1.4846 0.0395 1.1484 0.0707
+#> 477: 92.1960 -5.8242 -0.0766 2.3827 -0.9402 0.1465 3.1483 0.3724 0.3811 0.1552 1.4849 0.0395 1.1483 0.0708
+#> 478: 92.1955 -5.8236 -0.0767 2.3826 -0.9402 0.1463 3.1447 0.3722 0.3808 0.1553 1.4854 0.0395 1.1481 0.0708
+#> 479: 92.1952 -5.8232 -0.0769 2.3824 -0.9401 0.1462 3.1421 0.3722 0.3805 0.1554 1.4857 0.0395 1.1478 0.0708
+#> 480: 92.1948 -5.8235 -0.0770 2.3822 -0.9400 0.1461 3.1426 0.3721 0.3803 0.1554 1.4862 0.0395 1.1478 0.0708
+#> 481: 92.1947 -5.8240 -0.0772 2.3820 -0.9399 0.1459 3.1455 0.3721 0.3801 0.1554 1.4868 0.0395 1.1483 0.0708
+#> 482: 92.1948 -5.8244 -0.0774 2.3817 -0.9399 0.1456 3.1476 0.3720 0.3799 0.1553 1.4873 0.0395 1.1488 0.0708
+#> 483: 92.1944 -5.8247 -0.0776 2.3815 -0.9397 0.1455 3.1487 0.3719 0.3797 0.1553 1.4876 0.0394 1.1494 0.0708
+#> 484: 92.1941 -5.8249 -0.0778 2.3811 -0.9396 0.1454 3.1493 0.3719 0.3795 0.1554 1.4879 0.0394 1.1501 0.0707
+#> 485: 92.1940 -5.8252 -0.0780 2.3809 -0.9396 0.1453 3.1501 0.3718 0.3793 0.1554 1.4881 0.0394 1.1503 0.0707
+#> 486: 92.1936 -5.8249 -0.0781 2.3807 -0.9395 0.1453 3.1486 0.3717 0.3792 0.1554 1.4884 0.0394 1.1508 0.0707
+#> 487: 92.1935 -5.8248 -0.0783 2.3804 -0.9394 0.1453 3.1485 0.3716 0.3791 0.1553 1.4887 0.0393 1.1507 0.0707
+#> 488: 92.1932 -5.8246 -0.0785 2.3800 -0.9394 0.1454 3.1478 0.3715 0.3788 0.1552 1.4892 0.0393 1.1510 0.0707
+#> 489: 92.1931 -5.8241 -0.0787 2.3796 -0.9394 0.1455 3.1468 0.3715 0.3787 0.1551 1.4895 0.0393 1.1514 0.0706
+#> 490: 92.1934 -5.8242 -0.0790 2.3793 -0.9393 0.1456 3.1478 0.3715 0.3786 0.1551 1.4898 0.0393 1.1528 0.0706
+#> 491: 92.1936 -5.8241 -0.0792 2.3788 -0.9392 0.1455 3.1472 0.3715 0.3785 0.1551 1.4900 0.0393 1.1533 0.0706
+#> 492: 92.1940 -5.8234 -0.0794 2.3783 -0.9391 0.1455 3.1449 0.3714 0.3783 0.1551 1.4903 0.0392 1.1538 0.0705
+#> 493: 92.1943 -5.8230 -0.0797 2.3779 -0.9390 0.1455 3.1426 0.3714 0.3783 0.1552 1.4907 0.0392 1.1541 0.0705
+#> 494: 92.1946 -5.8226 -0.0799 2.3774 -0.9390 0.1458 3.1405 0.3713 0.3782 0.1551 1.4911 0.0392 1.1541 0.0706
+#> 495: 92.1948 -5.8219 -0.0802 2.3770 -0.9391 0.1459 3.1366 0.3712 0.3782 0.1551 1.4916 0.0392 1.1543 0.0706
+#> 496: 92.1948 -5.8213 -0.0804 2.3766 -0.9392 0.1460 3.1331 0.3711 0.3781 0.1552 1.4920 0.0392 1.1556 0.0705
+#> 497: 92.1949 -5.8213 -0.0806 2.3762 -0.9393 0.1462 3.1326 0.3711 0.3780 0.1553 1.4923 0.0391 1.1564 0.0705
+#> 498: 92.1950 -5.8215 -0.0808 2.3758 -0.9394 0.1462 3.1331 0.3710 0.3779 0.1553 1.4926 0.0391 1.1568 0.0705
+#> 499: 92.1953 -5.8219 -0.0810 2.3754 -0.9395 0.1461 3.1343 0.3709 0.3778 0.1554 1.4929 0.0391 1.1567 0.0705
+#> 500: 92.1957 -5.8232 -0.0812 2.3751 -0.9395 0.1459 3.1411 0.3709 0.3776 0.1554 1.4931 0.0391 1.1575 0.0705
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 9.1294e+01 -5.0486e+00 -1.7441e+00 -3.5640e+00 -2.1387e+00 4.8639e-01 5.5948e+00 1.4680e+00 1.1057e+00 2.3810e+00 4.8150e-01 4.3452e-01 1.0359e+01 2.3790e-05 7.8082e+00 5.1813e-01
-#> 2: 9.1224e+01 -5.2308e+00 -1.9743e+00 -4.0115e+00 -1.8311e+00 9.8058e-02 5.3151e+00 1.3946e+00 1.0504e+00 2.8908e+00 4.5742e-01 5.2252e-01 5.9132e+00 5.7000e-04 6.5362e+00 1.8571e-07
-#> 3: 9.1371e+01 -5.5075e+00 -2.1136e+00 -4.0542e+00 -1.4871e+00 -4.1222e-02 5.0493e+00 1.3249e+00 9.9785e-01 3.4546e+00 4.3455e-01 6.3380e-01 4.0626e+00 1.0302e-05 4.6845e+00 5.0378e-04
-#> 4: 91.3391 -5.7912 -2.1450 -3.9623 -1.3302 -0.1356 4.7969 1.2586 0.9480 3.2819 0.4128 0.6021 3.3624 0.0249 3.6770 0.0248
-#> 5: 91.5018 -6.0214 -2.1492 -3.9323 -1.2118 -0.0647 4.5570 1.1957 0.9006 3.1178 0.3922 0.5720 2.9393 0.0349 3.1610 0.0371
-#> 6: 91.4496 -5.8734 -2.0974 -3.9977 -1.0936 -0.0608 4.3292 1.3347 0.8695 3.1231 0.3726 0.5434 2.5921 0.0366 2.7534 0.0396
-#> 7: 91.6540 -5.8545 -2.1019 -3.9268 -0.9717 -0.1622 4.1127 1.8221 0.8771 2.9670 0.3539 0.5162 2.3468 0.0466 2.4323 0.0474
-#> 8: 91.7226 -5.8139 -2.0764 -4.0030 -0.9804 -0.1283 3.9071 2.3972 0.9978 2.9945 0.3362 0.4904 2.0001 0.0405 2.0620 0.0557
-#> 9: 91.9975 -5.6339 -2.0812 -3.9379 -0.9156 -0.0654 4.4265 2.2773 0.9479 3.0945 0.3194 0.4659 1.8817 0.0397 1.4473 0.0845
-#> 10: 91.9477 -5.6101 -2.0459 -3.8821 -0.9368 -0.0428 4.9868 2.2787 0.9297 3.2162 0.3035 0.4426 1.6910 0.0397 1.3759 0.0892
-#> 11: 92.1798 -5.5425 -2.0676 -3.9349 -0.9248 -0.0339 5.0312 2.1648 0.8832 3.0554 0.2883 0.4205 1.6613 0.0375 1.3387 0.0823
-#> 12: 92.1456 -5.6294 -2.1011 -3.8899 -0.9195 -0.0410 4.7796 2.0565 0.9077 3.1066 0.3013 0.3995 1.6018 0.0393 1.5496 0.0691
-#> 13: 91.6764 -5.5607 -2.0911 -3.8832 -0.9268 -0.0367 4.5407 1.9537 0.9246 3.0425 0.2862 0.3795 1.6900 0.0350 1.4050 0.0712
-#> 14: 91.4832 -5.5007 -2.1133 -3.8869 -0.9208 -0.0202 4.3136 1.8560 0.8795 3.0389 0.2719 0.3605 1.5526 0.0389 1.7056 0.0502
-#> 15: 91.7854 -5.4454 -2.1124 -3.8750 -0.8842 -0.0608 4.0979 1.7632 0.9004 3.0463 0.2583 0.3425 1.6201 0.0384 1.2463 0.0747
-#> 16: 91.7608 -5.4097 -2.1449 -3.8750 -0.8797 -0.0532 3.8930 1.6751 0.9666 3.0463 0.2454 0.3254 1.6086 0.0384 1.0840 0.0850
-#> 17: 91.6692 -5.5401 -2.1688 -3.8762 -0.9022 -0.0101 3.6984 1.8405 1.0323 2.9672 0.2331 0.3091 1.4625 0.0371 1.1135 0.0841
-#> 18: 91.3169 -5.5720 -2.1777 -3.8851 -0.9396 0.0040 3.5135 1.8186 1.0419 3.0783 0.2215 0.2936 1.4778 0.0396 1.3403 0.0732
-#> 19: 91.4384 -5.6696 -2.1469 -3.8892 -0.9318 -0.0103 3.3378 2.2700 1.0489 3.0592 0.2128 0.2790 1.3854 0.0379 1.1760 0.0858
-#> 20: 91.3273 -5.7800 -2.1388 -3.9004 -0.9536 -0.0159 3.1709 2.7506 1.0297 3.0477 0.2021 0.2650 1.4542 0.0419 1.1576 0.0856
-#> 21: 91.7477 -5.7952 -2.1436 -3.9164 -0.9263 -0.0184 3.0124 3.0737 1.0414 3.0435 0.1948 0.2518 1.5026 0.0398 1.1833 0.0791
-#> 22: 91.6492 -6.0575 -2.1196 -3.9168 -0.9471 -0.0153 2.8617 4.1317 1.0322 3.0494 0.1850 0.2392 1.4351 0.0409 1.0739 0.0873
-#> 23: 91.8536 -6.2824 -2.1596 -3.9174 -0.9405 0.0031 2.7187 5.3935 1.0143 3.1085 0.1758 0.2272 1.4534 0.0404 1.0651 0.0805
-#> 24: 92.1616 -6.2246 -2.0912 -3.9224 -0.9338 0.0118 2.5827 5.7533 0.9636 3.0780 0.1741 0.2158 1.5863 0.0336 1.0915 0.0804
-#> 25: 92.2576 -6.2746 -2.1058 -3.9587 -0.9355 0.0189 2.4536 5.4656 0.9706 3.3477 0.1780 0.2051 1.4555 0.0365 1.0838 0.0782
-#> 26: 92.3314 -6.1739 -2.1211 -3.9676 -0.9474 0.0525 2.4934 5.5785 0.9981 3.3705 0.1835 0.1948 1.4433 0.0379 1.1300 0.0783
-#> 27: 92.8206 -6.1111 -2.0900 -3.9787 -0.9472 0.0058 2.5201 5.4329 1.0145 3.5013 0.1856 0.1851 1.4484 0.0391 1.1809 0.0723
-#> 28: 92.8685 -6.0934 -2.0963 -3.9872 -0.9693 0.0053 2.9812 5.1612 0.9925 3.5416 0.1816 0.1758 1.4713 0.0389 1.1766 0.0704
-#> 29: 92.6774 -5.8779 -2.0833 -3.9954 -0.9546 -0.0099 4.3751 4.9032 1.0762 3.5483 0.1755 0.1670 1.4844 0.0378 1.3435 0.0599
-#> 30: 92.6704 -5.9657 -2.0746 -3.9920 -0.9342 -0.0329 4.1563 4.6580 1.0571 3.5382 0.1667 0.1587 1.4510 0.0427 1.2218 0.0678
-#> 31: 92.4139 -5.7428 -2.0922 -3.9765 -0.9178 -0.0302 3.9485 4.4251 1.0210 3.5601 0.1596 0.1507 1.5981 0.0349 1.3086 0.0619
-#> 32: 92.8243 -5.8072 -2.1154 -3.9699 -0.9130 0.0065 3.7511 4.2039 1.0622 3.4768 0.1667 0.1432 1.5321 0.0333 1.3779 0.0611
-#> 33: 92.8737 -5.6655 -2.1132 -3.9763 -0.9155 0.0183 3.5635 3.9937 1.1068 3.5075 0.1583 0.1360 1.5351 0.0341 1.2700 0.0673
-#> 34: 93.0233 -5.7429 -2.1022 -3.9648 -0.9057 0.0202 3.3853 3.7940 1.0830 3.4532 0.1504 0.1292 1.5128 0.0368 1.1942 0.0702
-#> 35: 93.1333 -5.7707 -2.1003 -4.0004 -0.9031 0.0201 3.2161 3.6043 1.1161 3.4701 0.1429 0.1228 1.6003 0.0307 1.1387 0.0734
-#> 36: 93.1398 -5.7700 -2.1168 -3.9678 -0.9038 0.0107 3.0553 3.4241 1.1209 3.4126 0.1358 0.1166 1.4919 0.0331 1.0642 0.0755
-#> 37: 92.8847 -5.6651 -2.1538 -3.9634 -0.9176 0.0364 2.9995 3.2529 1.1108 3.3776 0.1402 0.1173 1.5093 0.0396 1.1550 0.0693
-#> 38: 93.2326 -5.5244 -2.1571 -3.9909 -0.9231 0.0179 2.8832 3.0902 1.0763 3.5170 0.1332 0.1205 1.4962 0.0472 1.1657 0.0679
-#> 39: 92.9946 -5.4516 -2.1475 -3.9365 -0.9067 0.0309 3.0986 2.9357 1.0562 3.4194 0.1265 0.1251 1.4786 0.0464 1.1183 0.0721
-#> 40: 93.2028 -5.6148 -2.1367 -3.9235 -0.9048 0.0099 2.9436 2.7889 1.1256 3.3460 0.1241 0.1288 1.4515 0.0459 1.0449 0.0753
-#> 41: 93.1297 -5.4665 -2.0545 -4.0108 -0.9136 -0.0216 2.7964 2.6495 1.1471 3.4754 0.1281 0.1223 1.7359 0.0321 1.0876 0.0780
-#> 42: 93.0469 -5.3767 -2.0820 -4.0213 -0.9361 -0.0264 2.6566 2.5170 1.0897 3.5120 0.1411 0.1162 1.7070 0.0276 1.2377 0.0691
-#> 43: 93.3305 -5.4943 -2.0910 -4.0226 -0.9414 -0.0201 2.5238 2.3912 1.0896 3.4589 0.1621 0.1126 1.5584 0.0393 1.1485 0.0705
-#> 44: 93.2566 -5.4919 -2.1016 -4.0718 -0.9373 0.0024 2.3976 2.2716 1.0451 3.8959 0.1612 0.1162 1.5769 0.0286 1.2778 0.0693
-#> 45: 93.0284 -5.4885 -2.1012 -4.0740 -0.9202 -0.0197 2.2777 2.1580 1.0268 3.9297 0.1553 0.1104 1.5589 0.0289 1.1388 0.0778
-#> 46: 92.7188 -5.5807 -2.1102 -4.0875 -0.9465 0.0076 2.1638 2.2084 0.9840 4.0322 0.1475 0.1048 1.6729 0.0295 1.2763 0.0735
-#> 47: 92.6718 -5.5108 -2.1268 -4.0638 -0.9220 0.0131 2.0556 2.0980 1.0064 3.8306 0.1475 0.0996 1.6527 0.0271 1.3190 0.0659
-#> 48: 92.6727 -5.5268 -2.1326 -4.0693 -0.8999 0.0259 1.9529 2.2445 1.0387 3.8064 0.1459 0.0946 1.6587 0.0283 1.3555 0.0604
-#> 49: 92.5230 -5.5592 -2.1701 -4.0595 -0.9087 0.0350 1.8552 2.5181 1.0238 3.7514 0.1552 0.0899 1.5473 0.0307 1.2437 0.0662
-#> 50: 92.4920 -5.5778 -2.1309 -4.0711 -0.9317 0.0383 1.7625 2.6771 1.0203 3.7435 0.1587 0.0854 1.5727 0.0330 1.2555 0.0611
-#> 51: 92.4606 -5.5485 -2.1346 -4.0687 -0.9148 0.0638 1.6743 2.8079 1.0402 3.6978 0.1513 0.0811 1.5476 0.0335 1.2744 0.0658
-#> 52: 92.6305 -5.6829 -2.1658 -4.0697 -0.9298 0.0848 1.5906 2.8530 1.0565 3.6998 0.1644 0.0798 1.4751 0.0296 1.1351 0.0747
-#> 53: 92.6412 -5.5519 -2.1984 -4.1605 -0.9472 0.0803 1.8328 2.7103 1.0501 4.4111 0.1626 0.0758 1.5735 0.0343 1.2247 0.0643
-#> 54: 92.7616 -5.5718 -2.1826 -4.2028 -0.9382 0.0939 1.9108 2.5748 1.0708 4.7287 0.1775 0.0720 1.4860 0.0299 1.2190 0.0638
-#> 55: 92.8466 -5.6434 -2.1590 -4.0501 -0.9219 0.0660 2.3709 2.4461 1.0399 4.4922 0.1686 0.0684 1.5899 0.0297 1.2586 0.0598
-#> 56: 92.8839 -5.6503 -2.1758 -4.0467 -0.9265 0.0765 2.2523 2.3238 1.0755 4.2676 0.1698 0.0666 1.5357 0.0319 1.1854 0.0633
-#> 57: 92.8882 -5.3950 -2.1926 -4.0282 -0.9455 0.0600 2.4994 2.2076 1.0411 4.0542 0.1684 0.0633 1.5839 0.0342 1.2789 0.0612
-#> 58: 92.9510 -5.4362 -2.1993 -4.0402 -0.9349 0.0576 2.3744 2.0972 1.0184 3.8515 0.1757 0.0604 1.5796 0.0328 1.3027 0.0570
-#> 59: 92.8806 -5.4605 -2.2176 -4.2201 -0.9360 0.0998 2.2557 1.9923 1.0248 5.1421 0.1904 0.0573 1.6469 0.0325 1.4177 0.0534
-#> 60: 92.8606 -5.4697 -2.2016 -4.1707 -0.9218 0.0747 2.1429 1.8927 1.0489 4.8850 0.1809 0.0545 1.5984 0.0318 1.2879 0.0589
-#> 61: 92.8939 -5.5167 -2.2169 -4.1567 -0.9434 0.0680 2.1067 1.9160 1.0677 4.6408 0.1775 0.0517 1.5223 0.0404 1.2033 0.0623
-#> 62: 93.1569 -5.6121 -2.2073 -4.1427 -0.9431 0.0717 2.5977 2.0627 1.0518 4.5133 0.1758 0.0494 1.4644 0.0364 1.1857 0.0621
-#> 63: 93.2362 -5.5056 -2.1832 -4.0832 -0.9433 0.0754 3.4639 1.9596 1.0905 4.2877 0.1851 0.0536 1.5500 0.0320 1.2533 0.0610
-#> 64: 93.3935 -5.4320 -2.1735 -4.0754 -0.9601 0.0719 5.0337 1.8616 1.0723 4.0733 0.1907 0.0649 1.5436 0.0270 1.4154 0.0546
-#> 65: 93.1102 -5.5419 -2.1870 -4.0496 -0.9481 0.0753 5.0250 1.9760 1.1263 3.8696 0.1902 0.0617 1.4779 0.0262 1.1326 0.0712
-#> 66: 92.9832 -5.7640 -2.1941 -4.0532 -0.9444 0.0635 5.2049 2.6553 1.1258 3.7699 0.1915 0.0586 1.4926 0.0307 1.0960 0.0645
-#> 67: 92.6674 -5.6976 -2.1858 -4.0855 -0.9209 0.0562 4.9447 2.5225 1.1285 4.0204 0.1948 0.0556 1.4667 0.0315 1.1023 0.0650
-#> 68: 92.7718 -5.7724 -2.1760 -4.0242 -0.9354 0.0441 4.6975 2.8536 1.1471 3.8194 0.1922 0.0529 1.4283 0.0329 1.1174 0.0664
-#> 69: 92.8377 -5.7554 -2.1833 -4.0670 -0.9412 0.0834 4.4626 2.7404 1.1565 3.7904 0.1826 0.0502 1.4628 0.0318 1.0793 0.0747
-#> 70: 92.6830 -5.9071 -2.2266 -4.0604 -0.9399 0.0730 4.2394 3.5629 1.1459 3.7282 0.1734 0.0477 1.4892 0.0331 1.1526 0.0683
-#> 71: 92.5729 -5.8185 -2.2009 -4.0623 -0.9401 0.0878 4.0275 3.3847 1.0886 3.7348 0.1648 0.0453 1.4739 0.0373 1.0902 0.0678
-#> 72: 92.1755 -6.0270 -2.2108 -4.1507 -0.9564 0.0665 3.8261 3.9851 1.1200 4.1726 0.1617 0.0431 1.4478 0.0348 1.1400 0.0673
-#> 73: 91.8986 -6.0175 -2.1916 -4.1416 -0.9347 0.0243 3.6348 4.0607 1.1553 4.0576 0.1802 0.0409 1.4330 0.0406 1.0914 0.0712
-#> 74: 91.7729 -5.8767 -2.1898 -4.0934 -0.9122 0.0184 3.4531 3.8577 1.1254 3.8547 0.1827 0.0389 1.3372 0.0524 1.0717 0.0687
-#> 75: 91.3098 -5.9950 -2.1572 -4.1349 -0.9427 0.0190 3.4756 3.8000 1.1626 3.8402 0.1969 0.0369 1.3378 0.0501 1.1602 0.0685
-#> 76: 91.3766 -5.8701 -2.2042 -4.1128 -0.9081 0.0539 3.9350 3.6100 1.2348 3.7994 0.1891 0.0369 1.3400 0.0495 1.0656 0.0738
-#> 77: 91.6057 -5.7437 -2.1988 -4.1241 -0.8890 0.0500 5.0868 3.4295 1.1971 3.8470 0.1950 0.0469 1.4928 0.0397 1.1129 0.0700
-#> 78: 91.7868 -5.7832 -2.1844 -4.1102 -0.9104 0.0698 4.8325 3.2580 1.1670 3.6547 0.1993 0.0502 1.4336 0.0340 0.9512 0.0805
-#> 79: 91.7221 -5.7881 -2.2166 -4.1137 -0.9160 0.0672 4.5909 3.0951 1.1582 3.5765 0.1928 0.0486 1.4632 0.0352 1.0210 0.0728
-#> 80: 91.8608 -5.8064 -2.2006 -4.0971 -0.9209 0.0642 4.3613 3.2163 1.1481 3.4758 0.1832 0.0462 1.4368 0.0356 1.0605 0.0710
-#> 81: 91.6423 -5.8749 -2.2037 -4.0893 -0.9187 0.0503 4.1432 3.5329 1.0907 3.5148 0.2011 0.0451 1.4719 0.0346 1.1684 0.0646
-#> 82: 91.8319 -6.0898 -2.2251 -4.0826 -0.9368 0.0842 4.1509 4.4964 1.0606 3.4836 0.1910 0.0428 1.4468 0.0387 1.1605 0.0637
-#> 83: 91.9794 -6.0417 -2.1947 -4.1042 -0.9114 0.0741 6.5949 4.5668 1.1113 3.6409 0.1815 0.0407 1.4780 0.0346 1.1277 0.0634
-#> 84: 91.8669 -6.1877 -2.1979 -4.1052 -0.9300 0.0807 6.2651 5.1958 1.1750 3.6752 0.1724 0.0386 1.4931 0.0278 1.0401 0.0685
-#> 85: 91.6789 -6.0634 -2.1896 -4.1357 -0.9371 0.0933 5.9519 4.9360 1.1259 3.8493 0.1732 0.0367 1.5058 0.0275 1.1356 0.0670
-#> 86: 91.6989 -6.2114 -2.2056 -4.1542 -0.9646 0.0882 5.6543 5.0411 1.1091 3.9411 0.1988 0.0349 1.4099 0.0338 1.1811 0.0636
-#> 87: 92.3758 -6.3779 -2.2062 -4.1739 -0.9385 0.0916 5.3716 6.2290 1.1213 4.0290 0.1889 0.0331 1.4809 0.0306 1.1443 0.0626
-#> 88: 92.2757 -6.2016 -2.2215 -4.1389 -0.9582 0.0942 5.1030 5.9176 1.0797 4.0768 0.1990 0.0315 1.4282 0.0386 1.2235 0.0629
-#> 89: 92.1970 -6.3356 -2.2081 -4.1412 -0.9555 0.1057 4.8478 5.9597 1.1474 4.0677 0.1890 0.0299 1.3856 0.0377 1.1807 0.0640
-#> 90: 92.0813 -6.4550 -2.2045 -4.1524 -0.9553 0.0885 4.6054 6.9999 1.1542 3.9901 0.1880 0.0284 1.3416 0.0416 1.1379 0.0653
-#> 91: 91.7111 -6.5289 -2.2203 -4.1763 -0.9288 0.0823 5.4933 6.9237 1.1601 4.0435 0.1839 0.0360 1.3387 0.0401 1.1768 0.0591
-#> 92: 92.1217 -6.5567 -2.2232 -4.2082 -0.9411 0.0815 8.0692 6.7286 1.1684 3.9422 0.1763 0.0411 1.3740 0.0463 1.1538 0.0613
-#> 93: 92.7497 -6.3512 -2.2463 -4.1806 -0.9633 0.0724 7.6657 6.3922 1.1870 3.8858 0.1796 0.0391 1.4232 0.0454 1.3749 0.0497
-#> 94: 92.2679 -6.3542 -2.2473 -4.1873 -0.9382 0.0711 7.2824 6.0726 1.1940 3.8847 0.1956 0.0371 1.3812 0.0465 1.2897 0.0521
-#> 95: 92.0257 -6.2448 -2.2624 -4.1681 -0.9624 0.0810 6.9183 5.7690 1.1345 3.8091 0.1858 0.0359 1.3026 0.0509 1.3000 0.0530
-#> 96: 91.5166 -5.9442 -2.2924 -4.2449 -0.9238 0.1058 7.1159 5.4805 1.1231 4.2529 0.1953 0.0343 1.4063 0.0445 1.3479 0.0482
-#> 97: 91.1606 -5.8541 -2.2912 -4.2398 -0.8875 0.1101 9.4515 5.2065 1.1256 4.3194 0.2081 0.0337 1.3436 0.0498 1.3317 0.0496
-#> 98: 91.2787 -6.0967 -2.2703 -4.2641 -0.9260 0.0869 8.9789 4.9462 1.2070 4.2238 0.1977 0.0373 1.3124 0.0495 1.1362 0.0653
-#> 99: 91.6449 -5.9441 -2.2562 -4.2355 -0.9312 0.1237 8.5300 4.6988 1.2343 4.0468 0.1878 0.0369 1.3508 0.0462 1.0542 0.0704
-#> 100: 91.7795 -5.8857 -2.2516 -4.3381 -0.9344 0.1291 8.1035 4.4639 1.2355 4.6941 0.1968 0.0393 1.4327 0.0358 1.1170 0.0668
-#> 101: 92.2537 -5.7930 -2.2345 -4.3477 -0.9272 0.1340 8.3402 4.2407 1.1961 4.7638 0.1933 0.0402 1.4683 0.0375 1.1216 0.0626
-#> 102: 92.3920 -6.0193 -2.2332 -4.3487 -0.9155 0.1565 11.1006 4.2977 1.1700 4.8048 0.2260 0.0444 1.4443 0.0342 1.0888 0.0674
-#> 103: 92.0043 -5.7825 -2.2376 -4.2616 -0.9043 0.1686 10.5455 4.0829 1.1587 4.5646 0.2147 0.0422 1.4198 0.0338 1.1639 0.0625
-#> 104: 92.1575 -5.8497 -2.2470 -4.2456 -0.9128 0.1762 10.0183 3.8787 1.1405 4.3364 0.2040 0.0440 1.3919 0.0379 1.2040 0.0582
-#> 105: 92.2784 -5.7971 -2.2582 -4.2100 -0.9128 0.1731 9.5173 3.6848 1.1351 4.1196 0.1938 0.0418 1.3982 0.0404 1.1069 0.0656
-#> 106: 92.4336 -5.7752 -2.2690 -4.3771 -0.8925 0.1644 9.0415 3.5005 1.1547 5.0970 0.1841 0.0476 1.3670 0.0423 1.1716 0.0625
-#> 107: 92.5128 -5.8328 -2.2549 -4.4193 -0.9403 0.2268 8.5894 3.3255 1.1160 5.2711 0.1749 0.0453 1.4023 0.0347 1.0279 0.0757
-#> 108: 92.8926 -5.7266 -2.2606 -4.5037 -0.9392 0.2394 8.1599 3.1592 1.1293 5.9652 0.1661 0.0447 1.3837 0.0346 0.9545 0.0747
-#> 109: 92.4657 -5.8687 -2.2884 -4.4108 -0.9043 0.2611 7.7519 4.0001 1.0729 5.6669 0.1578 0.0424 1.3441 0.0351 0.9758 0.0708
-#> 110: 92.6620 -5.6900 -2.2825 -4.4337 -0.9003 0.2602 7.3643 3.8001 1.0843 5.3836 0.1499 0.0433 1.4652 0.0302 0.9950 0.0722
-#> 111: 92.8949 -5.6946 -2.2661 -4.5240 -0.9233 0.2372 6.9961 3.6101 1.0845 5.8133 0.1551 0.0411 1.5005 0.0327 0.9284 0.0753
-#> 112: 93.4237 -5.6562 -2.2474 -4.4809 -0.9441 0.2322 6.6463 3.4296 1.1498 5.5227 0.1474 0.0409 1.4612 0.0317 0.9336 0.0762
-#> 113: 93.1883 -5.6891 -2.2846 -4.3984 -0.9416 0.2317 6.3140 3.2581 1.1062 5.2465 0.1596 0.0463 1.3924 0.0380 1.0268 0.0698
-#> 114: 93.4464 -5.7087 -2.2902 -4.4274 -0.9401 0.2638 5.9983 3.0952 1.1170 5.0203 0.1516 0.0495 1.4108 0.0361 1.0355 0.0682
-#> 115: 93.1873 -5.8732 -2.2668 -4.5086 -0.9636 0.2516 5.6984 3.3427 1.1141 5.7549 0.1440 0.0490 1.5010 0.0309 1.0443 0.0679
-#> 116: 92.6878 -5.8520 -2.2903 -4.5349 -0.9663 0.2612 5.4135 3.2444 1.1048 5.8809 0.1471 0.0511 1.3910 0.0360 1.0423 0.0702
-#> 117: 92.7775 -5.7892 -2.2897 -4.4572 -0.9544 0.2380 5.1428 3.0822 1.0731 5.5869 0.1397 0.0703 1.3493 0.0360 0.9831 0.0713
-#> 118: 93.1533 -5.8045 -2.2859 -4.4787 -0.9667 0.2150 4.8857 3.0277 1.0872 5.6786 0.1439 0.0812 1.3838 0.0373 1.0547 0.0696
-#> 119: 92.8370 -5.7208 -2.2738 -4.4627 -0.9462 0.2095 4.6414 2.8764 1.1172 5.6197 0.1643 0.0772 1.3394 0.0348 0.9180 0.0803
-#> 120: 92.5430 -5.7795 -2.3004 -4.4203 -0.9479 0.2313 4.4093 2.8377 1.1312 5.3387 0.1655 0.0803 1.2967 0.0360 1.0699 0.0761
-#> 121: 92.5318 -5.6550 -2.2866 -4.5065 -0.9166 0.2321 4.1888 2.6959 1.0994 6.0180 0.1686 0.0763 1.3882 0.0322 0.9895 0.0733
-#> 122: 92.7380 -5.6688 -2.2968 -4.4523 -0.9279 0.2529 3.9794 2.5611 1.0642 5.7171 0.1601 0.0851 1.3786 0.0316 0.9358 0.0742
-#> 123: 93.0753 -5.7451 -2.2896 -4.5423 -0.9371 0.2724 3.7804 2.9938 1.0758 5.9349 0.1521 0.0808 1.4275 0.0339 0.9652 0.0727
-#> 124: 93.2708 -5.8004 -2.2782 -4.4951 -0.9451 0.2590 3.5914 3.0594 1.0875 5.6382 0.1607 0.0768 1.3628 0.0340 1.0577 0.0693
-#> 125: 93.4025 -5.7710 -2.2990 -4.4498 -0.9661 0.2633 3.4118 2.9276 1.0809 5.3563 0.1527 0.0730 1.3816 0.0406 1.0295 0.0671
-#> 126: 93.4928 -5.7054 -2.3002 -4.4087 -0.9394 0.2965 3.4732 2.7812 1.1275 5.0884 0.1481 0.0693 1.2949 0.0423 0.9084 0.0726
-#> 127: 93.6449 -5.6593 -2.2683 -4.3418 -0.9194 0.2560 4.2986 2.6422 1.1070 4.8340 0.1449 0.0707 1.4258 0.0341 0.8802 0.0777
-#> 128: 93.7430 -5.6359 -2.2686 -4.4174 -0.9500 0.2279 5.2477 2.5101 1.1046 5.5376 0.1512 0.0859 1.4523 0.0327 0.8659 0.0826
-#> 129: 93.7432 -5.6851 -2.2849 -4.2019 -0.9660 0.1995 7.2497 2.8789 1.1315 5.2607 0.1762 0.0972 1.3901 0.0357 1.1264 0.0743
-#> 130: 93.2409 -5.8965 -2.2946 -4.1880 -0.9774 0.1719 7.4467 3.2276 1.1464 4.9977 0.1720 0.0924 1.3517 0.0446 1.0461 0.0705
-#> 131: 92.7780 -6.0551 -2.2647 -4.1894 -0.9579 0.1391 7.0744 3.7584 1.1291 4.7478 0.1714 0.0995 1.2542 0.0438 0.9139 0.0777
-#> 132: 92.7157 -6.1161 -2.2501 -4.1784 -0.9651 0.1146 6.7207 3.9259 1.1674 4.5104 0.1712 0.0957 1.2549 0.0473 0.8964 0.0803
-#> 133: 92.2696 -5.8545 -2.2717 -4.1907 -0.9782 0.0985 6.3846 3.7296 1.1652 4.2849 0.1626 0.1198 1.2208 0.0498 0.9730 0.0822
-#> 134: 92.2067 -5.8603 -2.2743 -4.2095 -0.9754 0.1398 6.0654 3.5431 1.1551 4.0706 0.1695 0.1138 1.3022 0.0432 0.9960 0.0795
-#> 135: 92.3979 -5.9500 -2.3053 -4.1938 -0.9425 0.1134 5.7621 3.3660 1.1771 3.8671 0.1610 0.1081 1.3373 0.0462 1.1323 0.0665
-#> 136: 92.3749 -5.8701 -2.2979 -4.2493 -0.9386 0.1504 5.4740 3.3090 1.1638 3.9609 0.1724 0.1027 1.3578 0.0389 1.1943 0.0650
-#> 137: 92.6942 -5.9020 -2.2755 -4.2318 -0.9464 0.1541 5.2003 3.5521 1.1704 3.8948 0.1685 0.0976 1.4170 0.0399 1.1472 0.0626
-#> 138: 92.7234 -5.8085 -2.2653 -4.2164 -0.9662 0.1808 4.9403 3.3745 1.1977 3.8348 0.1694 0.0927 1.4229 0.0387 1.0934 0.0708
-#> 139: 92.7341 -5.7737 -2.2685 -4.1759 -0.9334 0.1554 4.6933 3.2057 1.1971 3.6962 0.1917 0.0881 1.4324 0.0363 1.1669 0.0652
-#> 140: 92.1593 -5.6287 -2.2576 -4.1977 -0.9232 0.1345 4.6967 3.0455 1.1676 3.8133 0.2060 0.0837 1.5032 0.0349 1.1418 0.0678
-#> 141: 92.3199 -5.8323 -2.2451 -4.1948 -0.9447 0.1295 4.9624 3.3893 1.1408 3.8423 0.1957 0.0795 1.4470 0.0325 1.0892 0.0739
-#> 142: 92.7246 -6.1252 -2.2304 -4.1984 -0.9160 0.0816 4.7143 4.6501 1.1420 3.8554 0.1901 0.0755 1.4847 0.0386 1.2815 0.0576
-#> 143: 92.4130 -6.0231 -2.2261 -4.2205 -0.9495 0.1020 4.4786 4.4176 1.1454 4.0301 0.1929 0.0717 1.4103 0.0410 1.0418 0.0739
-#> 144: 92.4006 -5.9898 -2.2232 -4.2429 -0.9553 0.1131 4.2547 4.1967 1.1579 4.2583 0.1904 0.0681 1.4272 0.0339 1.0591 0.0737
-#> 145: 92.5011 -6.2340 -2.2232 -4.1872 -0.9560 0.1322 6.1775 4.8941 1.1594 4.0453 0.1811 0.0647 1.4059 0.0298 1.0219 0.0752
-#> 146: 92.7460 -6.2989 -2.2417 -4.2501 -0.9650 0.1527 5.8686 5.6454 1.1154 4.0076 0.1720 0.0758 1.4027 0.0348 1.1220 0.0689
-#> 147: 93.0630 -6.0839 -2.2217 -4.1822 -0.9661 0.1634 5.5752 5.3631 1.0596 3.8072 0.1743 0.0733 1.3682 0.0393 1.0992 0.0700
-#> 148: 92.7639 -5.8682 -2.2550 -4.1926 -0.9440 0.1599 5.8048 5.0950 1.0858 3.6230 0.1749 0.0696 1.3364 0.0436 1.0967 0.0721
-#> 149: 92.6183 -6.1270 -2.2379 -4.1103 -0.9643 0.1202 5.8027 4.8402 1.1089 3.4860 0.1661 0.0661 1.3061 0.0457 1.0014 0.0724
-#> 150: 92.7472 -6.1515 -2.2199 -4.1027 -0.9611 0.1014 5.6767 4.5982 1.1061 3.6113 0.1578 0.0654 1.3543 0.0405 1.0847 0.0707
-#> 151: 92.9566 -5.8911 -2.2174 -4.0722 -0.9516 0.0992 5.9638 4.3683 1.1057 3.5122 0.1767 0.0621 1.3619 0.0396 1.0158 0.0734
-#> 152: 93.0035 -5.8395 -2.2559 -4.0650 -0.9389 0.0928 4.4799 3.2331 1.0387 3.4826 0.1713 0.0604 1.3425 0.0428 1.1101 0.0635
-#> 153: 92.7242 -5.7832 -2.2538 -4.1288 -0.9159 0.1047 4.6102 3.0838 1.0527 3.8052 0.1718 0.0597 1.3905 0.0398 1.1371 0.0635
-#> 154: 92.2125 -5.9077 -2.2400 -4.0922 -0.9106 0.1033 4.4732 3.8350 1.0261 3.6148 0.1955 0.0643 1.3176 0.0419 1.1130 0.0635
-#> 155: 92.6226 -5.6271 -2.2239 -4.0122 -0.8948 0.0647 4.5553 2.5675 1.0412 3.0513 0.1845 0.0866 1.3266 0.0459 1.0244 0.0680
-#> 156: 92.6532 -5.5576 -2.2251 -4.0066 -0.9006 0.0922 3.8517 2.3273 1.0455 3.0971 0.1928 0.0863 1.4000 0.0394 0.9203 0.0754
-#> 157: 92.5192 -5.4834 -2.2356 -4.0069 -0.9321 0.0904 3.0410 1.8841 0.9867 3.1990 0.1905 0.0816 1.3927 0.0407 1.1517 0.0614
-#> 158: 92.5628 -5.5318 -2.2044 -4.0269 -0.9319 0.0742 3.5124 1.9585 1.0692 3.1835 0.1958 0.0934 1.4038 0.0324 0.9680 0.0758
-#> 159: 92.9690 -5.6416 -2.2134 -4.0156 -0.9556 0.0560 4.3830 2.2442 1.0543 3.2358 0.1873 0.0951 1.3624 0.0375 1.1207 0.0696
-#> 160: 92.9861 -5.5872 -2.2207 -3.9908 -0.9190 0.0417 4.1202 2.1685 1.0711 3.1521 0.1766 0.0913 1.3760 0.0371 1.0970 0.0713
-#> 161: 93.3139 -5.5349 -2.1972 -3.9860 -0.9365 0.0011 4.2865 1.8741 1.0759 3.0304 0.2007 0.0750 1.3650 0.0411 1.1220 0.0662
-#> 162: 93.3324 -5.6135 -2.1579 -4.0151 -0.9507 -0.0091 4.6402 2.0208 1.0535 3.0349 0.1935 0.0764 1.4069 0.0383 1.2550 0.0598
-#> 163: 93.0110 -5.5253 -2.1419 -4.0151 -0.9197 -0.0072 5.8946 1.9087 1.0965 3.0349 0.1833 0.0814 1.5095 0.0290 1.1314 0.0665
-#> 164: 93.0848 -5.4980 -2.1670 -4.0213 -0.9345 0.0150 4.9128 1.8293 1.0379 3.0653 0.1728 0.0835 1.4913 0.0343 1.0589 0.0687
-#> 165: 92.9407 -5.3978 -2.1707 -4.0090 -0.9480 0.0126 3.4620 1.3870 1.0594 3.0115 0.1702 0.0982 1.5550 0.0296 1.0978 0.0694
-#> 166: 93.1504 -5.4880 -2.1890 -3.9958 -0.9511 0.0316 2.7859 1.8457 1.0294 3.0739 0.1738 0.1031 1.5109 0.0308 1.1800 0.0651
-#> 167: 92.8442 -5.4673 -2.1984 -4.0259 -0.9262 0.0243 2.0497 1.6348 1.0469 3.1258 0.1650 0.0981 1.6185 0.0291 1.1733 0.0655
-#> 168: 92.9484 -5.6255 -2.2012 -4.0136 -0.9309 0.0199 1.8121 2.0784 1.0415 3.1795 0.1816 0.0929 1.5727 0.0268 1.4222 0.0543
-#> 169: 93.0266 -5.6135 -2.1677 -4.0179 -0.9279 0.0375 1.7553 2.1663 1.0298 3.1675 0.2013 0.0926 1.5356 0.0274 1.2960 0.0596
-#> 170: 92.9844 -5.6286 -2.1839 -4.0509 -0.9471 0.0414 1.9485 2.4078 1.0656 3.2787 0.2112 0.0950 1.5210 0.0265 1.3069 0.0616
-#> 171: 92.6832 -5.6238 -2.2059 -4.0710 -0.9175 0.0383 1.5941 2.2918 1.1095 3.3435 0.1921 0.0895 1.4678 0.0345 1.2189 0.0618
-#> 172: 92.5302 -5.5653 -2.2086 -4.0429 -0.9412 0.0773 1.5302 2.2565 1.1293 3.2157 0.1924 0.0680 1.4438 0.0367 1.2084 0.0661
-#> 173: 92.3877 -5.5357 -2.2141 -4.0246 -0.9268 0.0866 1.2153 2.0588 1.0844 3.2941 0.2060 0.0726 1.4686 0.0359 1.3683 0.0596
-#> 174: 92.4410 -5.4921 -2.1955 -4.0398 -0.9269 0.0645 1.6903 2.0042 1.1236 3.3646 0.1847 0.0804 1.5533 0.0310 1.2320 0.0675
-#> 175: 92.4192 -5.4726 -2.1945 -4.0271 -0.9222 0.0728 1.1344 1.9292 1.1085 3.3173 0.1875 0.0912 1.5350 0.0302 1.2461 0.0679
-#> 176: 92.3581 -5.5256 -2.2055 -3.9958 -0.9211 0.0720 1.1140 1.8097 1.0898 3.1459 0.2018 0.1104 1.4391 0.0323 1.2240 0.0677
-#> 177: 92.2144 -5.6699 -2.2357 -4.0017 -0.9402 0.0785 1.1932 2.6190 1.0355 3.1852 0.2266 0.1125 1.4705 0.0327 1.2866 0.0621
-#> 178: 92.3608 -5.7040 -2.2245 -4.0242 -0.9642 0.0596 0.7932 2.6061 0.9408 3.1080 0.1958 0.1180 1.5158 0.0365 1.3571 0.0600
-#> 179: 92.4358 -5.6877 -2.2243 -4.0166 -0.9486 0.0595 0.7591 2.3791 0.9241 3.0638 0.1900 0.1257 1.4317 0.0363 1.2359 0.0686
-#> 180: 92.5146 -5.7856 -2.2343 -4.0098 -0.9522 0.0522 0.4573 2.6882 0.9636 3.0406 0.1835 0.1270 1.4631 0.0361 1.2192 0.0701
-#> 181: 92.5469 -5.7684 -2.2220 -4.0549 -0.9488 0.0901 0.4189 2.4963 0.9873 3.1470 0.1744 0.1268 1.5165 0.0336 1.1359 0.0760
-#> 182: 92.5829 -5.7658 -2.2385 -4.0362 -0.9723 0.0572 0.3720 2.5387 0.9203 3.0397 0.1769 0.1636 1.4781 0.0375 1.2697 0.0677
-#> 183: 92.5737 -5.9187 -2.2130 -4.0638 -0.9876 0.0797 0.3084 3.3137 0.9467 3.0532 0.1737 0.1599 1.4288 0.0309 1.3024 0.0617
-#> 184: 92.4989 -5.9837 -2.1994 -4.0476 -0.9737 0.0594 0.2533 3.6658 0.9248 3.1230 0.1776 0.1552 1.3829 0.0316 1.2818 0.0621
-#> 185: 92.5677 -6.0227 -2.2084 -4.0403 -0.9584 0.0609 0.2215 3.8810 0.9134 3.0961 0.1739 0.1473 1.4202 0.0319 1.2731 0.0579
-#> 186: 92.7090 -5.9641 -2.2218 -4.0319 -0.9573 0.0575 0.2917 3.9574 0.9373 3.0666 0.1691 0.1703 1.4378 0.0296 1.2775 0.0601
-#> 187: 92.7358 -6.2503 -2.2003 -4.0534 -0.9742 0.0691 0.3037 5.2011 0.9333 3.0796 0.1647 0.1553 1.4254 0.0293 1.1987 0.0629
-#> 188: 92.6733 -6.1434 -2.1988 -4.0792 -0.9878 0.0860 0.3122 4.9451 0.9080 3.1891 0.1628 0.1558 1.4099 0.0317 1.3162 0.0593
-#> 189: 92.7256 -6.0886 -2.1766 -4.0419 -0.9672 0.0550 0.3758 4.3461 0.9140 3.0795 0.1697 0.1649 1.5310 0.0301 1.3258 0.0566
-#> 190: 92.5144 -6.1827 -2.2159 -4.0525 -0.9677 0.0728 0.3855 4.3370 0.9706 3.0518 0.1486 0.1841 1.4390 0.0295 1.1259 0.0740
-#> 191: 92.6209 -6.1257 -2.2287 -4.1095 -0.9670 0.1034 0.3340 4.3051 0.9486 3.1970 0.1549 0.1776 1.4397 0.0296 1.2004 0.0684
-#> 192: 92.6156 -6.1289 -2.2067 -4.1191 -0.9900 0.1090 0.3069 4.1314 0.9134 3.1476 0.1596 0.1912 1.4380 0.0301 1.1238 0.0720
-#> 193: 92.5434 -5.9782 -2.1800 -4.0845 -0.9547 0.1173 0.2694 3.6834 0.9005 2.9479 0.1582 0.1733 1.4538 0.0294 0.8798 0.0866
-#> 194: 92.5884 -5.7815 -2.2110 -4.0714 -0.9510 0.0928 0.2493 2.8236 0.9615 2.9852 0.1488 0.1730 1.4409 0.0297 1.1446 0.0677
-#> 195: 92.6180 -5.9277 -2.2213 -4.0714 -0.9379 0.1177 0.1993 3.5172 0.8976 2.9852 0.1449 0.1735 1.5012 0.0299 1.2131 0.0618
-#> 196: 92.5920 -5.7723 -2.2496 -4.0669 -0.9184 0.1262 0.2595 3.2454 0.9419 2.9697 0.1600 0.1881 1.4017 0.0338 0.9594 0.0790
-#> 197: 92.6292 -5.8658 -2.2434 -4.0640 -0.9365 0.1216 0.2491 3.3540 0.9267 2.9523 0.1598 0.1749 1.3953 0.0383 1.0788 0.0702
-#> 198: 92.6911 -5.8407 -2.2605 -4.0640 -0.9319 0.1264 0.1930 3.2321 0.8884 2.9523 0.1320 0.1940 1.4026 0.0358 1.0613 0.0704
-#> 199: 92.6480 -5.6988 -2.2599 -4.0668 -0.9395 0.1328 0.1412 2.6535 0.8915 2.9610 0.1573 0.2052 1.4353 0.0360 0.9900 0.0742
-#> 200: 92.7139 -5.6152 -2.2522 -4.0684 -0.9192 0.1589 0.1686 2.4362 0.9098 3.0185 0.1702 0.1705 1.4153 0.0338 1.1747 0.0705
-#> 201: 92.7134 -5.7029 -2.2504 -4.0502 -0.9270 0.1453 0.1499 2.6851 0.8909 2.9484 0.1749 0.1772 1.3851 0.0363 1.1255 0.0714
-#> 202: 92.7087 -5.7236 -2.2421 -4.0499 -0.9364 0.1238 0.1324 2.7215 0.8810 2.9507 0.1694 0.1913 1.3864 0.0365 1.1192 0.0705
-#> 203: 92.7013 -5.7563 -2.2293 -4.0494 -0.9394 0.1134 0.1269 2.8279 0.8866 2.9501 0.1618 0.1915 1.3981 0.0356 1.0942 0.0710
-#> 204: 92.6964 -5.8134 -2.2208 -4.0646 -0.9373 0.1144 0.1192 3.1058 0.8973 3.0279 0.1523 0.1983 1.4126 0.0345 1.0629 0.0723
-#> 205: 92.6936 -5.8441 -2.2195 -4.0787 -0.9373 0.1144 0.1068 3.2553 0.9029 3.0962 0.1473 0.2001 1.4217 0.0344 1.0532 0.0719
-#> 206: 92.6881 -5.8805 -2.2209 -4.0887 -0.9432 0.1187 0.1016 3.4269 0.9126 3.1477 0.1479 0.1957 1.4251 0.0348 1.0697 0.0712
-#> 207: 92.6929 -5.9304 -2.2259 -4.0987 -0.9473 0.1234 0.1028 3.6444 0.9261 3.1982 0.1469 0.1910 1.4170 0.0348 1.0586 0.0717
-#> 208: 92.6907 -5.9413 -2.2275 -4.1043 -0.9482 0.1267 0.1038 3.6864 0.9313 3.2244 0.1467 0.1889 1.4121 0.0343 1.0499 0.0718
-#> 209: 92.6917 -5.9265 -2.2304 -4.1109 -0.9498 0.1289 0.1022 3.5975 0.9363 3.2487 0.1478 0.1863 1.4053 0.0344 1.0521 0.0716
-#> 210: 92.6966 -5.9218 -2.2322 -4.1164 -0.9516 0.1337 0.0984 3.5650 0.9413 3.2688 0.1493 0.1874 1.3949 0.0342 1.0499 0.0719
-#> 211: 92.7020 -5.9160 -2.2351 -4.1209 -0.9542 0.1385 0.0958 3.5091 0.9390 3.2968 0.1503 0.1873 1.3925 0.0345 1.0547 0.0718
-#> 212: 92.7065 -5.9119 -2.2376 -4.1247 -0.9564 0.1432 0.0933 3.4520 0.9373 3.3205 0.1531 0.1901 1.3869 0.0346 1.0625 0.0717
-#> 213: 92.7107 -5.9047 -2.2402 -4.1286 -0.9575 0.1455 0.0930 3.3990 0.9361 3.3369 0.1536 0.1932 1.3814 0.0349 1.0698 0.0712
-#> 214: 92.7110 -5.9061 -2.2415 -4.1321 -0.9585 0.1483 0.0921 3.3864 0.9364 3.3517 0.1542 0.1963 1.3794 0.0348 1.0721 0.0712
-#> 215: 92.7116 -5.9128 -2.2417 -4.1360 -0.9581 0.1510 0.0941 3.4201 0.9347 3.3646 0.1545 0.1988 1.3764 0.0350 1.0731 0.0712
-#> 216: 92.7135 -5.9184 -2.2432 -4.1383 -0.9589 0.1540 0.0957 3.4623 0.9337 3.3698 0.1541 0.2016 1.3761 0.0353 1.0737 0.0714
-#> 217: 92.7143 -5.9262 -2.2453 -4.1428 -0.9604 0.1568 0.0981 3.5202 0.9323 3.3854 0.1542 0.2053 1.3770 0.0352 1.0779 0.0716
-#> 218: 92.7102 -5.9169 -2.2463 -4.1446 -0.9606 0.1604 0.1000 3.4823 0.9305 3.3851 0.1530 0.2083 1.3802 0.0353 1.0819 0.0716
-#> 219: 92.7062 -5.9089 -2.2470 -4.1481 -0.9597 0.1636 0.1000 3.4465 0.9295 3.3874 0.1529 0.2125 1.3779 0.0352 1.0836 0.0716
-#> 220: 92.7027 -5.9052 -2.2480 -4.1509 -0.9594 0.1668 0.1020 3.4302 0.9264 3.3877 0.1531 0.2168 1.3780 0.0352 1.0893 0.0713
-#> 221: 92.7029 -5.8990 -2.2497 -4.1541 -0.9586 0.1696 0.1017 3.4007 0.9227 3.3916 0.1535 0.2208 1.3781 0.0354 1.0925 0.0709
-#> 222: 92.7063 -5.8993 -2.2519 -4.1604 -0.9582 0.1732 0.1025 3.4099 0.9190 3.4135 0.1537 0.2268 1.3791 0.0355 1.1031 0.0702
-#> 223: 92.7090 -5.8932 -2.2537 -4.1669 -0.9573 0.1757 0.1022 3.3946 0.9157 3.4424 0.1543 0.2319 1.3802 0.0356 1.1040 0.0701
-#> 224: 92.7116 -5.8930 -2.2545 -4.1712 -0.9561 0.1774 0.1017 3.3964 0.9133 3.4673 0.1550 0.2355 1.3795 0.0356 1.1018 0.0701
-#> 225: 92.7136 -5.8911 -2.2564 -4.1715 -0.9551 0.1788 0.1016 3.4013 0.9125 3.4628 0.1548 0.2380 1.3756 0.0359 1.1003 0.0700
-#> 226: 92.7153 -5.8883 -2.2569 -4.1711 -0.9536 0.1793 0.1016 3.4046 0.9134 3.4575 0.1549 0.2398 1.3737 0.0360 1.1016 0.0699
-#> 227: 92.7163 -5.8830 -2.2575 -4.1720 -0.9526 0.1796 0.1019 3.3952 0.9129 3.4575 0.1545 0.2407 1.3718 0.0363 1.1015 0.0698
-#> 228: 92.7182 -5.8865 -2.2578 -4.1728 -0.9528 0.1804 0.1017 3.4198 0.9113 3.4576 0.1538 0.2433 1.3722 0.0363 1.1068 0.0695
-#> 229: 92.7199 -5.8965 -2.2578 -4.1718 -0.9523 0.1812 0.1023 3.5030 0.9097 3.4503 0.1529 0.2463 1.3749 0.0363 1.1093 0.0694
-#> 230: 92.7205 -5.8997 -2.2578 -4.1712 -0.9514 0.1825 0.1025 3.5337 0.9071 3.4446 0.1519 0.2497 1.3802 0.0362 1.1115 0.0693
-#> 231: 92.7208 -5.9001 -2.2581 -4.1711 -0.9511 0.1838 0.1044 3.5537 0.9037 3.4423 0.1510 0.2533 1.3834 0.0361 1.1125 0.0693
-#> 232: 92.7183 -5.9041 -2.2588 -4.1715 -0.9504 0.1855 0.1061 3.5958 0.9001 3.4391 0.1503 0.2572 1.3871 0.0362 1.1161 0.0690
-#> 233: 92.7169 -5.9106 -2.2593 -4.1725 -0.9490 0.1866 0.1073 3.6433 0.8968 3.4367 0.1496 0.2609 1.3900 0.0362 1.1179 0.0688
-#> 234: 92.7125 -5.9165 -2.2594 -4.1728 -0.9479 0.1873 0.1098 3.6870 0.8932 3.4321 0.1498 0.2641 1.3907 0.0363 1.1177 0.0687
-#> 235: 92.7072 -5.9203 -2.2592 -4.1729 -0.9472 0.1876 0.1128 3.7229 0.8899 3.4269 0.1506 0.2676 1.3913 0.0364 1.1212 0.0686
-#> 236: 92.7048 -5.9319 -2.2603 -4.1724 -0.9467 0.1879 0.1147 3.7863 0.8879 3.4175 0.1510 0.2705 1.3898 0.0365 1.1181 0.0688
-#> 237: 92.7037 -5.9349 -2.2609 -4.1720 -0.9461 0.1881 0.1152 3.8047 0.8862 3.4096 0.1512 0.2731 1.3891 0.0367 1.1164 0.0688
-#> 238: 92.7027 -5.9359 -2.2605 -4.1715 -0.9459 0.1884 0.1151 3.7997 0.8842 3.4023 0.1516 0.2755 1.3905 0.0366 1.1171 0.0688
-#> 239: 92.7027 -5.9375 -2.2599 -4.1712 -0.9463 0.1881 0.1143 3.8187 0.8835 3.3954 0.1521 0.2780 1.3923 0.0366 1.1193 0.0688
-#> 240: 92.7025 -5.9409 -2.2593 -4.1710 -0.9467 0.1884 0.1135 3.8437 0.8830 3.3888 0.1530 0.2797 1.3939 0.0366 1.1266 0.0685
-#> 241: 92.7006 -5.9429 -2.2589 -4.1703 -0.9469 0.1887 0.1130 3.8580 0.8825 3.3820 0.1529 0.2815 1.3967 0.0364 1.1299 0.0685
-#> 242: 92.6977 -5.9366 -2.2594 -4.1693 -0.9471 0.1887 0.1130 3.8245 0.8810 3.3742 0.1534 0.2833 1.3967 0.0364 1.1323 0.0685
-#> 243: 92.6951 -5.9310 -2.2605 -4.1683 -0.9473 0.1891 0.1131 3.7904 0.8807 3.3666 0.1541 0.2853 1.3953 0.0364 1.1380 0.0683
-#> 244: 92.6928 -5.9289 -2.2610 -4.1680 -0.9471 0.1899 0.1130 3.7709 0.8797 3.3604 0.1545 0.2880 1.3947 0.0364 1.1399 0.0683
-#> 245: 92.6902 -5.9291 -2.2615 -4.1677 -0.9472 0.1914 0.1129 3.7637 0.8787 3.3538 0.1549 0.2898 1.3942 0.0364 1.1440 0.0681
-#> 246: 92.6880 -5.9271 -2.2617 -4.1677 -0.9472 0.1926 0.1131 3.7457 0.8785 3.3500 0.1549 0.2916 1.3938 0.0364 1.1468 0.0681
-#> 247: 92.6865 -5.9264 -2.2613 -4.1676 -0.9471 0.1930 0.1127 3.7331 0.8793 3.3487 0.1551 0.2918 1.3931 0.0364 1.1464 0.0683
-#> 248: 92.6855 -5.9212 -2.2604 -4.1671 -0.9476 0.1935 0.1116 3.7055 0.8795 3.3451 0.1549 0.2923 1.3942 0.0363 1.1453 0.0684
-#> 249: 92.6848 -5.9190 -2.2600 -4.1667 -0.9482 0.1939 0.1110 3.6857 0.8801 3.3428 0.1548 0.2923 1.3942 0.0363 1.1440 0.0685
-#> 250: 92.6858 -5.9194 -2.2605 -4.1663 -0.9489 0.1945 0.1109 3.6821 0.8806 3.3397 0.1547 0.2920 1.3932 0.0363 1.1430 0.0686
-#> 251: 92.6849 -5.9179 -2.2610 -4.1665 -0.9492 0.1950 0.1111 3.6795 0.8814 3.3392 0.1550 0.2919 1.3922 0.0364 1.1434 0.0685
-#> 252: 92.6848 -5.9141 -2.2615 -4.1660 -0.9493 0.1957 0.1110 3.6611 0.8818 3.3363 0.1548 0.2918 1.3919 0.0364 1.1423 0.0686
-#> 253: 92.6837 -5.9110 -2.2637 -4.1634 -0.9493 0.1952 0.1114 3.6462 0.8788 3.3481 0.1550 0.2920 1.3941 0.0363 1.1417 0.0688
-#> 254: 92.6827 -5.9082 -2.2650 -4.1608 -0.9492 0.1944 0.1117 3.6309 0.8753 3.3595 0.1548 0.2921 1.3964 0.0361 1.1415 0.0688
-#> 255: 92.6829 -5.9076 -2.2662 -4.1585 -0.9495 0.1934 0.1118 3.6221 0.8723 3.3737 0.1547 0.2923 1.3977 0.0359 1.1397 0.0689
-#> 256: 92.6821 -5.9079 -2.2672 -4.1559 -0.9495 0.1923 0.1118 3.6279 0.8697 3.3865 0.1547 0.2925 1.3990 0.0357 1.1387 0.0691
-#> 257: 92.6822 -5.9054 -2.2686 -4.1534 -0.9499 0.1914 0.1119 3.6202 0.8673 3.3988 0.1548 0.2923 1.4010 0.0356 1.1438 0.0690
-#> 258: 92.6828 -5.9054 -2.2700 -4.1509 -0.9498 0.1900 0.1121 3.6166 0.8651 3.4085 0.1547 0.2926 1.4028 0.0356 1.1473 0.0688
-#> 259: 92.6842 -5.9087 -2.2710 -4.1474 -0.9496 0.1890 0.1128 3.6314 0.8629 3.4154 0.1548 0.2923 1.4040 0.0355 1.1482 0.0689
-#> 260: 92.6852 -5.9118 -2.2717 -4.1444 -0.9493 0.1885 0.1124 3.6485 0.8606 3.4227 0.1544 0.2919 1.4073 0.0354 1.1518 0.0688
-#> 261: 92.6858 -5.9137 -2.2721 -4.1419 -0.9493 0.1882 0.1122 3.6641 0.8581 3.4314 0.1543 0.2913 1.4106 0.0353 1.1577 0.0684
-#> 262: 92.6861 -5.9117 -2.2726 -4.1394 -0.9493 0.1881 0.1116 3.6572 0.8558 3.4391 0.1541 0.2908 1.4137 0.0352 1.1613 0.0682
-#> 263: 92.6855 -5.9124 -2.2730 -4.1372 -0.9494 0.1875 0.1113 3.6626 0.8533 3.4465 0.1541 0.2905 1.4152 0.0351 1.1636 0.0681
-#> 264: 92.6841 -5.9137 -2.2734 -4.1351 -0.9496 0.1871 0.1109 3.6703 0.8505 3.4529 0.1538 0.2903 1.4156 0.0350 1.1632 0.0681
-#> 265: 92.6833 -5.9153 -2.2741 -4.1327 -0.9498 0.1867 0.1108 3.6816 0.8472 3.4581 0.1535 0.2899 1.4168 0.0350 1.1647 0.0679
-#> 266: 92.6835 -5.9147 -2.2752 -4.1307 -0.9497 0.1865 0.1107 3.6768 0.8450 3.4641 0.1531 0.2896 1.4176 0.0349 1.1640 0.0679
-#> 267: 92.6835 -5.9167 -2.2761 -4.1283 -0.9499 0.1862 0.1105 3.6851 0.8430 3.4700 0.1530 0.2892 1.4178 0.0348 1.1639 0.0679
-#> 268: 92.6841 -5.9141 -2.2767 -4.1269 -0.9503 0.1860 0.1107 3.6718 0.8407 3.4775 0.1533 0.2891 1.4187 0.0348 1.1673 0.0677
-#> 269: 92.6845 -5.9094 -2.2774 -4.1253 -0.9503 0.1855 0.1112 3.6520 0.8384 3.4840 0.1535 0.2890 1.4192 0.0348 1.1686 0.0675
-#> 270: 92.6847 -5.9042 -2.2779 -4.1239 -0.9505 0.1853 0.1107 3.6288 0.8365 3.4895 0.1536 0.2889 1.4192 0.0347 1.1698 0.0675
-#> 271: 92.6849 -5.9000 -2.2785 -4.1228 -0.9506 0.1853 0.1102 3.6083 0.8348 3.4956 0.1536 0.2889 1.4191 0.0346 1.1692 0.0676
-#> 272: 92.6850 -5.8965 -2.2794 -4.1223 -0.9507 0.1853 0.1092 3.5892 0.8331 3.5071 0.1538 0.2889 1.4194 0.0345 1.1700 0.0676
-#> 273: 92.6851 -5.8916 -2.2805 -4.1222 -0.9508 0.1850 0.1089 3.5697 0.8315 3.5211 0.1538 0.2889 1.4209 0.0345 1.1720 0.0675
-#> 274: 92.6849 -5.8898 -2.2815 -4.1218 -0.9506 0.1852 0.1084 3.5607 0.8301 3.5339 0.1542 0.2886 1.4221 0.0344 1.1728 0.0675
-#> 275: 92.6844 -5.8885 -2.2830 -4.1215 -0.9504 0.1855 0.1080 3.5514 0.8284 3.5491 0.1545 0.2883 1.4238 0.0343 1.1756 0.0673
-#> 276: 92.6834 -5.8885 -2.2843 -4.1210 -0.9501 0.1859 0.1077 3.5477 0.8272 3.5648 0.1547 0.2878 1.4243 0.0343 1.1749 0.0674
-#> 277: 92.6829 -5.8892 -2.2858 -4.1208 -0.9500 0.1862 0.1071 3.5505 0.8257 3.5807 0.1552 0.2872 1.4244 0.0343 1.1747 0.0674
-#> 278: 92.6825 -5.8885 -2.2871 -4.1205 -0.9499 0.1862 0.1072 3.5463 0.8245 3.5960 0.1555 0.2866 1.4247 0.0343 1.1742 0.0675
-#> 279: 92.6815 -5.8887 -2.2883 -4.1201 -0.9501 0.1864 0.1072 3.5433 0.8239 3.6088 0.1556 0.2860 1.4247 0.0343 1.1737 0.0676
-#> 280: 92.6800 -5.8901 -2.2896 -4.1211 -0.9503 0.1865 0.1078 3.5481 0.8238 3.6285 0.1556 0.2848 1.4252 0.0344 1.1742 0.0676
-#> 281: 92.6779 -5.8914 -2.2907 -4.1218 -0.9502 0.1865 0.1084 3.5491 0.8240 3.6471 0.1558 0.2838 1.4251 0.0343 1.1732 0.0677
-#> 282: 92.6767 -5.8906 -2.2919 -4.1236 -0.9501 0.1862 0.1091 3.5462 0.8248 3.6747 0.1558 0.2825 1.4250 0.0344 1.1732 0.0677
-#> 283: 92.6750 -5.8895 -2.2928 -4.1253 -0.9499 0.1857 0.1097 3.5418 0.8260 3.7025 0.1555 0.2814 1.4253 0.0344 1.1712 0.0678
-#> 284: 92.6736 -5.8903 -2.2934 -4.1271 -0.9497 0.1854 0.1107 3.5438 0.8269 3.7297 0.1553 0.2800 1.4257 0.0343 1.1698 0.0678
-#> 285: 92.6730 -5.8917 -2.2942 -4.1284 -0.9497 0.1852 0.1116 3.5481 0.8274 3.7528 0.1551 0.2787 1.4260 0.0343 1.1689 0.0678
-#> 286: 92.6715 -5.8913 -2.2947 -4.1285 -0.9492 0.1849 0.1122 3.5473 0.8274 3.7660 0.1550 0.2775 1.4265 0.0342 1.1678 0.0679
-#> 287: 92.6702 -5.8925 -2.2952 -4.1290 -0.9489 0.1846 0.1125 3.5531 0.8268 3.7818 0.1549 0.2764 1.4269 0.0342 1.1673 0.0678
-#> 288: 92.6688 -5.8918 -2.2959 -4.1290 -0.9490 0.1843 0.1126 3.5495 0.8262 3.7946 0.1546 0.2756 1.4275 0.0341 1.1673 0.0678
-#> 289: 92.6673 -5.8907 -2.2966 -4.1295 -0.9490 0.1841 0.1124 3.5445 0.8260 3.8067 0.1543 0.2750 1.4280 0.0342 1.1690 0.0677
-#> 290: 92.6657 -5.8909 -2.2973 -4.1302 -0.9490 0.1838 0.1123 3.5433 0.8260 3.8201 0.1540 0.2744 1.4279 0.0342 1.1687 0.0676
-#> 291: 92.6642 -5.8902 -2.2978 -4.1312 -0.9493 0.1835 0.1124 3.5399 0.8262 3.8365 0.1538 0.2738 1.4279 0.0342 1.1695 0.0676
-#> 292: 92.6635 -5.8917 -2.2983 -4.1316 -0.9495 0.1831 0.1121 3.5453 0.8263 3.8517 0.1535 0.2733 1.4275 0.0342 1.1695 0.0675
-#> 293: 92.6622 -5.8936 -2.2991 -4.1323 -0.9497 0.1830 0.1121 3.5526 0.8265 3.8692 0.1533 0.2728 1.4274 0.0342 1.1701 0.0675
-#> 294: 92.6604 -5.8936 -2.2999 -4.1328 -0.9499 0.1826 0.1126 3.5505 0.8263 3.8838 0.1533 0.2723 1.4273 0.0342 1.1712 0.0675
-#> 295: 92.6593 -5.8924 -2.3007 -4.1329 -0.9498 0.1823 0.1131 3.5443 0.8262 3.9004 0.1531 0.2717 1.4276 0.0342 1.1718 0.0674
-#> 296: 92.6586 -5.8906 -2.3016 -4.1323 -0.9496 0.1822 0.1133 3.5374 0.8266 3.9103 0.1530 0.2707 1.4272 0.0343 1.1714 0.0674
-#> 297: 92.6578 -5.8889 -2.3026 -4.1329 -0.9494 0.1819 0.1139 3.5315 0.8271 3.9280 0.1528 0.2697 1.4267 0.0343 1.1697 0.0675
-#> 298: 92.6575 -5.8885 -2.3036 -4.1330 -0.9490 0.1814 0.1143 3.5303 0.8275 3.9410 0.1527 0.2689 1.4263 0.0344 1.1688 0.0675
-#> 299: 92.6566 -5.8879 -2.3047 -4.1329 -0.9488 0.1807 0.1147 3.5286 0.8282 3.9507 0.1526 0.2679 1.4263 0.0345 1.1680 0.0674
-#> 300: 92.6555 -5.8862 -2.3057 -4.1325 -0.9483 0.1802 0.1151 3.5225 0.8293 3.9582 0.1527 0.2671 1.4261 0.0345 1.1677 0.0674
-#> 301: 92.6545 -5.8854 -2.3067 -4.1326 -0.9480 0.1795 0.1156 3.5191 0.8300 3.9691 0.1530 0.2665 1.4257 0.0346 1.1672 0.0674
-#> 302: 92.6539 -5.8839 -2.3078 -4.1322 -0.9477 0.1788 0.1161 3.5154 0.8309 3.9769 0.1532 0.2657 1.4252 0.0346 1.1664 0.0675
-#> 303: 92.6541 -5.8799 -2.3089 -4.1327 -0.9474 0.1782 0.1161 3.5012 0.8319 3.9913 0.1534 0.2649 1.4242 0.0347 1.1653 0.0675
-#> 304: 92.6554 -5.8766 -2.3096 -4.1326 -0.9472 0.1774 0.1164 3.4879 0.8328 3.9978 0.1536 0.2641 1.4234 0.0348 1.1644 0.0675
-#> 305: 92.6559 -5.8732 -2.3104 -4.1325 -0.9470 0.1764 0.1161 3.4740 0.8334 4.0037 0.1535 0.2633 1.4231 0.0348 1.1634 0.0676
-#> 306: 92.6564 -5.8717 -2.3113 -4.1322 -0.9470 0.1758 0.1161 3.4705 0.8341 4.0097 0.1537 0.2622 1.4236 0.0348 1.1628 0.0676
-#> 307: 92.6573 -5.8703 -2.3121 -4.1320 -0.9469 0.1748 0.1158 3.4630 0.8349 4.0154 0.1538 0.2614 1.4231 0.0348 1.1617 0.0677
-#> 308: 92.6578 -5.8695 -2.3129 -4.1318 -0.9465 0.1738 0.1154 3.4585 0.8356 4.0210 0.1540 0.2607 1.4229 0.0348 1.1604 0.0677
-#> 309: 92.6577 -5.8691 -2.3132 -4.1317 -0.9465 0.1732 0.1151 3.4548 0.8369 4.0270 0.1540 0.2596 1.4233 0.0348 1.1589 0.0678
-#> 310: 92.6580 -5.8680 -2.3135 -4.1309 -0.9466 0.1727 0.1147 3.4472 0.8377 4.0280 0.1540 0.2587 1.4231 0.0348 1.1569 0.0679
-#> 311: 92.6575 -5.8681 -2.3141 -4.1303 -0.9466 0.1722 0.1144 3.4477 0.8384 4.0303 0.1539 0.2577 1.4236 0.0348 1.1557 0.0679
-#> 312: 92.6571 -5.8685 -2.3145 -4.1299 -0.9467 0.1720 0.1143 3.4498 0.8393 4.0328 0.1538 0.2566 1.4237 0.0348 1.1545 0.0680
-#> 313: 92.6559 -5.8685 -2.3150 -4.1296 -0.9469 0.1718 0.1142 3.4483 0.8403 4.0358 0.1537 0.2555 1.4234 0.0348 1.1532 0.0681
-#> 314: 92.6543 -5.8699 -2.3155 -4.1294 -0.9471 0.1715 0.1142 3.4526 0.8404 4.0401 0.1537 0.2546 1.4236 0.0347 1.1522 0.0681
-#> 315: 92.6528 -5.8713 -2.3161 -4.1289 -0.9472 0.1712 0.1144 3.4584 0.8402 4.0427 0.1537 0.2538 1.4234 0.0347 1.1520 0.0682
-#> 316: 92.6510 -5.8726 -2.3166 -4.1283 -0.9472 0.1705 0.1146 3.4647 0.8404 4.0443 0.1537 0.2528 1.4236 0.0347 1.1511 0.0682
-#> 317: 92.6496 -5.8736 -2.3170 -4.1281 -0.9474 0.1699 0.1147 3.4701 0.8406 4.0497 0.1536 0.2520 1.4238 0.0347 1.1504 0.0683
-#> 318: 92.6479 -5.8745 -2.3174 -4.1276 -0.9475 0.1695 0.1153 3.4729 0.8410 4.0511 0.1535 0.2510 1.4238 0.0347 1.1503 0.0683
-#> 319: 92.6463 -5.8773 -2.3175 -4.1272 -0.9476 0.1690 0.1155 3.4868 0.8409 4.0527 0.1535 0.2502 1.4234 0.0347 1.1484 0.0685
-#> 320: 92.6447 -5.8770 -2.3179 -4.1263 -0.9478 0.1684 0.1158 3.4849 0.8407 4.0516 0.1534 0.2493 1.4238 0.0347 1.1483 0.0685
-#> 321: 92.6433 -5.8768 -2.3181 -4.1255 -0.9479 0.1679 0.1161 3.4850 0.8405 4.0511 0.1533 0.2485 1.4238 0.0346 1.1474 0.0686
-#> 322: 92.6425 -5.8766 -2.3182 -4.1246 -0.9480 0.1673 0.1161 3.4839 0.8403 4.0505 0.1530 0.2474 1.4243 0.0346 1.1458 0.0687
-#> 323: 92.6414 -5.8778 -2.3183 -4.1241 -0.9481 0.1669 0.1162 3.4888 0.8402 4.0517 0.1530 0.2466 1.4244 0.0346 1.1454 0.0687
-#> 324: 92.6404 -5.8771 -2.3186 -4.1236 -0.9482 0.1666 0.1161 3.4855 0.8401 4.0525 0.1529 0.2459 1.4247 0.0345 1.1446 0.0687
-#> 325: 92.6396 -5.8753 -2.3188 -4.1231 -0.9483 0.1664 0.1156 3.4767 0.8396 4.0533 0.1529 0.2454 1.4253 0.0345 1.1438 0.0689
-#> 326: 92.6397 -5.8766 -2.3192 -4.1226 -0.9484 0.1663 0.1152 3.4798 0.8389 4.0542 0.1527 0.2449 1.4253 0.0345 1.1431 0.0690
-#> 327: 92.6395 -5.8785 -2.3197 -4.1224 -0.9483 0.1660 0.1151 3.4880 0.8382 4.0557 0.1528 0.2445 1.4250 0.0345 1.1430 0.0690
-#> 328: 92.6397 -5.8805 -2.3202 -4.1221 -0.9483 0.1657 0.1153 3.5011 0.8373 4.0568 0.1528 0.2442 1.4246 0.0345 1.1427 0.0690
-#> 329: 92.6390 -5.8838 -2.3208 -4.1219 -0.9482 0.1655 0.1161 3.5176 0.8365 4.0580 0.1530 0.2439 1.4241 0.0345 1.1429 0.0690
-#> 330: 92.6380 -5.8862 -2.3215 -4.1216 -0.9484 0.1653 0.1166 3.5286 0.8355 4.0584 0.1529 0.2437 1.4234 0.0346 1.1428 0.0690
-#> 331: 92.6367 -5.8867 -2.3223 -4.1206 -0.9484 0.1651 0.1165 3.5288 0.8348 4.0577 0.1528 0.2435 1.4233 0.0346 1.1429 0.0690
-#> 332: 92.6360 -5.8859 -2.3230 -4.1199 -0.9485 0.1650 0.1165 3.5235 0.8343 4.0572 0.1527 0.2433 1.4227 0.0346 1.1429 0.0689
-#> 333: 92.6361 -5.8839 -2.3237 -4.1194 -0.9485 0.1649 0.1162 3.5142 0.8340 4.0564 0.1527 0.2430 1.4224 0.0347 1.1429 0.0689
-#> 334: 92.6359 -5.8824 -2.3244 -4.1190 -0.9486 0.1649 0.1158 3.5070 0.8337 4.0567 0.1527 0.2424 1.4218 0.0347 1.1442 0.0689
-#> 335: 92.6366 -5.8826 -2.3250 -4.1186 -0.9485 0.1645 0.1157 3.5069 0.8334 4.0574 0.1527 0.2419 1.4214 0.0347 1.1448 0.0688
-#> 336: 92.6374 -5.8816 -2.3253 -4.1182 -0.9486 0.1644 0.1158 3.5034 0.8330 4.0580 0.1528 0.2415 1.4212 0.0347 1.1471 0.0687
-#> 337: 92.6378 -5.8810 -2.3258 -4.1176 -0.9487 0.1642 0.1159 3.5023 0.8325 4.0582 0.1528 0.2410 1.4212 0.0347 1.1467 0.0688
-#> 338: 92.6383 -5.8814 -2.3262 -4.1168 -0.9488 0.1637 0.1160 3.5028 0.8322 4.0571 0.1526 0.2409 1.4216 0.0346 1.1456 0.0689
-#> 339: 92.6392 -5.8808 -2.3266 -4.1160 -0.9490 0.1631 0.1161 3.4989 0.8318 4.0566 0.1524 0.2408 1.4220 0.0346 1.1441 0.0690
-#> 340: 92.6393 -5.8810 -2.3269 -4.1152 -0.9491 0.1626 0.1157 3.4997 0.8316 4.0564 0.1524 0.2407 1.4216 0.0346 1.1419 0.0692
-#> 341: 92.6394 -5.8807 -2.3272 -4.1148 -0.9492 0.1619 0.1153 3.4966 0.8308 4.0552 0.1523 0.2405 1.4218 0.0346 1.1415 0.0692
-#> 342: 92.6394 -5.8806 -2.3274 -4.1141 -0.9493 0.1612 0.1146 3.4936 0.8303 4.0537 0.1522 0.2405 1.4221 0.0346 1.1406 0.0692
-#> 343: 92.6398 -5.8819 -2.3277 -4.1134 -0.9494 0.1606 0.1141 3.4961 0.8297 4.0519 0.1522 0.2402 1.4219 0.0347 1.1404 0.0692
-#> 344: 92.6401 -5.8823 -2.3280 -4.1128 -0.9497 0.1599 0.1137 3.4963 0.8293 4.0504 0.1523 0.2400 1.4214 0.0346 1.1404 0.0692
-#> 345: 92.6404 -5.8829 -2.3283 -4.1124 -0.9498 0.1593 0.1136 3.4958 0.8289 4.0494 0.1523 0.2396 1.4214 0.0346 1.1398 0.0692
-#> 346: 92.6405 -5.8829 -2.3283 -4.1119 -0.9499 0.1587 0.1135 3.4953 0.8287 4.0484 0.1522 0.2394 1.4216 0.0346 1.1397 0.0692
-#> 347: 92.6404 -5.8833 -2.3288 -4.1117 -0.9500 0.1582 0.1133 3.4965 0.8289 4.0480 0.1521 0.2391 1.4211 0.0346 1.1388 0.0692
-#> 348: 92.6407 -5.8838 -2.3293 -4.1113 -0.9502 0.1578 0.1132 3.4978 0.8290 4.0471 0.1520 0.2388 1.4209 0.0346 1.1385 0.0692
-#> 349: 92.6409 -5.8847 -2.3299 -4.1110 -0.9503 0.1571 0.1128 3.5024 0.8290 4.0474 0.1519 0.2386 1.4207 0.0347 1.1379 0.0692
-#> 350: 92.6413 -5.8853 -2.3304 -4.1107 -0.9504 0.1567 0.1125 3.5037 0.8287 4.0478 0.1519 0.2383 1.4207 0.0347 1.1366 0.0693
-#> 351: 92.6415 -5.8868 -2.3310 -4.1104 -0.9504 0.1562 0.1122 3.5109 0.8287 4.0490 0.1518 0.2378 1.4208 0.0347 1.1364 0.0693
-#> 352: 92.6413 -5.8882 -2.3316 -4.1103 -0.9504 0.1557 0.1120 3.5196 0.8287 4.0517 0.1517 0.2375 1.4207 0.0346 1.1361 0.0693
-#> 353: 92.6414 -5.8890 -2.3322 -4.1101 -0.9503 0.1553 0.1117 3.5237 0.8290 4.0533 0.1517 0.2371 1.4202 0.0346 1.1345 0.0693
-#> 354: 92.6417 -5.8879 -2.3327 -4.1099 -0.9502 0.1548 0.1115 3.5206 0.8294 4.0546 0.1515 0.2368 1.4200 0.0346 1.1336 0.0694
-#> 355: 92.6417 -5.8882 -2.3333 -4.1096 -0.9500 0.1541 0.1115 3.5265 0.8296 4.0548 0.1514 0.2364 1.4203 0.0346 1.1325 0.0694
-#> 356: 92.6414 -5.8881 -2.3338 -4.1093 -0.9497 0.1535 0.1115 3.5339 0.8299 4.0553 0.1513 0.2362 1.4204 0.0346 1.1318 0.0694
-#> 357: 92.6414 -5.8874 -2.3343 -4.1087 -0.9497 0.1529 0.1117 3.5320 0.8302 4.0548 0.1512 0.2358 1.4205 0.0346 1.1315 0.0694
-#> 358: 92.6415 -5.8865 -2.3349 -4.1087 -0.9497 0.1523 0.1118 3.5274 0.8308 4.0583 0.1510 0.2354 1.4206 0.0346 1.1308 0.0695
-#> 359: 92.6415 -5.8855 -2.3352 -4.1085 -0.9497 0.1518 0.1123 3.5208 0.8308 4.0597 0.1509 0.2349 1.4205 0.0346 1.1298 0.0695
-#> 360: 92.6413 -5.8851 -2.3356 -4.1080 -0.9496 0.1513 0.1125 3.5176 0.8308 4.0606 0.1508 0.2344 1.4207 0.0346 1.1289 0.0695
-#> 361: 92.6412 -5.8854 -2.3359 -4.1076 -0.9498 0.1508 0.1126 3.5187 0.8308 4.0618 0.1508 0.2338 1.4214 0.0345 1.1279 0.0695
-#> 362: 92.6415 -5.8861 -2.3362 -4.1072 -0.9499 0.1503 0.1126 3.5210 0.8306 4.0636 0.1507 0.2333 1.4218 0.0345 1.1273 0.0695
-#> 363: 92.6412 -5.8884 -2.3364 -4.1066 -0.9499 0.1498 0.1126 3.5327 0.8305 4.0646 0.1507 0.2328 1.4221 0.0345 1.1273 0.0695
-#> 364: 92.6411 -5.8895 -2.3367 -4.1062 -0.9501 0.1494 0.1126 3.5366 0.8306 4.0659 0.1507 0.2322 1.4227 0.0345 1.1280 0.0695
-#> 365: 92.6411 -5.8908 -2.3367 -4.1060 -0.9502 0.1489 0.1125 3.5405 0.8307 4.0690 0.1507 0.2317 1.4228 0.0344 1.1280 0.0695
-#> 366: 92.6412 -5.8926 -2.3366 -4.1062 -0.9502 0.1484 0.1125 3.5483 0.8307 4.0724 0.1507 0.2311 1.4228 0.0344 1.1280 0.0695
-#> 367: 92.6406 -5.8940 -2.3366 -4.1059 -0.9503 0.1483 0.1124 3.5557 0.8308 4.0738 0.1507 0.2305 1.4228 0.0344 1.1273 0.0695
-#> 368: 92.6402 -5.8940 -2.3365 -4.1059 -0.9504 0.1483 0.1122 3.5538 0.8306 4.0773 0.1507 0.2299 1.4228 0.0344 1.1266 0.0696
-#> 369: 92.6398 -5.8933 -2.3366 -4.1058 -0.9504 0.1482 0.1122 3.5489 0.8303 4.0796 0.1507 0.2295 1.4228 0.0343 1.1261 0.0696
-#> 370: 92.6394 -5.8928 -2.3366 -4.1059 -0.9504 0.1481 0.1123 3.5445 0.8302 4.0819 0.1506 0.2291 1.4229 0.0343 1.1258 0.0696
-#> 371: 92.6390 -5.8930 -2.3369 -4.1062 -0.9503 0.1481 0.1125 3.5446 0.8299 4.0854 0.1506 0.2285 1.4230 0.0343 1.1257 0.0696
-#> 372: 92.6387 -5.8926 -2.3372 -4.1064 -0.9503 0.1482 0.1125 3.5424 0.8298 4.0887 0.1505 0.2281 1.4234 0.0343 1.1262 0.0696
-#> 373: 92.6385 -5.8927 -2.3376 -4.1067 -0.9502 0.1483 0.1126 3.5447 0.8297 4.0919 0.1504 0.2275 1.4236 0.0343 1.1268 0.0696
-#> 374: 92.6382 -5.8932 -2.3380 -4.1064 -0.9502 0.1481 0.1131 3.5490 0.8295 4.0929 0.1503 0.2272 1.4238 0.0343 1.1267 0.0696
-#> 375: 92.6385 -5.8944 -2.3383 -4.1062 -0.9502 0.1481 0.1136 3.5562 0.8292 4.0936 0.1503 0.2269 1.4240 0.0343 1.1274 0.0695
-#> 376: 92.6388 -5.8942 -2.3387 -4.1061 -0.9502 0.1481 0.1141 3.5575 0.8295 4.0942 0.1502 0.2267 1.4236 0.0343 1.1272 0.0695
-#> 377: 92.6389 -5.8942 -2.3392 -4.1060 -0.9502 0.1482 0.1145 3.5579 0.8298 4.0950 0.1501 0.2264 1.4233 0.0344 1.1272 0.0695
-#> 378: 92.6388 -5.8939 -2.3397 -4.1060 -0.9502 0.1481 0.1150 3.5558 0.8298 4.0959 0.1500 0.2261 1.4232 0.0344 1.1271 0.0695
-#> 379: 92.6388 -5.8934 -2.3399 -4.1062 -0.9500 0.1483 0.1153 3.5521 0.8294 4.0980 0.1500 0.2257 1.4236 0.0344 1.1279 0.0694
-#> 380: 92.6390 -5.8920 -2.3402 -4.1065 -0.9499 0.1484 0.1155 3.5446 0.8292 4.1007 0.1500 0.2254 1.4241 0.0344 1.1285 0.0694
-#> 381: 92.6394 -5.8906 -2.3404 -4.1069 -0.9498 0.1485 0.1157 3.5378 0.8290 4.1040 0.1500 0.2250 1.4249 0.0343 1.1296 0.0694
-#> 382: 92.6403 -5.8893 -2.3406 -4.1085 -0.9498 0.1487 0.1157 3.5319 0.8289 4.1195 0.1500 0.2246 1.4250 0.0343 1.1301 0.0694
-#> 383: 92.6402 -5.8882 -2.3408 -4.1096 -0.9499 0.1488 0.1155 3.5269 0.8287 4.1290 0.1500 0.2243 1.4253 0.0343 1.1300 0.0694
-#> 384: 92.6401 -5.8871 -2.3412 -4.1102 -0.9498 0.1490 0.1155 3.5219 0.8285 4.1340 0.1499 0.2241 1.4254 0.0343 1.1297 0.0694
-#> 385: 92.6396 -5.8867 -2.3417 -4.1105 -0.9497 0.1493 0.1155 3.5195 0.8281 4.1364 0.1498 0.2238 1.4252 0.0343 1.1297 0.0695
-#> 386: 92.6393 -5.8863 -2.3423 -4.1116 -0.9496 0.1497 0.1153 3.5190 0.8280 4.1452 0.1497 0.2235 1.4251 0.0343 1.1307 0.0694
-#> 387: 92.6391 -5.8865 -2.3429 -4.1124 -0.9495 0.1498 0.1155 3.5219 0.8280 4.1502 0.1497 0.2234 1.4247 0.0343 1.1301 0.0695
-#> 388: 92.6389 -5.8861 -2.3436 -4.1129 -0.9494 0.1501 0.1158 3.5228 0.8278 4.1540 0.1496 0.2233 1.4243 0.0343 1.1293 0.0695
-#> 389: 92.6384 -5.8849 -2.3442 -4.1132 -0.9491 0.1504 0.1159 3.5195 0.8276 4.1571 0.1496 0.2231 1.4242 0.0343 1.1284 0.0696
-#> 390: 92.6382 -5.8838 -2.3447 -4.1134 -0.9489 0.1506 0.1159 3.5172 0.8276 4.1603 0.1497 0.2230 1.4242 0.0343 1.1273 0.0697
-#> 391: 92.6380 -5.8821 -2.3454 -4.1140 -0.9486 0.1509 0.1159 3.5134 0.8274 4.1661 0.1498 0.2228 1.4238 0.0343 1.1266 0.0697
-#> 392: 92.6374 -5.8800 -2.3460 -4.1140 -0.9485 0.1513 0.1158 3.5069 0.8274 4.1673 0.1499 0.2226 1.4235 0.0343 1.1258 0.0698
-#> 393: 92.6372 -5.8785 -2.3467 -4.1140 -0.9485 0.1514 0.1159 3.5019 0.8275 4.1684 0.1499 0.2223 1.4232 0.0343 1.1258 0.0698
-#> 394: 92.6372 -5.8765 -2.3473 -4.1142 -0.9485 0.1515 0.1161 3.4955 0.8275 4.1710 0.1499 0.2221 1.4228 0.0344 1.1260 0.0697
-#> 395: 92.6371 -5.8761 -2.3476 -4.1145 -0.9485 0.1515 0.1164 3.4940 0.8273 4.1739 0.1498 0.2220 1.4227 0.0344 1.1254 0.0698
-#> 396: 92.6370 -5.8759 -2.3480 -4.1147 -0.9485 0.1516 0.1166 3.4942 0.8269 4.1764 0.1498 0.2217 1.4222 0.0344 1.1252 0.0698
-#> 397: 92.6371 -5.8756 -2.3483 -4.1149 -0.9486 0.1516 0.1167 3.4914 0.8267 4.1796 0.1498 0.2214 1.4219 0.0344 1.1253 0.0697
-#> 398: 92.6371 -5.8756 -2.3486 -4.1155 -0.9486 0.1518 0.1167 3.4909 0.8268 4.1840 0.1498 0.2210 1.4216 0.0344 1.1250 0.0697
-#> 399: 92.6368 -5.8765 -2.3489 -4.1157 -0.9485 0.1519 0.1170 3.4958 0.8266 4.1866 0.1498 0.2205 1.4213 0.0344 1.1245 0.0698
-#> 400: 92.6368 -5.8769 -2.3491 -4.1158 -0.9485 0.1522 0.1174 3.4972 0.8266 4.1888 0.1499 0.2200 1.4209 0.0344 1.1242 0.0698
-#> 401: 92.6366 -5.8768 -2.3493 -4.1161 -0.9484 0.1524 0.1175 3.4964 0.8267 4.1913 0.1499 0.2196 1.4204 0.0344 1.1240 0.0698
-#> 402: 92.6362 -5.8767 -2.3495 -4.1164 -0.9483 0.1525 0.1176 3.4961 0.8267 4.1937 0.1499 0.2192 1.4201 0.0344 1.1240 0.0698
-#> 403: 92.6362 -5.8769 -2.3497 -4.1166 -0.9483 0.1526 0.1178 3.4981 0.8270 4.1960 0.1499 0.2187 1.4197 0.0345 1.1236 0.0698
-#> 404: 92.6359 -5.8772 -2.3499 -4.1166 -0.9483 0.1527 0.1179 3.4997 0.8272 4.1968 0.1499 0.2183 1.4193 0.0345 1.1232 0.0698
-#> 405: 92.6355 -5.8763 -2.3501 -4.1165 -0.9483 0.1527 0.1180 3.4946 0.8273 4.1976 0.1500 0.2180 1.4189 0.0345 1.1230 0.0698
-#> 406: 92.6351 -5.8768 -2.3503 -4.1164 -0.9482 0.1528 0.1184 3.4953 0.8274 4.1979 0.1500 0.2176 1.4184 0.0345 1.1227 0.0698
-#> 407: 92.6346 -5.8772 -2.3505 -4.1165 -0.9481 0.1527 0.1187 3.4965 0.8275 4.1999 0.1500 0.2173 1.4182 0.0344 1.1222 0.0698
-#> 408: 92.6344 -5.8786 -2.3508 -4.1167 -0.9482 0.1528 0.1190 3.5025 0.8276 4.2020 0.1500 0.2171 1.4178 0.0344 1.1215 0.0699
-#> 409: 92.6342 -5.8806 -2.3511 -4.1168 -0.9484 0.1529 0.1193 3.5134 0.8277 4.2037 0.1500 0.2167 1.4176 0.0344 1.1212 0.0699
-#> 410: 92.6341 -5.8826 -2.3514 -4.1170 -0.9486 0.1531 0.1193 3.5229 0.8279 4.2061 0.1500 0.2163 1.4175 0.0344 1.1212 0.0699
-#> 411: 92.6339 -5.8840 -2.3517 -4.1172 -0.9488 0.1532 0.1192 3.5280 0.8280 4.2087 0.1499 0.2159 1.4175 0.0345 1.1208 0.0699
-#> 412: 92.6338 -5.8850 -2.3520 -4.1175 -0.9489 0.1534 0.1193 3.5311 0.8280 4.2121 0.1497 0.2155 1.4177 0.0345 1.1204 0.0699
-#> 413: 92.6343 -5.8859 -2.3523 -4.1177 -0.9491 0.1536 0.1191 3.5337 0.8282 4.2156 0.1497 0.2151 1.4176 0.0345 1.1198 0.0699
-#> 414: 92.6350 -5.8861 -2.3526 -4.1184 -0.9491 0.1540 0.1191 3.5350 0.8283 4.2209 0.1496 0.2147 1.4177 0.0345 1.1196 0.0699
-#> 415: 92.6354 -5.8866 -2.3528 -4.1191 -0.9492 0.1543 0.1191 3.5373 0.8284 4.2258 0.1496 0.2142 1.4179 0.0345 1.1191 0.0699
-#> 416: 92.6360 -5.8873 -2.3531 -4.1201 -0.9493 0.1548 0.1193 3.5431 0.8286 4.2328 0.1495 0.2137 1.4178 0.0345 1.1187 0.0699
-#> 417: 92.6361 -5.8878 -2.3533 -4.1213 -0.9494 0.1551 0.1192 3.5465 0.8288 4.2415 0.1494 0.2131 1.4182 0.0345 1.1189 0.0699
-#> 418: 92.6366 -5.8883 -2.3535 -4.1221 -0.9495 0.1555 0.1194 3.5499 0.8291 4.2477 0.1493 0.2127 1.4180 0.0345 1.1184 0.0699
-#> 419: 92.6367 -5.8885 -2.3536 -4.1236 -0.9495 0.1560 0.1195 3.5517 0.8292 4.2588 0.1492 0.2123 1.4179 0.0345 1.1180 0.0700
-#> 420: 92.6371 -5.8874 -2.3536 -4.1249 -0.9495 0.1564 0.1197 3.5474 0.8293 4.2666 0.1491 0.2118 1.4181 0.0345 1.1182 0.0700
-#> 421: 92.6374 -5.8860 -2.3537 -4.1263 -0.9494 0.1569 0.1197 3.5416 0.8292 4.2759 0.1492 0.2114 1.4184 0.0345 1.1188 0.0699
-#> 422: 92.6377 -5.8850 -2.3538 -4.1279 -0.9493 0.1572 0.1197 3.5365 0.8292 4.2865 0.1491 0.2110 1.4185 0.0345 1.1188 0.0700
-#> 423: 92.6380 -5.8844 -2.3540 -4.1299 -0.9494 0.1576 0.1196 3.5323 0.8290 4.2999 0.1491 0.2106 1.4186 0.0345 1.1192 0.0699
-#> 424: 92.6382 -5.8842 -2.3541 -4.1312 -0.9495 0.1581 0.1198 3.5309 0.8290 4.3092 0.1491 0.2103 1.4184 0.0345 1.1197 0.0699
-#> 425: 92.6382 -5.8838 -2.3543 -4.1320 -0.9495 0.1584 0.1197 3.5281 0.8289 4.3140 0.1491 0.2099 1.4185 0.0346 1.1196 0.0699
-#> 426: 92.6380 -5.8829 -2.3545 -4.1327 -0.9494 0.1587 0.1196 3.5234 0.8293 4.3183 0.1491 0.2096 1.4182 0.0346 1.1194 0.0699
-#> 427: 92.6375 -5.8823 -2.3548 -4.1335 -0.9494 0.1589 0.1197 3.5189 0.8295 4.3233 0.1492 0.2092 1.4180 0.0346 1.1196 0.0699
-#> 428: 92.6370 -5.8813 -2.3552 -4.1343 -0.9494 0.1592 0.1199 3.5140 0.8295 4.3286 0.1491 0.2088 1.4182 0.0346 1.1198 0.0699
-#> 429: 92.6368 -5.8802 -2.3556 -4.1356 -0.9495 0.1597 0.1202 3.5093 0.8296 4.3372 0.1491 0.2086 1.4182 0.0346 1.1208 0.0699
-#> 430: 92.6370 -5.8794 -2.3560 -4.1366 -0.9496 0.1602 0.1201 3.5058 0.8297 4.3439 0.1492 0.2084 1.4183 0.0346 1.1216 0.0698
-#> 431: 92.6371 -5.8792 -2.3564 -4.1372 -0.9497 0.1606 0.1201 3.5029 0.8298 4.3473 0.1493 0.2082 1.4182 0.0346 1.1215 0.0698
-#> 432: 92.6371 -5.8793 -2.3567 -4.1377 -0.9499 0.1609 0.1201 3.5008 0.8297 4.3499 0.1494 0.2080 1.4180 0.0346 1.1218 0.0698
-#> 433: 92.6370 -5.8799 -2.3570 -4.1387 -0.9501 0.1612 0.1201 3.5014 0.8298 4.3560 0.1495 0.2078 1.4180 0.0346 1.1218 0.0699
-#> 434: 92.6371 -5.8790 -2.3573 -4.1398 -0.9501 0.1615 0.1200 3.4982 0.8300 4.3624 0.1496 0.2076 1.4179 0.0346 1.1213 0.0699
-#> 435: 92.6368 -5.8789 -2.3576 -4.1409 -0.9501 0.1619 0.1199 3.4979 0.8302 4.3697 0.1496 0.2074 1.4176 0.0346 1.1205 0.0699
-#> 436: 92.6365 -5.8792 -2.3579 -4.1424 -0.9500 0.1623 0.1197 3.4987 0.8304 4.3798 0.1497 0.2073 1.4173 0.0346 1.1198 0.0699
-#> 437: 92.6364 -5.8798 -2.3582 -4.1439 -0.9500 0.1627 0.1195 3.5017 0.8307 4.3905 0.1497 0.2071 1.4172 0.0346 1.1191 0.0700
-#> 438: 92.6362 -5.8803 -2.3585 -4.1450 -0.9499 0.1631 0.1193 3.5053 0.8309 4.3973 0.1497 0.2070 1.4172 0.0346 1.1186 0.0700
-#> 439: 92.6361 -5.8811 -2.3588 -4.1463 -0.9498 0.1634 0.1190 3.5101 0.8312 4.4052 0.1496 0.2069 1.4172 0.0346 1.1188 0.0700
-#> 440: 92.6360 -5.8816 -2.3591 -4.1477 -0.9498 0.1637 0.1187 3.5127 0.8315 4.4145 0.1495 0.2068 1.4172 0.0346 1.1189 0.0700
-#> 441: 92.6357 -5.8816 -2.3594 -4.1492 -0.9499 0.1640 0.1185 3.5136 0.8319 4.4252 0.1494 0.2069 1.4175 0.0346 1.1191 0.0700
-#> 442: 92.6356 -5.8819 -2.3596 -4.1501 -0.9500 0.1642 0.1181 3.5151 0.8323 4.4310 0.1494 0.2070 1.4176 0.0346 1.1193 0.0700
-#> 443: 92.6356 -5.8825 -2.3598 -4.1512 -0.9501 0.1643 0.1180 3.5178 0.8324 4.4379 0.1493 0.2071 1.4179 0.0346 1.1196 0.0700
-#> 444: 92.6352 -5.8827 -2.3602 -4.1525 -0.9502 0.1644 0.1180 3.5169 0.8327 4.4458 0.1493 0.2073 1.4178 0.0346 1.1198 0.0700
-#> 445: 92.6348 -5.8828 -2.3605 -4.1534 -0.9502 0.1643 0.1180 3.5178 0.8329 4.4505 0.1493 0.2074 1.4178 0.0346 1.1202 0.0700
-#> 446: 92.6342 -5.8830 -2.3609 -4.1541 -0.9503 0.1643 0.1183 3.5182 0.8331 4.4539 0.1494 0.2077 1.4176 0.0346 1.1199 0.0700
-#> 447: 92.6334 -5.8832 -2.3613 -4.1548 -0.9503 0.1643 0.1188 3.5188 0.8333 4.4571 0.1494 0.2079 1.4172 0.0346 1.1198 0.0700
-#> 448: 92.6331 -5.8833 -2.3616 -4.1557 -0.9503 0.1643 0.1190 3.5190 0.8335 4.4613 0.1494 0.2080 1.4170 0.0346 1.1198 0.0700
-#> 449: 92.6327 -5.8835 -2.3619 -4.1563 -0.9504 0.1641 0.1192 3.5191 0.8335 4.4636 0.1493 0.2081 1.4172 0.0346 1.1196 0.0700
-#> 450: 92.6322 -5.8831 -2.3620 -4.1566 -0.9505 0.1639 0.1194 3.5152 0.8340 4.4647 0.1492 0.2083 1.4172 0.0346 1.1189 0.0700
-#> 451: 92.6315 -5.8835 -2.3622 -4.1569 -0.9505 0.1635 0.1194 3.5192 0.8343 4.4648 0.1492 0.2084 1.4169 0.0346 1.1187 0.0700
-#> 452: 92.6312 -5.8834 -2.3625 -4.1572 -0.9506 0.1632 0.1193 3.5173 0.8345 4.4654 0.1492 0.2086 1.4166 0.0346 1.1183 0.0700
-#> 453: 92.6309 -5.8838 -2.3628 -4.1574 -0.9506 0.1629 0.1193 3.5175 0.8348 4.4660 0.1493 0.2087 1.4166 0.0346 1.1180 0.0700
-#> 454: 92.6307 -5.8832 -2.3629 -4.1574 -0.9507 0.1625 0.1193 3.5128 0.8354 4.4658 0.1493 0.2087 1.4164 0.0346 1.1176 0.0700
-#> 455: 92.6305 -5.8821 -2.3632 -4.1579 -0.9508 0.1624 0.1192 3.5071 0.8360 4.4678 0.1494 0.2089 1.4164 0.0346 1.1171 0.0701
-#> 456: 92.6307 -5.8811 -2.3634 -4.1589 -0.9509 0.1623 0.1190 3.5014 0.8364 4.4730 0.1494 0.2088 1.4168 0.0346 1.1168 0.0701
-#> 457: 92.6307 -5.8808 -2.3636 -4.1597 -0.9509 0.1621 0.1188 3.4980 0.8368 4.4772 0.1494 0.2089 1.4168 0.0347 1.1166 0.0701
-#> 458: 92.6308 -5.8813 -2.3638 -4.1607 -0.9510 0.1621 0.1185 3.4994 0.8369 4.4823 0.1494 0.2088 1.4168 0.0347 1.1161 0.0701
-#> 459: 92.6308 -5.8819 -2.3639 -4.1615 -0.9511 0.1620 0.1184 3.5008 0.8371 4.4861 0.1494 0.2086 1.4167 0.0347 1.1155 0.0701
-#> 460: 92.6309 -5.8824 -2.3642 -4.1621 -0.9511 0.1621 0.1182 3.5024 0.8374 4.4886 0.1493 0.2085 1.4164 0.0347 1.1148 0.0702
-#> 461: 92.6309 -5.8821 -2.3647 -4.1631 -0.9511 0.1621 0.1181 3.5000 0.8378 4.4937 0.1493 0.2084 1.4160 0.0347 1.1141 0.0702
-#> 462: 92.6309 -5.8825 -2.3651 -4.1638 -0.9511 0.1623 0.1180 3.5006 0.8381 4.4975 0.1492 0.2082 1.4156 0.0348 1.1133 0.0702
-#> 463: 92.6307 -5.8824 -2.3656 -4.1654 -0.9510 0.1624 0.1179 3.5000 0.8382 4.5074 0.1491 0.2081 1.4154 0.0348 1.1124 0.0702
-#> 464: 92.6305 -5.8825 -2.3660 -4.1668 -0.9510 0.1625 0.1178 3.5001 0.8384 4.5171 0.1491 0.2080 1.4149 0.0348 1.1115 0.0703
-#> 465: 92.6302 -5.8828 -2.3664 -4.1681 -0.9511 0.1626 0.1179 3.5012 0.8386 4.5247 0.1490 0.2079 1.4151 0.0348 1.1107 0.0703
-#> 466: 92.6300 -5.8827 -2.3668 -4.1697 -0.9511 0.1626 0.1179 3.5005 0.8390 4.5370 0.1490 0.2079 1.4148 0.0349 1.1098 0.0704
-#> 467: 92.6301 -5.8828 -2.3671 -4.1721 -0.9512 0.1628 0.1180 3.4991 0.8393 4.5562 0.1490 0.2078 1.4148 0.0349 1.1092 0.0704
-#> 468: 92.6303 -5.8833 -2.3675 -4.1745 -0.9513 0.1630 0.1181 3.4996 0.8397 4.5756 0.1489 0.2078 1.4148 0.0349 1.1086 0.0704
-#> 469: 92.6304 -5.8835 -2.3680 -4.1759 -0.9513 0.1630 0.1181 3.4991 0.8401 4.5829 0.1490 0.2080 1.4145 0.0349 1.1082 0.0704
-#> 470: 92.6304 -5.8839 -2.3685 -4.1772 -0.9512 0.1630 0.1183 3.4993 0.8405 4.5904 0.1490 0.2081 1.4142 0.0349 1.1079 0.0704
-#> 471: 92.6304 -5.8838 -2.3690 -4.1786 -0.9511 0.1631 0.1182 3.4992 0.8408 4.5981 0.1489 0.2082 1.4143 0.0350 1.1075 0.0704
-#> 472: 92.6301 -5.8839 -2.3695 -4.1800 -0.9511 0.1631 0.1182 3.5005 0.8413 4.6063 0.1488 0.2083 1.4143 0.0350 1.1072 0.0704
-#> 473: 92.6296 -5.8841 -2.3699 -4.1811 -0.9510 0.1630 0.1182 3.5019 0.8417 4.6119 0.1487 0.2085 1.4142 0.0350 1.1065 0.0704
-#> 474: 92.6293 -5.8843 -2.3704 -4.1823 -0.9510 0.1629 0.1184 3.5038 0.8422 4.6182 0.1487 0.2087 1.4145 0.0350 1.1060 0.0704
-#> 475: 92.6293 -5.8851 -2.3709 -4.1839 -0.9509 0.1628 0.1185 3.5084 0.8426 4.6277 0.1487 0.2089 1.4142 0.0351 1.1057 0.0704
-#> 476: 92.6293 -5.8854 -2.3713 -4.1847 -0.9509 0.1627 0.1185 3.5137 0.8430 4.6318 0.1486 0.2092 1.4139 0.0351 1.1057 0.0704
-#> 477: 92.6292 -5.8858 -2.3718 -4.1859 -0.9508 0.1627 0.1183 3.5201 0.8430 4.6397 0.1485 0.2095 1.4139 0.0351 1.1060 0.0704
-#> 478: 92.6291 -5.8871 -2.3722 -4.1867 -0.9508 0.1625 0.1181 3.5291 0.8432 4.6449 0.1483 0.2098 1.4140 0.0351 1.1058 0.0704
-#> 479: 92.6293 -5.8891 -2.3726 -4.1873 -0.9509 0.1623 0.1178 3.5422 0.8435 4.6486 0.1482 0.2100 1.4139 0.0352 1.1056 0.0704
-#> 480: 92.6294 -5.8910 -2.3730 -4.1881 -0.9509 0.1622 0.1175 3.5568 0.8437 4.6535 0.1482 0.2102 1.4140 0.0352 1.1053 0.0705
-#> 481: 92.6297 -5.8919 -2.3734 -4.1888 -0.9509 0.1621 0.1174 3.5650 0.8440 4.6572 0.1482 0.2104 1.4138 0.0353 1.1051 0.0705
-#> 482: 92.6293 -5.8929 -2.3737 -4.1894 -0.9509 0.1619 0.1173 3.5745 0.8444 4.6620 0.1482 0.2107 1.4134 0.0353 1.1047 0.0705
-#> 483: 92.6284 -5.8939 -2.3741 -4.1901 -0.9508 0.1616 0.1176 3.5832 0.8446 4.6672 0.1482 0.2109 1.4131 0.0353 1.1044 0.0705
-#> 484: 92.6276 -5.8943 -2.3744 -4.1904 -0.9507 0.1615 0.1179 3.5877 0.8447 4.6692 0.1483 0.2113 1.4128 0.0353 1.1041 0.0705
-#> 485: 92.6266 -5.8947 -2.3746 -4.1912 -0.9507 0.1616 0.1182 3.5903 0.8448 4.6751 0.1483 0.2115 1.4126 0.0354 1.1042 0.0705
-#> 486: 92.6258 -5.8952 -2.3749 -4.1918 -0.9508 0.1615 0.1185 3.5929 0.8450 4.6799 0.1485 0.2115 1.4125 0.0354 1.1045 0.0704
-#> 487: 92.6250 -5.8956 -2.3750 -4.1923 -0.9509 0.1614 0.1189 3.5922 0.8452 4.6835 0.1486 0.2115 1.4122 0.0354 1.1050 0.0704
-#> 488: 92.6242 -5.8956 -2.3752 -4.1927 -0.9510 0.1613 0.1191 3.5898 0.8453 4.6866 0.1487 0.2115 1.4119 0.0354 1.1051 0.0704
-#> 489: 92.6238 -5.8954 -2.3753 -4.1932 -0.9511 0.1611 0.1190 3.5871 0.8454 4.6905 0.1487 0.2115 1.4118 0.0354 1.1057 0.0704
-#> 490: 92.6237 -5.8951 -2.3754 -4.1936 -0.9511 0.1611 0.1188 3.5839 0.8454 4.6945 0.1487 0.2114 1.4117 0.0354 1.1064 0.0703
-#> 491: 92.6235 -5.8942 -2.3755 -4.1941 -0.9511 0.1610 0.1187 3.5790 0.8455 4.6981 0.1488 0.2115 1.4118 0.0354 1.1068 0.0703
-#> 492: 92.6234 -5.8938 -2.3755 -4.1952 -0.9512 0.1609 0.1186 3.5760 0.8454 4.7074 0.1488 0.2115 1.4119 0.0354 1.1074 0.0703
-#> 493: 92.6236 -5.8938 -2.3755 -4.1958 -0.9512 0.1608 0.1186 3.5747 0.8454 4.7121 0.1488 0.2114 1.4120 0.0354 1.1078 0.0702
-#> 494: 92.6239 -5.8945 -2.3756 -4.1964 -0.9513 0.1607 0.1186 3.5772 0.8455 4.7167 0.1488 0.2115 1.4120 0.0354 1.1082 0.0702
-#> 495: 92.6242 -5.8950 -2.3756 -4.1971 -0.9514 0.1605 0.1187 3.5798 0.8454 4.7227 0.1489 0.2117 1.4122 0.0354 1.1084 0.0702
-#> 496: 92.6242 -5.8962 -2.3757 -4.1978 -0.9514 0.1603 0.1189 3.5870 0.8455 4.7283 0.1489 0.2119 1.4121 0.0354 1.1090 0.0702
-#> 497: 92.6241 -5.8972 -2.3757 -4.1981 -0.9514 0.1602 0.1191 3.5934 0.8454 4.7298 0.1488 0.2120 1.4123 0.0354 1.1096 0.0701
-#> 498: 92.6244 -5.8973 -2.3758 -4.1981 -0.9514 0.1601 0.1190 3.5947 0.8454 4.7296 0.1488 0.2121 1.4123 0.0354 1.1101 0.0701
-#> 499: 92.6244 -5.8968 -2.3759 -4.1980 -0.9514 0.1600 0.1188 3.5935 0.8453 4.7290 0.1488 0.2124 1.4123 0.0354 1.1108 0.0701
-#> 500: 92.6245 -5.8959 -2.3759 -4.1978 -0.9513 0.1597 0.1188 3.5912 0.8452 4.7282 0.1488 0.2126 1.4123 0.0354 1.1111 0.0701
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>
#> 1: 90.7519 -4.8586 -1.7674 -3.5599 -2.0059 0.5800 4.8899 1.4250 1.1400 2.6923 0.4845 0.4370 10.2815 0.0004 9.0437 0.4047
+#> 2: 9.0763e+01 -5.2004e+00 -1.9605e+00 -4.2009e+00 -1.8767e+00 2.0341e-01 4.6454e+00 1.3537e+00 1.0830e+00 2.7771e+00 4.6027e-01 5.1181e-01 6.3469e+00 4.0033e-04 6.8216e+00 9.0448e-05
+#> 3: 9.0656e+01 -5.4820e+00 -2.0937e+00 -4.0962e+00 -1.5381e+00 -1.7136e-02 4.4131e+00 1.2861e+00 1.0288e+00 3.5620e+00 4.3726e-01 6.1217e-01 4.8763e+00 4.1436e-05 5.4967e+00 1.0148e-05
+#> 4: 9.0543e+01 -5.7744e+00 -2.1074e+00 -4.0393e+00 -1.3603e+00 -2.3531e-01 5.0162e+00 1.2218e+00 1.0041e+00 3.3839e+00 4.1540e-01 5.8157e-01 4.1029e+00 2.1466e-04 4.2869e+00 1.9419e-06
+#> 5: 91.1621 -6.0534 -2.0430 -4.0508 -1.2523 -0.2043 6.1015 1.1715 1.1998 3.2147 0.3946 0.5525 3.5979 0.0187 3.8221 0.0271
+#> 6: 91.1179 -5.9892 -2.0082 -4.1363 -1.1428 -0.1930 5.7964 1.1960 1.2360 3.4525 0.3749 0.5293 3.3091 0.0209 3.6230 0.0284
+#> 7: 91.6680 -5.9609 -2.0492 -4.1163 -1.0919 -0.1505 5.6134 1.6750 1.3055 3.2799 0.3631 0.5028 3.2412 0.0254 3.5108 0.0371
+#> 8: 91.6903 -5.9346 -2.0630 -4.0790 -1.1130 -0.0963 5.3327 2.2525 1.3524 3.1159 0.3449 0.4777 2.6165 0.0445 2.8556 0.0576
+#> 9: 92.2564 -5.7600 -2.0460 -4.1144 -1.0635 -0.0594 5.9616 2.1399 1.2848 2.9601 0.3277 0.4538 2.3593 0.0295 2.5704 0.0491
+#> 10: 92.2425 -5.7990 -2.0052 -4.0409 -1.0387 -0.1141 6.9547 2.1239 1.2205 2.8121 0.3113 0.4311 2.3237 0.0323 2.4227 0.0421
+#> 11: 92.4404 -5.6829 -2.0866 -4.0010 -1.0214 -0.0587 6.6790 2.0177 1.1595 2.6715 0.2957 0.4096 1.9963 0.0407 2.2478 0.0501
+#> 12: 92.0713 -5.8051 -2.1699 -4.0539 -0.9807 0.0174 6.7885 2.1380 1.1811 2.6017 0.2810 0.3891 1.8480 0.0502 2.0516 0.0522
+#> 13: 91.7214 -5.6954 -2.1579 -4.0944 -0.9935 -0.0195 6.4491 2.0311 1.1221 2.4716 0.2669 0.3696 1.8299 0.0531 1.9271 0.0520
+#> 14: 91.1978 -5.6733 -2.1988 -4.0794 -0.9387 0.0091 6.1267 1.9295 1.1589 2.3480 0.2536 0.3511 1.6357 0.0470 1.8899 0.0639
+#> 15: 91.3746 -5.5864 -2.1484 -4.1356 -0.9126 0.0045 5.8203 1.8330 1.2078 2.3265 0.2409 0.3336 1.6218 0.0428 1.6558 0.0725
+#> 16: 91.5646 -5.4931 -2.1474 -4.1242 -0.9148 0.0179 5.5293 1.7414 1.1474 2.2733 0.2288 0.3169 1.6467 0.0377 1.6977 0.0600
+#> 17: 91.4767 -5.5885 -2.1424 -4.1386 -0.9308 0.0602 5.2528 1.9428 1.2141 2.1762 0.2174 0.3343 1.4916 0.0424 1.4326 0.0717
+#> 18: 90.9989 -5.6364 -2.1601 -4.1606 -0.9676 0.0694 4.9902 1.8457 1.2521 2.2899 0.2065 0.3279 1.4504 0.0471 1.4267 0.0700
+#> 19: 91.4050 -5.7347 -2.0985 -4.1476 -0.9656 0.0668 4.7407 2.3263 1.4064 2.2061 0.1962 0.3296 1.3679 0.0485 1.2735 0.0844
+#> 20: 91.2707 -5.7623 -2.1155 -4.1538 -0.9601 0.0425 4.5037 2.6509 1.3408 2.1958 0.1864 0.3576 1.3736 0.0452 1.3454 0.0743
+#> 21: 91.6878 -5.8143 -2.1261 -4.1649 -0.9325 0.0333 4.7695 2.8996 1.3244 2.1300 0.1771 0.3509 1.4793 0.0508 1.0333 0.0839
+#> 22: 91.5363 -5.9047 -2.1358 -4.1655 -0.9207 0.0339 4.5310 3.4408 1.3022 2.1829 0.1682 0.3378 1.4260 0.0488 0.9436 0.0877
+#> 23: 91.9969 -5.9565 -2.1378 -4.1609 -0.9243 0.0701 4.3045 3.7239 1.3446 2.2424 0.1598 0.3209 1.4182 0.0412 0.9205 0.0873
+#> 24: 92.2835 -5.9272 -2.0883 -4.1651 -0.9248 0.0834 4.0892 3.7780 1.2773 2.2187 0.1518 0.3049 1.4749 0.0427 0.9837 0.0802
+#> 25: 92.3389 -6.1292 -2.1033 -4.2473 -0.9069 0.0593 3.8848 4.7059 1.2740 2.4323 0.1442 0.2896 1.3656 0.0493 0.9299 0.0798
+#> 26: 91.9840 -5.9821 -2.1124 -4.2150 -0.9100 0.1076 3.6905 4.4706 1.2103 2.4699 0.1458 0.2751 1.3200 0.0504 0.8256 0.0912
+#> 27: 92.4671 -5.8765 -2.0910 -4.2169 -0.9356 0.0483 3.5060 4.2471 1.2302 2.4791 0.1385 0.2614 1.4252 0.0520 0.8191 0.0836
+#> 28: 92.4130 -5.9480 -2.0870 -4.2191 -0.9338 0.0866 3.3859 4.1337 1.2210 2.4685 0.1412 0.2557 1.3860 0.0484 0.9189 0.0770
+#> 29: 92.3064 -5.7845 -2.0759 -4.2321 -0.9270 0.0855 4.2691 3.9271 1.3369 2.5457 0.1341 0.2922 1.3848 0.0513 0.9658 0.0785
+#> 30: 92.2109 -5.9347 -2.0725 -4.2042 -0.9074 0.0481 5.5659 3.9234 1.2701 2.4184 0.1370 0.2776 1.2925 0.0560 0.9058 0.0806
+#> 31: 91.8912 -5.7466 -2.0912 -4.1504 -0.9087 0.0443 5.2876 3.7272 1.2690 2.2975 0.1301 0.2637 1.3348 0.0517 0.8672 0.0840
+#> 32: 92.3866 -5.8560 -2.0979 -4.1547 -0.9044 0.0335 5.0232 3.5408 1.2761 2.3185 0.1307 0.2505 1.3558 0.0487 0.9422 0.0791
+#> 33: 92.4555 -5.6989 -2.0956 -4.1479 -0.9038 0.0447 4.7720 3.3638 1.3253 2.2962 0.1242 0.2380 1.4321 0.0432 0.8961 0.0799
+#> 34: 92.6307 -5.8831 -2.0769 -4.1319 -0.8946 0.0430 4.5334 3.7151 1.2785 2.2638 0.1201 0.2261 1.4076 0.0457 0.8269 0.0813
+#> 35: 92.5659 -5.9100 -2.0748 -4.1482 -0.9079 0.0563 4.6634 3.7452 1.3141 2.3378 0.1168 0.2148 1.3571 0.0451 0.8317 0.0831
+#> 36: 92.5738 -5.8574 -2.0981 -4.1214 -0.8963 0.0302 5.3272 3.7371 1.3359 2.2776 0.1331 0.2041 1.3308 0.0480 0.8953 0.0791
+#> 37: 92.1615 -5.7137 -2.0922 -4.1178 -0.9035 0.0455 5.4894 3.5503 1.2691 2.2508 0.1473 0.1939 1.3692 0.0495 0.9358 0.0800
+#> 38: 92.4421 -5.6978 -2.0905 -4.1275 -0.9052 0.0108 5.4295 3.3728 1.2057 2.2119 0.1432 0.1842 1.3421 0.0549 0.8932 0.0781
+#> 39: 92.3995 -5.6121 -2.0804 -4.1275 -0.8903 0.0270 5.1580 3.2041 1.1454 2.2119 0.1360 0.1978 1.3353 0.0524 0.9062 0.0775
+#> 40: 92.5616 -5.7907 -2.1099 -4.1127 -0.9074 0.0501 4.9001 3.0439 1.1582 2.1723 0.1387 0.1879 1.2981 0.0510 0.9517 0.0797
+#> 41: 92.2655 -5.6532 -2.0631 -4.1437 -0.9128 0.0346 4.6551 2.8917 1.1202 2.1498 0.1403 0.1785 1.4500 0.0461 0.7394 0.0903
+#> 42: 92.3218 -5.4916 -2.1072 -4.1312 -0.9310 0.0360 4.4224 2.7471 1.1648 2.1428 0.1332 0.1695 1.4034 0.0508 0.8131 0.0854
+#> 43: 92.6165 -5.5145 -2.0838 -4.1239 -0.9215 0.0347 4.2012 2.6098 1.1892 2.1202 0.1463 0.1611 1.3416 0.0507 0.8213 0.0847
+#> 44: 92.5385 -5.5590 -2.0872 -4.1376 -0.9210 0.0672 3.9912 2.4793 1.1416 2.2253 0.1450 0.1530 1.4008 0.0352 0.8639 0.0847
+#> 45: 92.2152 -5.6170 -2.1014 -4.1657 -0.9331 0.0781 3.7916 2.4382 1.1250 2.2378 0.1516 0.1556 1.4612 0.0329 1.0091 0.0820
+#> 46: 91.8943 -5.6650 -2.1329 -4.1649 -0.9241 0.1060 3.6020 2.6448 1.0705 2.3112 0.1441 0.1549 1.5047 0.0384 1.0179 0.0805
+#> 47: 91.8153 -5.5910 -2.1514 -4.1919 -0.9169 0.0885 3.4219 2.5125 1.0386 2.3140 0.1506 0.1620 1.4759 0.0375 1.1021 0.0740
+#> 48: 91.6295 -5.5438 -2.1516 -4.1570 -0.8742 0.0851 3.2508 2.3869 1.0816 2.1983 0.1630 0.1786 1.4024 0.0405 1.1135 0.0732
+#> 49: 91.4363 -5.5847 -2.1732 -4.1794 -0.8634 0.0948 3.0883 2.4829 1.0865 2.2378 0.1549 0.1697 1.4314 0.0434 1.0529 0.0742
+#> 50: 91.3634 -5.5794 -2.1613 -4.1507 -0.8849 0.0862 2.9339 2.6404 1.0829 2.2519 0.1493 0.1612 1.3704 0.0446 1.0081 0.0736
+#> 51: 91.2150 -5.5503 -2.1675 -4.1432 -0.8749 0.1178 2.7872 2.7368 1.0605 2.2261 0.1418 0.1532 1.4312 0.0418 1.0380 0.0781
+#> 52: 91.4343 -5.6336 -2.2138 -4.1552 -0.8867 0.1391 2.6677 2.7022 1.0857 2.2588 0.1493 0.1455 1.3220 0.0469 0.9272 0.0761
+#> 53: 91.3310 -5.5185 -2.2340 -4.1430 -0.8855 0.1545 2.9130 2.5670 1.0720 2.3074 0.1532 0.1385 1.3224 0.0503 0.9688 0.0723
+#> 54: 91.4342 -5.5008 -2.2086 -4.1777 -0.8720 0.1688 2.8202 2.4387 1.0624 2.4253 0.1631 0.1315 1.3186 0.0429 0.9425 0.0723
+#> 55: 91.4983 -5.5944 -2.1709 -4.1211 -0.8638 0.1168 3.4789 2.5154 1.0549 2.3041 0.1557 0.1279 1.3800 0.0423 0.9620 0.0727
+#> 56: 91.5954 -5.5317 -2.1881 -4.1263 -0.8627 0.1366 4.1396 2.3896 1.0732 2.2684 0.1562 0.1221 1.3285 0.0431 1.0156 0.0708
+#> 57: 91.6591 -5.3839 -2.2082 -4.1122 -0.8929 0.1457 4.5073 2.2701 1.0672 2.3639 0.1539 0.1160 1.4074 0.0478 0.9796 0.0722
+#> 58: 91.7434 -5.3597 -2.2068 -4.1214 -0.8912 0.1437 4.2819 2.1566 1.0605 2.4496 0.1667 0.1109 1.4274 0.0450 1.0782 0.0676
+#> 59: 91.6597 -5.4672 -2.1918 -4.1412 -0.9021 0.1657 4.0678 2.0488 1.1306 2.5245 0.1888 0.1054 1.4745 0.0391 1.1492 0.0670
+#> 60: 91.7565 -5.4513 -2.2051 -4.1618 -0.9013 0.1554 3.8644 1.9464 1.1728 2.6191 0.1793 0.1001 1.4135 0.0402 1.1572 0.0665
+#> 61: 91.9484 -5.5390 -2.1973 -4.1611 -0.9011 0.1318 3.6712 1.8963 1.1460 2.6242 0.1704 0.0951 1.3855 0.0481 1.1109 0.0634
+#> 62: 92.1661 -5.4985 -2.1729 -4.1352 -0.8887 0.1327 4.3155 1.8588 1.1087 2.5551 0.1633 0.0995 1.3847 0.0444 1.0736 0.0656
+#> 63: 92.1727 -5.4086 -2.1610 -4.1488 -0.8998 0.1451 4.6019 1.7659 1.1413 2.6020 0.1718 0.1152 1.4299 0.0404 1.2202 0.0603
+#> 64: 92.4331 -5.5220 -2.1121 -4.1300 -0.9428 0.1211 5.0354 1.8121 1.0982 2.6157 0.1775 0.1209 1.4168 0.0348 1.2148 0.0625
+#> 65: 92.1871 -5.6089 -2.1258 -4.1412 -0.9127 0.1399 4.7836 2.1060 1.1568 2.5971 0.1757 0.1148 1.4000 0.0336 1.0305 0.0707
+#> 66: 92.1419 -5.7752 -2.1344 -4.1493 -0.9237 0.1494 4.5444 2.7076 1.1563 2.6439 0.1740 0.1091 1.4238 0.0341 1.0285 0.0688
+#> 67: 92.1187 -5.5967 -2.1430 -4.1460 -0.9074 0.1245 4.3172 2.5722 1.2052 2.6139 0.1868 0.1104 1.4100 0.0381 1.0508 0.0703
+#> 68: 92.1123 -5.6882 -2.1481 -4.1269 -0.9083 0.1206 4.1014 2.5548 1.2021 2.4832 0.1781 0.1462 1.3099 0.0417 1.0099 0.0713
+#> 69: 92.2511 -5.6923 -2.1456 -4.1315 -0.9077 0.1421 4.3551 2.6261 1.1850 2.3591 0.1692 0.1389 1.3546 0.0416 0.9516 0.0762
+#> 70: 92.0291 -5.7376 -2.1689 -4.1364 -0.8908 0.1407 4.1373 3.0520 1.1595 2.2495 0.1608 0.1465 1.3226 0.0436 0.9904 0.0711
+#> 71: 91.7690 -5.7223 -2.1773 -4.1986 -0.9036 0.1831 3.9304 2.8994 1.1015 2.4335 0.1527 0.1602 1.3135 0.0450 0.9564 0.0722
+#> 72: 91.4802 -5.7302 -2.2079 -4.2000 -0.8990 0.2112 3.7339 3.2965 1.1222 2.4612 0.1451 0.1622 1.3222 0.0426 1.0215 0.0717
+#> 73: 91.1247 -5.7803 -2.1827 -4.2214 -0.8876 0.1385 3.5472 3.2786 1.1612 2.5216 0.1650 0.1541 1.2811 0.0493 1.0076 0.0696
+#> 74: 90.9765 -5.6534 -2.1808 -4.2511 -0.8824 0.1308 3.8553 3.1146 1.1389 2.8140 0.1725 0.1464 1.2895 0.0518 1.0100 0.0707
+#> 75: 90.4805 -5.7293 -2.1481 -4.2613 -0.8704 0.1395 4.1255 2.9589 1.1623 2.7523 0.1713 0.1391 1.3112 0.0483 0.9439 0.0788
+#> 76: 90.3958 -5.7635 -2.1508 -4.2426 -0.8841 0.1402 4.7427 3.0223 1.2187 2.7243 0.1789 0.1321 1.3065 0.0468 0.9303 0.0758
+#> 77: 90.7518 -5.6517 -2.1498 -4.2773 -0.8730 0.1688 5.9340 2.8712 1.1840 2.8530 0.1828 0.1255 1.3553 0.0422 0.9755 0.0696
+#> 78: 91.0443 -5.7462 -2.1351 -4.2601 -0.8848 0.1746 5.6373 2.9912 1.1312 2.7659 0.1887 0.1192 1.3303 0.0410 0.8578 0.0744
+#> 79: 90.9631 -5.7307 -2.1618 -4.2593 -0.8965 0.1944 5.7520 3.1324 1.1206 2.8212 0.1875 0.1340 1.3519 0.0449 0.9006 0.0799
+#> 80: 90.8703 -5.7665 -2.1989 -4.2476 -0.9122 0.1933 5.4644 3.4527 1.1063 2.7920 0.1781 0.1273 1.3014 0.0497 0.9305 0.0792
+#> 81: 90.7781 -5.8702 -2.1789 -4.2821 -0.8828 0.1793 5.1912 3.7553 1.0662 3.0568 0.1807 0.1209 1.3120 0.0472 0.9808 0.0772
+#> 82: 90.8137 -6.1164 -2.2001 -4.3046 -0.8912 0.1916 4.9316 4.9023 1.0714 3.1363 0.1716 0.1149 1.2724 0.0539 1.0644 0.0693
+#> 83: 90.9900 -6.2077 -2.1695 -4.3121 -0.8924 0.1722 6.7123 5.3290 1.1120 3.2733 0.1741 0.1091 1.2822 0.0510 1.0142 0.0715
+#> 84: 90.8158 -6.3282 -2.1595 -4.2907 -0.9096 0.1818 6.3767 5.9725 1.1342 3.2384 0.1763 0.1037 1.2704 0.0420 0.8891 0.0834
+#> 85: 90.5926 -6.2052 -2.1643 -4.2780 -0.9000 0.1579 6.0579 5.6739 1.1472 3.0765 0.1751 0.0985 1.3263 0.0433 0.9484 0.0814
+#> 86: 90.3804 -6.2707 -2.1470 -4.2627 -0.9260 0.1650 5.7550 5.5542 1.1135 2.9227 0.1956 0.0936 1.2747 0.0447 0.9731 0.0780
+#> 87: 90.8425 -6.4455 -2.1135 -4.2273 -0.9294 0.1491 5.4672 6.8599 1.0716 2.7765 0.1858 0.0928 1.3204 0.0427 1.0005 0.0744
+#> 88: 91.2019 -6.2302 -2.1362 -4.1982 -0.9333 0.1615 5.1939 6.5169 1.1221 2.7203 0.1841 0.0928 1.2689 0.0466 0.9914 0.0771
+#> 89: 90.9907 -6.4173 -2.1174 -4.2493 -0.9182 0.1628 4.9342 6.2408 1.1719 2.9614 0.1749 0.1021 1.3580 0.0403 1.0171 0.0775
+#> 90: 91.1666 -6.5154 -2.1219 -4.2011 -0.9210 0.1594 4.6875 7.4895 1.1930 2.8133 0.1745 0.0970 1.2500 0.0432 0.9467 0.0799
+#> 91: 91.0165 -6.5918 -2.1465 -4.2231 -0.9079 0.1382 4.9772 7.3172 1.1706 2.6789 0.1810 0.1032 1.2958 0.0458 1.1223 0.0639
+#> 92: 91.5386 -6.6567 -2.1376 -4.2247 -0.9358 0.1696 5.5955 7.4188 1.1543 2.6339 0.1754 0.0980 1.2894 0.0463 0.9927 0.0764
+#> 93: 92.2552 -6.5096 -2.1645 -4.2340 -0.9393 0.1798 5.3157 7.0479 1.1612 2.6312 0.1718 0.0931 1.3698 0.0431 1.2649 0.0579
+#> 94: 91.7588 -6.4124 -2.1795 -4.2305 -0.9265 0.1842 5.8275 6.6955 1.1988 2.6403 0.1891 0.0884 1.3022 0.0481 1.0741 0.0713
+#> 95: 91.6694 -6.2975 -2.1946 -4.2442 -0.9392 0.2004 5.5361 6.3607 1.1399 2.7164 0.1796 0.1027 1.2519 0.0513 1.0982 0.0724
+#> 96: 91.2252 -6.0124 -2.2316 -4.2701 -0.8946 0.2375 5.2593 6.0427 1.0829 2.7921 0.2024 0.1147 1.3343 0.0426 1.3064 0.0560
+#> 97: 91.0388 -5.9178 -2.2563 -4.2703 -0.9093 0.2304 5.6825 5.7405 1.0890 2.7678 0.2113 0.1090 1.3517 0.0484 1.4160 0.0493
+#> 98: 90.9013 -6.1325 -2.2597 -4.2776 -0.9133 0.2447 5.7546 5.4535 1.1028 2.6806 0.2130 0.1182 1.2983 0.0451 1.2436 0.0584
+#> 99: 91.2086 -6.0047 -2.2719 -4.2972 -0.9136 0.2738 5.4668 5.1808 1.1776 2.7160 0.2132 0.1123 1.3301 0.0431 1.1850 0.0628
+#> 100: 91.3181 -5.9175 -2.2311 -4.3202 -0.8947 0.2844 5.1935 4.9218 1.1187 2.8660 0.2289 0.1471 1.3409 0.0371 0.9566 0.0806
+#> 101: 91.5112 -5.7721 -2.2292 -4.3060 -0.8842 0.3006 6.3617 4.6757 1.0628 2.7227 0.2174 0.1500 1.3269 0.0407 1.2002 0.0592
+#> 102: 91.5205 -5.9982 -2.2162 -4.3041 -0.8813 0.3065 7.7957 4.4419 1.0320 2.7176 0.2290 0.1474 1.3218 0.0392 0.9685 0.0783
+#> 103: 91.2416 -5.7012 -2.2204 -4.3198 -0.8610 0.3180 7.4059 4.2198 1.0242 2.5817 0.2175 0.1714 1.3003 0.0395 0.9472 0.0825
+#> 104: 91.2662 -5.8136 -2.2357 -4.3063 -0.8700 0.3110 7.0356 4.0088 1.0024 2.4701 0.2067 0.1939 1.2806 0.0407 1.0387 0.0743
+#> 105: 91.4688 -5.7922 -2.2204 -4.3319 -0.8703 0.2767 6.6838 3.8084 0.9751 2.6368 0.1963 0.1967 1.3320 0.0470 1.2043 0.0580
+#> 106: 91.3665 -5.8505 -2.2225 -4.3614 -0.8757 0.2922 7.1982 3.6180 1.0018 2.6378 0.1865 0.2132 1.2613 0.0464 1.0683 0.0693
+#> 107: 91.4934 -5.8933 -2.1993 -4.3433 -0.9112 0.3267 6.8383 3.7379 0.9616 2.5329 0.1772 0.2169 1.2911 0.0449 1.0688 0.0731
+#> 108: 92.1268 -5.7807 -2.1863 -4.4348 -0.9273 0.3235 6.4964 3.5510 1.0093 2.9025 0.1718 0.2061 1.3153 0.0414 0.8982 0.0796
+#> 109: 91.6585 -5.9778 -2.2083 -4.3550 -0.9061 0.3339 6.1715 4.5778 1.0600 2.7574 0.1755 0.2163 1.2754 0.0382 0.8100 0.0868
+#> 110: 92.0456 -5.6784 -2.2236 -4.3483 -0.8911 0.3022 5.8630 4.3489 1.0427 2.6195 0.1667 0.2472 1.3782 0.0336 0.7819 0.0931
+#> 111: 92.2862 -5.6624 -2.1985 -4.3680 -0.9178 0.3156 5.5698 4.1315 1.0149 2.5443 0.1622 0.2348 1.3541 0.0415 0.7848 0.0868
+#> 112: 92.5436 -5.6572 -2.2134 -4.3290 -0.9267 0.3025 5.2913 3.9249 1.0720 2.5118 0.1541 0.2231 1.3798 0.0385 0.9087 0.0799
+#> 113: 92.5970 -5.6263 -2.2030 -4.3044 -0.9123 0.2856 5.0268 3.7287 1.1371 2.4674 0.1764 0.2119 1.3007 0.0455 0.8651 0.0850
+#> 114: 92.9227 -5.6379 -2.2032 -4.2926 -0.9187 0.3282 4.7754 3.5422 1.1022 2.4105 0.1676 0.2013 1.3103 0.0439 0.9003 0.0815
+#> 115: 92.7678 -5.8033 -2.1888 -4.2988 -0.9406 0.3026 4.5367 3.3651 1.1127 2.5043 0.1592 0.1913 1.3643 0.0420 0.9649 0.0800
+#> 116: 92.0655 -5.8531 -2.2033 -4.2989 -0.9487 0.3013 4.3098 3.6792 1.1260 2.4981 0.1513 0.1817 1.2783 0.0445 0.9812 0.0818
+#> 117: 92.2258 -5.7861 -2.2095 -4.3393 -0.9399 0.2998 4.0943 3.4952 1.0697 2.7102 0.1437 0.1752 1.3037 0.0426 0.9067 0.0786
+#> 118: 92.3560 -5.8080 -2.2058 -4.3166 -0.9480 0.2743 4.6025 3.3205 1.0709 2.6198 0.1432 0.1747 1.2850 0.0481 0.9236 0.0769
+#> 119: 92.0489 -5.7726 -2.1972 -4.2740 -0.9087 0.2627 4.3723 3.1544 1.0892 2.4888 0.1620 0.1660 1.2659 0.0435 0.8389 0.0832
+#> 120: 91.9163 -5.8211 -2.2101 -4.2770 -0.9142 0.2674 4.1537 3.1700 1.0985 2.5003 0.1795 0.1577 1.2289 0.0454 0.9280 0.0826
+#> 121: 92.0274 -5.7601 -2.1916 -4.2686 -0.9055 0.2571 3.9460 3.1181 1.1026 2.3985 0.1908 0.1498 1.3015 0.0432 0.9363 0.0807
+#> 122: 92.2933 -5.7972 -2.2019 -4.2888 -0.8932 0.2679 3.7487 3.1755 1.0809 2.3976 0.1843 0.1636 1.2918 0.0433 0.8760 0.0803
+#> 123: 92.3361 -5.8903 -2.1745 -4.3386 -0.9157 0.2665 3.5613 3.8794 1.1308 2.5838 0.1751 0.1555 1.3219 0.0421 0.8987 0.0806
+#> 124: 92.5677 -6.0471 -2.1638 -4.2764 -0.9325 0.2645 3.3832 4.6152 1.1336 2.4546 0.1664 0.1526 1.2938 0.0375 0.9412 0.0798
+#> 125: 92.7852 -5.9841 -2.1661 -4.2825 -0.9373 0.2866 3.2141 4.3844 1.0770 2.3788 0.1581 0.1727 1.3137 0.0417 0.9228 0.0733
+#> 126: 92.7867 -5.9126 -2.1636 -4.2413 -0.9141 0.2756 3.0534 4.1652 1.0857 2.2921 0.1502 0.1994 1.2428 0.0450 0.8206 0.0795
+#> 127: 92.8733 -5.9110 -2.1546 -4.2269 -0.9258 0.2531 2.9007 3.9569 1.0914 2.3822 0.1426 0.2029 1.3043 0.0369 0.8206 0.0795
+#> 128: 93.0457 -5.9202 -2.1505 -4.2076 -0.9466 0.2463 3.3353 3.7591 1.0647 2.3012 0.1355 0.2180 1.3420 0.0385 0.8503 0.0803
+#> 129: 92.9207 -5.9882 -2.1704 -4.2204 -0.9319 0.2464 4.3160 4.4368 1.1187 2.3415 0.1386 0.2316 1.2546 0.0435 0.8777 0.0830
+#> 130: 92.2660 -6.2043 -2.1712 -4.2251 -0.9276 0.2186 4.4370 5.1440 1.0817 2.3426 0.1338 0.2200 1.2733 0.0476 0.9132 0.0753
+#> 131: 92.1286 -6.4163 -2.1634 -4.2642 -0.9223 0.2300 4.2151 6.2253 1.0614 2.5012 0.1333 0.2090 1.2690 0.0430 0.8201 0.0814
+#> 132: 92.0287 -6.4297 -2.1522 -4.2717 -0.9259 0.2250 4.0044 6.1979 1.0791 2.5146 0.1314 0.1985 1.2736 0.0449 0.8671 0.0784
+#> 133: 91.6843 -6.1415 -2.1685 -4.2553 -0.9349 0.2209 3.8041 5.8880 1.1445 2.4277 0.1248 0.2026 1.3381 0.0426 0.9129 0.0858
+#> 134: 91.6928 -6.1408 -2.1467 -4.2709 -0.9270 0.2648 3.6139 5.5936 1.0873 2.5602 0.1305 0.1925 1.3202 0.0416 0.7626 0.0936
+#> 135: 91.7984 -6.0371 -2.1673 -4.2572 -0.9497 0.2480 3.4332 5.3139 1.0649 2.4322 0.1389 0.1829 1.2592 0.0544 0.9459 0.0831
+#> 136: 91.9754 -6.1770 -2.1769 -4.2311 -0.9401 0.2435 3.2616 5.0482 1.0717 2.3106 0.1691 0.1737 1.3170 0.0436 1.0497 0.0816
+#> 137: 92.1546 -6.1216 -2.1731 -4.2278 -0.9401 0.2492 3.0985 4.9378 1.0200 2.1950 0.1606 0.1988 1.4019 0.0421 1.0200 0.0766
+#> 138: 92.2370 -5.9463 -2.1794 -4.1949 -0.9321 0.2460 2.9436 4.6909 1.0203 2.1200 0.1535 0.1947 1.3378 0.0425 0.9448 0.0804
+#> 139: 92.2025 -5.8849 -2.1820 -4.1868 -0.9200 0.2294 2.9458 4.4564 0.9875 2.1260 0.1759 0.2080 1.3244 0.0428 1.0110 0.0778
+#> 140: 91.8182 -5.7494 -2.1569 -4.1998 -0.9095 0.2318 2.7985 4.2336 1.0015 2.1507 0.1830 0.2113 1.3502 0.0432 0.7716 0.0922
+#> 141: 91.8292 -5.9568 -2.1640 -4.2109 -0.9122 0.2130 4.4608 4.0219 1.0180 2.1032 0.1739 0.2057 1.3594 0.0419 0.8088 0.0883
+#> 142: 91.9995 -6.0927 -2.1471 -4.2313 -0.9091 0.1875 4.5415 4.7705 1.0571 2.1286 0.1810 0.1954 1.4145 0.0406 0.8943 0.0847
+#> 143: 91.9160 -5.9892 -2.1546 -4.2043 -0.9355 0.1819 4.3145 4.5320 1.1337 2.1453 0.1888 0.2208 1.3449 0.0394 1.0910 0.0797
+#> 144: 92.0136 -5.9765 -2.1643 -4.2346 -0.9448 0.2455 4.3041 4.3054 1.1130 2.1300 0.1817 0.3253 1.3828 0.0340 1.0535 0.0873
+#> 145: 92.3893 -6.2224 -2.1211 -4.2316 -0.9405 0.2285 5.2279 4.9099 1.0573 2.1037 0.1727 0.3091 1.3797 0.0340 1.0160 0.0832
+#> 146: 92.6097 -6.2204 -2.1406 -4.2210 -0.9217 0.1762 4.9665 5.4466 1.0724 2.1658 0.1640 0.2936 1.4421 0.0408 1.2412 0.0674
+#> 147: 92.8499 -6.0091 -2.1165 -4.2234 -0.9682 0.1783 4.7182 5.1743 1.0188 2.1714 0.1722 0.2789 1.4545 0.0397 1.4472 0.0556
+#> 148: 92.6602 -5.8003 -2.1059 -4.2132 -0.9282 0.2102 4.4823 4.9156 1.0106 2.1075 0.1880 0.2684 1.4013 0.0413 1.0748 0.0758
+#> 149: 92.7388 -5.8727 -2.1569 -4.2185 -0.9266 0.1868 4.2581 4.6698 1.1447 2.0851 0.1786 0.2550 1.3137 0.0413 0.9963 0.0723
+#> 150: 92.7348 -5.7926 -2.1184 -4.2257 -0.9324 0.1966 4.0452 4.4363 1.1760 2.1508 0.1697 0.2704 1.3792 0.0363 0.8204 0.0889
+#> 151: 92.7968 -5.7301 -2.1179 -4.1959 -0.9275 0.1927 3.8430 4.2145 1.1707 2.1702 0.1842 0.2569 1.3789 0.0387 0.7890 0.0873
+#> 152: 92.9011 -5.7417 -2.1622 -4.2086 -0.9215 0.1784 2.0089 3.0670 1.1984 2.2253 0.1814 0.2507 1.3431 0.0395 0.9622 0.0780
+#> 153: 92.8020 -5.7707 -2.1494 -4.2128 -0.9228 0.1818 2.2261 2.9648 1.1192 2.3058 0.1749 0.2548 1.3671 0.0369 0.9507 0.0744
+#> 154: 92.5217 -5.8043 -2.1447 -4.2074 -0.9303 0.1766 2.7638 3.1314 1.1141 2.2814 0.1811 0.2389 1.3250 0.0408 1.0538 0.0689
+#> 155: 92.8765 -5.5586 -2.1275 -4.1639 -0.9320 0.1434 2.4217 2.4658 1.1231 2.1314 0.1746 0.2426 1.3785 0.0407 0.9682 0.0796
+#> 156: 93.0074 -5.6819 -2.1343 -4.1819 -0.9382 0.1587 1.4756 2.7496 1.1200 2.1700 0.1849 0.2320 1.3643 0.0395 1.0875 0.0653
+#> 157: 92.7950 -5.6827 -2.1178 -4.1808 -0.9553 0.1585 1.1607 2.5156 1.1129 2.2109 0.1724 0.2366 1.4045 0.0374 1.1322 0.0676
+#> 158: 92.7684 -5.7106 -2.0933 -4.2149 -0.9717 0.1602 1.4884 2.6532 1.1269 2.1388 0.1838 0.2666 1.4009 0.0348 0.8728 0.0832
+#> 159: 93.0980 -5.8911 -2.1297 -4.2160 -0.9660 0.1407 1.6034 3.3765 1.1182 2.1661 0.1705 0.2804 1.3557 0.0430 1.0076 0.0776
+#> 160: 93.1849 -5.9433 -2.1177 -4.1735 -0.9436 0.1324 1.8692 4.0887 1.1252 2.0213 0.1642 0.2922 1.3251 0.0386 0.8586 0.0820
+#> 161: 93.4771 -5.7768 -2.0899 -4.1697 -0.9670 0.1043 2.0938 2.9110 1.1069 1.9538 0.1820 0.3046 1.3270 0.0413 0.8220 0.0855
+#> 162: 93.4961 -5.6516 -2.0965 -4.1633 -0.9708 0.1263 2.2053 2.3022 1.1179 1.9555 0.1758 0.2891 1.3158 0.0417 0.9943 0.0768
+#> 163: 93.1627 -5.5944 -2.1527 -4.1633 -0.9488 0.1452 2.9600 2.3291 1.1027 1.9555 0.1766 0.3000 1.3626 0.0376 0.9790 0.0743
+#> 164: 92.7951 -5.6646 -2.1539 -4.1699 -0.9447 0.1863 2.9195 2.7599 1.0794 1.9511 0.1651 0.2918 1.4091 0.0357 1.1005 0.0709
+#> 165: 92.6045 -5.5927 -2.1842 -4.1770 -0.9436 0.1939 2.2014 2.3213 1.0622 1.9775 0.1671 0.2899 1.3945 0.0372 1.0533 0.0694
+#> 166: 92.6660 -5.5922 -2.1438 -4.1611 -0.9441 0.1767 1.8951 2.3445 1.1025 2.0399 0.1802 0.2802 1.4229 0.0354 1.1552 0.0682
+#> 167: 92.4353 -5.5118 -2.1415 -4.1730 -0.9124 0.1827 1.5029 1.8145 1.0701 2.0090 0.1727 0.2642 1.4525 0.0362 1.0577 0.0754
+#> 168: 92.3761 -5.5522 -2.1625 -4.1911 -0.9114 0.1782 1.2703 2.0808 1.0814 2.0588 0.1810 0.2658 1.3973 0.0364 0.9874 0.0729
+#> 169: 92.5240 -5.6102 -2.1396 -4.1793 -0.8972 0.1722 1.3115 2.2750 1.0759 2.0910 0.2147 0.2549 1.3553 0.0392 0.9770 0.0759
+#> 170: 92.3827 -5.5942 -2.1231 -4.1847 -0.9338 0.1525 1.5707 2.3778 1.0542 2.0824 0.2042 0.2519 1.4424 0.0363 1.1270 0.0687
+#> 171: 92.1706 -5.6171 -2.1619 -4.1926 -0.9056 0.1390 1.0935 2.2869 1.1239 2.1697 0.1946 0.2624 1.2980 0.0411 0.9988 0.0740
+#> 172: 92.1491 -5.5704 -2.1447 -4.1913 -0.9285 0.1649 1.0292 2.2160 1.1231 2.1905 0.1860 0.2518 1.3154 0.0375 1.0152 0.0772
+#> 173: 91.9987 -5.5411 -2.1434 -4.1803 -0.9056 0.1585 0.6511 1.9989 1.0892 2.2283 0.1899 0.2413 1.3814 0.0380 1.1733 0.0693
+#> 174: 92.0377 -5.5419 -2.1081 -4.1928 -0.9057 0.1418 0.9013 2.0933 1.1813 2.2773 0.1756 0.2559 1.4419 0.0343 0.9942 0.0801
+#> 175: 92.0266 -5.5125 -2.1014 -4.1775 -0.9119 0.1371 0.7194 2.0624 1.1848 2.2328 0.1754 0.2504 1.3987 0.0353 1.0838 0.0728
+#> 176: 92.0365 -5.5658 -2.0914 -4.1646 -0.8956 0.1096 0.7557 2.0588 1.1642 2.1610 0.1617 0.2722 1.3658 0.0347 0.9405 0.0757
+#> 177: 91.8661 -5.6799 -2.0950 -4.1695 -0.9010 0.1193 0.8835 2.8899 1.1394 2.1886 0.1809 0.2777 1.3841 0.0351 0.9178 0.0794
+#> 178: 91.9392 -5.7853 -2.1139 -4.1711 -0.9190 0.1222 0.6673 3.0461 1.1712 2.1948 0.1576 0.2237 1.3623 0.0383 0.9060 0.0795
+#> 179: 92.0116 -5.7560 -2.1418 -4.1711 -0.9153 0.1034 0.4356 2.9139 1.1653 2.1948 0.1497 0.2364 1.3387 0.0392 0.9327 0.0793
+#> 180: 92.1013 -5.7920 -2.1368 -4.1654 -0.9059 0.0912 0.3859 3.2592 1.1357 2.1744 0.1570 0.2337 1.3622 0.0408 1.0299 0.0739
+#> 181: 92.1032 -5.8125 -2.1260 -4.1791 -0.9404 0.1731 0.4091 3.0817 1.1113 2.2356 0.1572 0.2742 1.4509 0.0340 0.9180 0.0865
+#> 182: 92.1315 -5.7991 -2.1327 -4.1737 -0.9319 0.1519 0.3145 3.0292 1.1520 2.1360 0.1661 0.2482 1.4105 0.0361 1.1338 0.0748
+#> 183: 92.1350 -6.0470 -2.1264 -4.1707 -0.9525 0.1787 0.2045 3.8296 1.1229 2.1369 0.1735 0.2453 1.3132 0.0350 1.0507 0.0759
+#> 184: 92.0539 -5.9856 -2.1289 -4.1968 -0.9281 0.1789 0.1166 3.9425 1.0558 2.2320 0.1658 0.2253 1.3390 0.0355 1.1271 0.0720
+#> 185: 92.0755 -6.0524 -2.1385 -4.2076 -0.9313 0.1794 0.1193 4.2430 1.0465 2.3571 0.1566 0.2152 1.3777 0.0368 1.2013 0.0631
+#> 186: 92.1639 -6.0663 -2.1399 -4.1869 -0.9311 0.1817 0.1392 4.4053 1.0495 2.4857 0.1532 0.2331 1.3751 0.0365 1.0497 0.0697
+#> 187: 92.1759 -6.3052 -2.1469 -4.2221 -0.9428 0.1970 0.1356 5.5622 0.9953 2.3367 0.1451 0.2359 1.3754 0.0367 1.0969 0.0656
+#> 188: 92.1744 -6.0494 -2.1406 -4.2445 -0.9595 0.2089 0.1364 4.3818 0.9882 2.4074 0.1480 0.2364 1.3709 0.0396 1.1259 0.0642
+#> 189: 92.1989 -6.1255 -2.1138 -4.2037 -0.9368 0.1796 0.1444 4.6756 0.9840 2.3786 0.1502 0.2303 1.3979 0.0393 1.2011 0.0630
+#> 190: 92.0944 -6.1343 -2.1536 -4.2106 -0.9267 0.2105 0.1288 4.4977 1.0475 2.3593 0.1443 0.2396 1.3247 0.0384 1.1304 0.0711
+#> 191: 92.1238 -6.0639 -2.1462 -4.2883 -0.9311 0.2155 0.1246 4.1066 1.0428 2.6836 0.1442 0.2344 1.4041 0.0344 1.1631 0.0684
+#> 192: 92.1328 -6.0743 -2.1232 -4.3119 -0.9586 0.2319 0.1192 4.1348 1.0020 2.7067 0.1466 0.2515 1.4039 0.0355 1.0021 0.0772
+#> 193: 92.0881 -5.8697 -2.1298 -4.2691 -0.9309 0.2295 0.1050 3.4476 0.9879 2.5496 0.1344 0.2348 1.4677 0.0351 1.0332 0.0705
+#> 194: 92.1086 -5.7557 -2.1176 -4.3249 -0.9029 0.2183 0.0702 2.7793 1.0043 2.8853 0.1460 0.2213 1.4733 0.0325 1.0929 0.0681
+#> 195: 92.1265 -5.8976 -2.1506 -4.2932 -0.9267 0.2511 0.0593 3.4959 0.9881 2.6806 0.1278 0.2505 1.6138 0.0350 1.1327 0.0703
+#> 196: 92.1316 -5.7018 -2.1627 -4.2889 -0.9278 0.2392 0.0717 2.9210 1.0160 2.7067 0.1470 0.2350 1.5063 0.0418 1.0525 0.0734
+#> 197: 92.1756 -5.7899 -2.1604 -4.2819 -0.9248 0.2765 0.0754 2.9991 1.0167 2.6170 0.1465 0.2314 1.4982 0.0387 1.0504 0.0774
+#> 198: 92.2153 -5.8248 -2.1571 -4.2245 -0.9350 0.2195 0.0651 3.0128 0.9196 2.3123 0.1451 0.2363 1.3965 0.0453 1.1561 0.0650
+#> 199: 92.1935 -5.8187 -2.1505 -4.2123 -0.9452 0.2406 0.0535 3.0017 0.9553 2.2771 0.1338 0.2415 1.4485 0.0407 1.0647 0.0699
+#> 200: 92.2308 -5.6732 -2.1578 -4.2182 -0.9324 0.2330 0.0618 2.4070 1.0687 2.2978 0.1513 0.2199 1.4101 0.0385 1.0283 0.0741
+#> 201: 92.2305 -5.6796 -2.1604 -4.2064 -0.9320 0.2262 0.0530 2.4360 1.0551 2.2994 0.1529 0.2219 1.3653 0.0407 1.0115 0.0757
+#> 202: 92.2259 -5.7201 -2.1550 -4.2058 -0.9263 0.2208 0.0461 2.6422 1.0351 2.2888 0.1520 0.2100 1.3739 0.0418 1.0474 0.0730
+#> 203: 92.2212 -5.7539 -2.1457 -4.2037 -0.9303 0.2163 0.0422 2.8480 1.0403 2.2723 0.1465 0.2070 1.3973 0.0404 1.0518 0.0729
+#> 204: 92.2164 -5.8068 -2.1371 -4.2093 -0.9300 0.2163 0.0383 3.1313 1.0426 2.2984 0.1423 0.2091 1.4025 0.0391 1.0284 0.0737
+#> 205: 92.2120 -5.8371 -2.1369 -4.2142 -0.9308 0.2156 0.0347 3.2786 1.0392 2.3249 0.1390 0.2048 1.4115 0.0385 1.0161 0.0733
+#> 206: 92.2071 -5.8681 -2.1391 -4.2176 -0.9287 0.2158 0.0336 3.4917 1.0442 2.3461 0.1388 0.2041 1.4017 0.0394 0.9977 0.0735
+#> 207: 92.2078 -5.8966 -2.1424 -4.2230 -0.9286 0.2181 0.0337 3.6741 1.0456 2.3743 0.1369 0.2009 1.3988 0.0397 0.9792 0.0740
+#> 208: 92.2077 -5.8972 -2.1459 -4.2249 -0.9300 0.2208 0.0340 3.6775 1.0460 2.3889 0.1362 0.1985 1.3969 0.0394 0.9729 0.0742
+#> 209: 92.2091 -5.8831 -2.1488 -4.2271 -0.9326 0.2227 0.0337 3.6019 1.0465 2.4005 0.1380 0.1967 1.3949 0.0395 0.9745 0.0741
+#> 210: 92.2115 -5.8806 -2.1490 -4.2282 -0.9349 0.2238 0.0324 3.5652 1.0516 2.4211 0.1386 0.1979 1.3941 0.0391 0.9820 0.0740
+#> 211: 92.2151 -5.8791 -2.1516 -4.2291 -0.9363 0.2258 0.0318 3.5315 1.0458 2.4465 0.1390 0.1989 1.3918 0.0394 0.9901 0.0735
+#> 212: 92.2189 -5.8789 -2.1532 -4.2297 -0.9380 0.2269 0.0312 3.4989 1.0434 2.4718 0.1409 0.1993 1.3884 0.0394 1.0007 0.0732
+#> 213: 92.2226 -5.8714 -2.1556 -4.2287 -0.9395 0.2255 0.0313 3.4460 1.0440 2.4800 0.1413 0.1993 1.3859 0.0397 1.0157 0.0722
+#> 214: 92.2233 -5.8706 -2.1553 -4.2279 -0.9394 0.2237 0.0309 3.4283 1.0431 2.4809 0.1414 0.2003 1.3849 0.0399 1.0186 0.0720
+#> 215: 92.2242 -5.8750 -2.1536 -4.2285 -0.9390 0.2212 0.0312 3.4442 1.0455 2.4800 0.1417 0.2015 1.3830 0.0401 1.0126 0.0723
+#> 216: 92.2252 -5.8788 -2.1521 -4.2277 -0.9393 0.2192 0.0316 3.4718 1.0459 2.4791 0.1410 0.2028 1.3817 0.0402 1.0046 0.0726
+#> 217: 92.2255 -5.8869 -2.1516 -4.2268 -0.9400 0.2177 0.0322 3.5295 1.0456 2.4751 0.1407 0.2042 1.3814 0.0401 1.0011 0.0729
+#> 218: 92.2230 -5.8819 -2.1511 -4.2259 -0.9400 0.2164 0.0327 3.5004 1.0473 2.4693 0.1399 0.2051 1.3784 0.0401 0.9962 0.0731
+#> 219: 92.2206 -5.8761 -2.1499 -4.2269 -0.9393 0.2156 0.0325 3.4736 1.0494 2.4667 0.1399 0.2066 1.3794 0.0399 0.9925 0.0734
+#> 220: 92.2185 -5.8775 -2.1494 -4.2267 -0.9380 0.2150 0.0331 3.4894 1.0511 2.4596 0.1396 0.2090 1.3788 0.0398 0.9881 0.0734
+#> 221: 92.2180 -5.8774 -2.1499 -4.2271 -0.9369 0.2142 0.0328 3.4873 1.0518 2.4559 0.1399 0.2109 1.3776 0.0399 0.9842 0.0735
+#> 222: 92.2191 -5.8833 -2.1503 -4.2280 -0.9359 0.2127 0.0328 3.5384 1.0518 2.4533 0.1400 0.2114 1.3778 0.0400 0.9825 0.0735
+#> 223: 92.2199 -5.8831 -2.1486 -4.2288 -0.9343 0.2112 0.0326 3.5474 1.0539 2.4515 0.1396 0.2127 1.3795 0.0398 0.9806 0.0735
+#> 224: 92.2206 -5.8870 -2.1467 -4.2283 -0.9331 0.2093 0.0324 3.5619 1.0550 2.4482 0.1395 0.2133 1.3805 0.0395 0.9792 0.0735
+#> 225: 92.2218 -5.8929 -2.1459 -4.2289 -0.9328 0.2086 0.0322 3.6001 1.0548 2.4492 0.1388 0.2142 1.3804 0.0393 0.9809 0.0734
+#> 226: 92.2228 -5.8909 -2.1440 -4.2293 -0.9322 0.2082 0.0320 3.6007 1.0566 2.4513 0.1383 0.2143 1.3826 0.0390 0.9815 0.0737
+#> 227: 92.2234 -5.8838 -2.1444 -4.2304 -0.9319 0.2088 0.0319 3.5748 1.0551 2.4562 0.1381 0.2140 1.3814 0.0390 0.9836 0.0736
+#> 228: 92.2243 -5.8835 -2.1444 -4.2314 -0.9326 0.2093 0.0317 3.5756 1.0526 2.4607 0.1377 0.2143 1.3824 0.0389 0.9901 0.0733
+#> 229: 92.2251 -5.8916 -2.1442 -4.2307 -0.9330 0.2095 0.0318 3.6344 1.0501 2.4580 0.1371 0.2148 1.3850 0.0388 0.9930 0.0733
+#> 230: 92.2250 -5.8951 -2.1442 -4.2303 -0.9334 0.2107 0.0318 3.6533 1.0475 2.4550 0.1369 0.2150 1.3872 0.0387 0.9953 0.0734
+#> 231: 92.2247 -5.8964 -2.1444 -4.2300 -0.9345 0.2119 0.0322 3.6564 1.0446 2.4549 0.1368 0.2151 1.3899 0.0388 0.9991 0.0733
+#> 232: 92.2230 -5.8982 -2.1451 -4.2306 -0.9352 0.2132 0.0326 3.6643 1.0422 2.4591 0.1365 0.2155 1.3934 0.0388 1.0052 0.0729
+#> 233: 92.2223 -5.9022 -2.1455 -4.2327 -0.9354 0.2141 0.0329 3.6824 1.0396 2.4697 0.1362 0.2165 1.3970 0.0388 1.0107 0.0726
+#> 234: 92.2200 -5.9075 -2.1457 -4.2324 -0.9348 0.2140 0.0335 3.7056 1.0364 2.4735 0.1366 0.2174 1.3977 0.0388 1.0163 0.0723
+#> 235: 92.2171 -5.9094 -2.1457 -4.2338 -0.9342 0.2142 0.0342 3.7222 1.0339 2.4854 0.1372 0.2189 1.3999 0.0389 1.0228 0.0721
+#> 236: 92.2161 -5.9195 -2.1464 -4.2368 -0.9340 0.2140 0.0346 3.7789 1.0329 2.4986 0.1376 0.2200 1.4007 0.0389 1.0281 0.0721
+#> 237: 92.2163 -5.9214 -2.1469 -4.2390 -0.9330 0.2143 0.0347 3.7862 1.0329 2.5074 0.1378 0.2195 1.4030 0.0389 1.0320 0.0719
+#> 238: 92.2165 -5.9203 -2.1473 -4.2399 -0.9326 0.2143 0.0347 3.7781 1.0336 2.5100 0.1381 0.2186 1.4031 0.0388 1.0347 0.0719
+#> 239: 92.2173 -5.9212 -2.1471 -4.2403 -0.9325 0.2136 0.0344 3.7908 1.0350 2.5128 0.1384 0.2175 1.4021 0.0389 1.0352 0.0718
+#> 240: 92.2178 -5.9217 -2.1470 -4.2394 -0.9322 0.2133 0.0342 3.8082 1.0363 2.5118 0.1384 0.2169 1.4025 0.0387 1.0345 0.0719
+#> 241: 92.2177 -5.9200 -2.1470 -4.2383 -0.9318 0.2136 0.0340 3.8123 1.0381 2.5110 0.1385 0.2161 1.4028 0.0387 1.0336 0.0720
+#> 242: 92.2170 -5.9109 -2.1478 -4.2371 -0.9308 0.2136 0.0340 3.7766 1.0387 2.5090 0.1385 0.2157 1.4027 0.0386 1.0322 0.0720
+#> 243: 92.2165 -5.9029 -2.1484 -4.2371 -0.9300 0.2140 0.0340 3.7433 1.0389 2.5128 0.1386 0.2150 1.4032 0.0385 1.0342 0.0720
+#> 244: 92.2161 -5.8998 -2.1489 -4.2374 -0.9294 0.2143 0.0340 3.7242 1.0392 2.5173 0.1386 0.2148 1.4030 0.0384 1.0343 0.0720
+#> 245: 92.2153 -5.9048 -2.1494 -4.2370 -0.9291 0.2149 0.0339 3.7491 1.0399 2.5182 0.1386 0.2146 1.4019 0.0383 1.0317 0.0722
+#> 246: 92.2147 -5.9093 -2.1498 -4.2371 -0.9289 0.2156 0.0339 3.7727 1.0409 2.5218 0.1384 0.2145 1.4016 0.0382 1.0309 0.0724
+#> 247: 92.2143 -5.9124 -2.1503 -4.2368 -0.9286 0.2159 0.0338 3.7972 1.0408 2.5232 0.1383 0.2144 1.4012 0.0382 1.0297 0.0725
+#> 248: 92.2137 -5.9122 -2.1500 -4.2367 -0.9286 0.2160 0.0336 3.8036 1.0409 2.5245 0.1382 0.2141 1.4022 0.0381 1.0272 0.0727
+#> 249: 92.2133 -5.9101 -2.1501 -4.2364 -0.9288 0.2160 0.0334 3.7984 1.0406 2.5268 0.1383 0.2136 1.4031 0.0381 1.0273 0.0726
+#> 250: 92.2139 -5.9115 -2.1502 -4.2368 -0.9289 0.2167 0.0335 3.8015 1.0412 2.5326 0.1380 0.2132 1.4035 0.0381 1.0261 0.0727
+#> 251: 92.2132 -5.9123 -2.1502 -4.2373 -0.9297 0.2170 0.0338 3.8015 1.0421 2.5362 0.1376 0.2126 1.4053 0.0379 1.0274 0.0727
+#> 252: 92.2128 -5.9106 -2.1502 -4.2366 -0.9299 0.2174 0.0338 3.7931 1.0427 2.5345 0.1371 0.2120 1.4062 0.0379 1.0262 0.0728
+#> 253: 92.2118 -5.9098 -2.1492 -4.2364 -0.9297 0.2173 0.0340 3.8011 1.0420 2.5338 0.1369 0.2121 1.4074 0.0378 1.0232 0.0731
+#> 254: 92.2107 -5.9104 -2.1479 -4.2362 -0.9296 0.2171 0.0341 3.8085 1.0398 2.5330 0.1366 0.2123 1.4093 0.0377 1.0230 0.0731
+#> 255: 92.2103 -5.9133 -2.1466 -4.2359 -0.9299 0.2166 0.0341 3.8219 1.0381 2.5346 0.1363 0.2122 1.4105 0.0377 1.0230 0.0731
+#> 256: 92.2094 -5.9171 -2.1453 -4.2356 -0.9299 0.2161 0.0341 3.8498 1.0366 2.5366 0.1362 0.2123 1.4114 0.0375 1.0239 0.0731
+#> 257: 92.2091 -5.9169 -2.1441 -4.2353 -0.9302 0.2153 0.0341 3.8529 1.0347 2.5385 0.1360 0.2118 1.4126 0.0375 1.0265 0.0729
+#> 258: 92.2089 -5.9191 -2.1431 -4.2349 -0.9301 0.2145 0.0340 3.8608 1.0331 2.5392 0.1359 0.2119 1.4126 0.0375 1.0282 0.0728
+#> 259: 92.2093 -5.9249 -2.1426 -4.2337 -0.9301 0.2145 0.0341 3.8853 1.0321 2.5385 0.1361 0.2120 1.4114 0.0374 1.0280 0.0728
+#> 260: 92.2095 -5.9297 -2.1415 -4.2328 -0.9303 0.2146 0.0339 3.9108 1.0302 2.5367 0.1358 0.2125 1.4112 0.0373 1.0265 0.0729
+#> 261: 92.2096 -5.9341 -2.1407 -4.2321 -0.9307 0.2147 0.0338 3.9343 1.0278 2.5343 0.1356 0.2131 1.4121 0.0373 1.0272 0.0728
+#> 262: 92.2094 -5.9342 -2.1398 -4.2312 -0.9310 0.2149 0.0336 3.9314 1.0254 2.5313 0.1356 0.2139 1.4115 0.0372 1.0249 0.0729
+#> 263: 92.2088 -5.9376 -2.1388 -4.2304 -0.9313 0.2153 0.0334 3.9452 1.0232 2.5289 0.1357 0.2143 1.4109 0.0371 1.0228 0.0731
+#> 264: 92.2077 -5.9410 -2.1379 -4.2301 -0.9317 0.2153 0.0333 3.9571 1.0204 2.5265 0.1356 0.2147 1.4105 0.0371 1.0224 0.0731
+#> 265: 92.2069 -5.9454 -2.1374 -4.2296 -0.9322 0.2154 0.0332 3.9800 1.0182 2.5230 0.1356 0.2147 1.4115 0.0371 1.0232 0.0730
+#> 266: 92.2067 -5.9463 -2.1370 -4.2291 -0.9324 0.2155 0.0330 3.9809 1.0165 2.5217 0.1354 0.2148 1.4121 0.0371 1.0220 0.0730
+#> 267: 92.2064 -5.9492 -2.1368 -4.2282 -0.9329 0.2154 0.0328 3.9874 1.0150 2.5199 0.1357 0.2150 1.4124 0.0370 1.0233 0.0729
+#> 268: 92.2065 -5.9468 -2.1360 -4.2276 -0.9333 0.2155 0.0328 3.9722 1.0133 2.5171 0.1362 0.2155 1.4133 0.0369 1.0243 0.0729
+#> 269: 92.2066 -5.9438 -2.1352 -4.2267 -0.9335 0.2151 0.0328 3.9526 1.0122 2.5142 0.1367 0.2154 1.4140 0.0369 1.0244 0.0728
+#> 270: 92.2067 -5.9388 -2.1351 -4.2259 -0.9339 0.2151 0.0326 3.9283 1.0112 2.5114 0.1370 0.2157 1.4137 0.0368 1.0240 0.0729
+#> 271: 92.2069 -5.9350 -2.1344 -4.2252 -0.9342 0.2152 0.0324 3.9072 1.0107 2.5094 0.1370 0.2158 1.4136 0.0367 1.0222 0.0730
+#> 272: 92.2069 -5.9317 -2.1341 -4.2246 -0.9348 0.2153 0.0321 3.8870 1.0104 2.5082 0.1372 0.2157 1.4139 0.0366 1.0219 0.0731
+#> 273: 92.2068 -5.9289 -2.1340 -4.2240 -0.9348 0.2152 0.0320 3.8711 1.0101 2.5075 0.1373 0.2159 1.4146 0.0366 1.0232 0.0730
+#> 274: 92.2067 -5.9271 -2.1337 -4.2239 -0.9350 0.2153 0.0318 3.8569 1.0101 2.5085 0.1377 0.2157 1.4144 0.0366 1.0239 0.0731
+#> 275: 92.2063 -5.9264 -2.1339 -4.2235 -0.9353 0.2156 0.0317 3.8476 1.0097 2.5078 0.1382 0.2157 1.4143 0.0365 1.0256 0.0730
+#> 276: 92.2059 -5.9271 -2.1339 -4.2231 -0.9354 0.2160 0.0316 3.8417 1.0097 2.5074 0.1387 0.2156 1.4132 0.0365 1.0260 0.0730
+#> 277: 92.2059 -5.9283 -2.1342 -4.2225 -0.9356 0.2163 0.0316 3.8412 1.0094 2.5073 0.1393 0.2155 1.4122 0.0364 1.0283 0.0729
+#> 278: 92.2062 -5.9278 -2.1341 -4.2220 -0.9361 0.2166 0.0318 3.8331 1.0081 2.5069 0.1397 0.2154 1.4117 0.0364 1.0321 0.0727
+#> 279: 92.2061 -5.9264 -2.1341 -4.2214 -0.9363 0.2168 0.0319 3.8188 1.0072 2.5051 0.1402 0.2155 1.4111 0.0364 1.0342 0.0726
+#> 280: 92.2057 -5.9263 -2.1344 -4.2211 -0.9365 0.2167 0.0321 3.8114 1.0072 2.5061 0.1406 0.2148 1.4108 0.0365 1.0361 0.0725
+#> 281: 92.2048 -5.9269 -2.1344 -4.2208 -0.9365 0.2166 0.0324 3.8082 1.0076 2.5077 0.1410 0.2142 1.4098 0.0365 1.0363 0.0726
+#> 282: 92.2045 -5.9257 -2.1347 -4.2205 -0.9366 0.2165 0.0328 3.8040 1.0082 2.5092 0.1413 0.2138 1.4090 0.0365 1.0364 0.0726
+#> 283: 92.2038 -5.9235 -2.1348 -4.2201 -0.9363 0.2163 0.0331 3.7955 1.0089 2.5108 0.1415 0.2134 1.4086 0.0365 1.0362 0.0726
+#> 284: 92.2032 -5.9234 -2.1348 -4.2198 -0.9359 0.2162 0.0335 3.7945 1.0100 2.5118 0.1420 0.2129 1.4083 0.0365 1.0362 0.0726
+#> 285: 92.2028 -5.9236 -2.1347 -4.2193 -0.9360 0.2161 0.0339 3.7930 1.0104 2.5124 0.1422 0.2125 1.4080 0.0365 1.0373 0.0725
+#> 286: 92.2020 -5.9221 -2.1344 -4.2187 -0.9355 0.2156 0.0341 3.7872 1.0104 2.5134 0.1425 0.2121 1.4074 0.0364 1.0377 0.0725
+#> 287: 92.2013 -5.9213 -2.1341 -4.2183 -0.9354 0.2154 0.0343 3.7888 1.0098 2.5151 0.1428 0.2119 1.4075 0.0364 1.0390 0.0724
+#> 288: 92.2003 -5.9195 -2.1339 -4.2182 -0.9355 0.2152 0.0343 3.7831 1.0090 2.5180 0.1430 0.2116 1.4082 0.0364 1.0408 0.0723
+#> 289: 92.1995 -5.9186 -2.1339 -4.2182 -0.9355 0.2154 0.0343 3.7805 1.0083 2.5217 0.1429 0.2115 1.4085 0.0364 1.0426 0.0722
+#> 290: 92.1984 -5.9180 -2.1339 -4.2177 -0.9354 0.2153 0.0343 3.7767 1.0080 2.5219 0.1427 0.2113 1.4083 0.0365 1.0429 0.0721
+#> 291: 92.1975 -5.9167 -2.1334 -4.2175 -0.9355 0.2151 0.0343 3.7701 1.0080 2.5230 0.1427 0.2108 1.4083 0.0364 1.0439 0.0721
+#> 292: 92.1971 -5.9175 -2.1330 -4.2166 -0.9356 0.2144 0.0342 3.7722 1.0081 2.5227 0.1426 0.2107 1.4079 0.0364 1.0443 0.0721
+#> 293: 92.1963 -5.9188 -2.1330 -4.2157 -0.9357 0.2141 0.0342 3.7768 1.0083 2.5242 0.1425 0.2103 1.4073 0.0364 1.0439 0.0721
+#> 294: 92.1953 -5.9189 -2.1328 -4.2157 -0.9357 0.2136 0.0344 3.7727 1.0078 2.5294 0.1427 0.2095 1.4079 0.0364 1.0456 0.0720
+#> 295: 92.1946 -5.9171 -2.1329 -4.2153 -0.9355 0.2135 0.0345 3.7623 1.0081 2.5331 0.1426 0.2090 1.4080 0.0364 1.0462 0.0720
+#> 296: 92.1940 -5.9154 -2.1329 -4.2150 -0.9354 0.2130 0.0346 3.7523 1.0082 2.5354 0.1425 0.2084 1.4075 0.0365 1.0463 0.0720
+#> 297: 92.1934 -5.9128 -2.1330 -4.2145 -0.9351 0.2127 0.0349 3.7395 1.0084 2.5373 0.1423 0.2079 1.4072 0.0365 1.0453 0.0720
+#> 298: 92.1932 -5.9128 -2.1332 -4.2138 -0.9347 0.2120 0.0350 3.7372 1.0085 2.5368 0.1423 0.2075 1.4068 0.0365 1.0449 0.0720
+#> 299: 92.1927 -5.9120 -2.1333 -4.2131 -0.9344 0.2112 0.0352 3.7324 1.0088 2.5366 0.1422 0.2070 1.4059 0.0366 1.0441 0.0721
+#> 300: 92.1921 -5.9097 -2.1335 -4.2122 -0.9343 0.2105 0.0353 3.7211 1.0096 2.5357 0.1425 0.2066 1.4050 0.0367 1.0443 0.0721
+#> 301: 92.1915 -5.9081 -2.1337 -4.2116 -0.9343 0.2098 0.0355 3.7110 1.0104 2.5355 0.1427 0.2061 1.4041 0.0368 1.0448 0.0721
+#> 302: 92.1912 -5.9067 -2.1340 -4.2108 -0.9342 0.2092 0.0355 3.7052 1.0114 2.5348 0.1428 0.2055 1.4036 0.0369 1.0442 0.0722
+#> 303: 92.1913 -5.9039 -2.1342 -4.2113 -0.9342 0.2087 0.0355 3.6925 1.0123 2.5408 0.1430 0.2049 1.4028 0.0369 1.0436 0.0723
+#> 304: 92.1920 -5.9012 -2.1342 -4.2119 -0.9342 0.2081 0.0356 3.6781 1.0129 2.5476 0.1432 0.2044 1.4026 0.0369 1.0436 0.0723
+#> 305: 92.1923 -5.8984 -2.1343 -4.2123 -0.9341 0.2076 0.0354 3.6633 1.0134 2.5525 0.1434 0.2038 1.4022 0.0370 1.0434 0.0724
+#> 306: 92.1926 -5.8977 -2.1343 -4.2121 -0.9343 0.2072 0.0354 3.6603 1.0144 2.5567 0.1436 0.2030 1.4022 0.0369 1.0431 0.0724
+#> 307: 92.1931 -5.8970 -2.1346 -4.2124 -0.9344 0.2068 0.0353 3.6555 1.0154 2.5617 0.1438 0.2021 1.4017 0.0370 1.0431 0.0725
+#> 308: 92.1935 -5.8963 -2.1347 -4.2127 -0.9343 0.2062 0.0351 3.6486 1.0166 2.5665 0.1439 0.2012 1.4017 0.0370 1.0431 0.0724
+#> 309: 92.1934 -5.8965 -2.1349 -4.2130 -0.9344 0.2058 0.0350 3.6454 1.0180 2.5711 0.1439 0.2003 1.4013 0.0370 1.0427 0.0725
+#> 310: 92.1935 -5.8965 -2.1349 -4.2133 -0.9345 0.2055 0.0350 3.6401 1.0193 2.5761 0.1439 0.1993 1.4013 0.0371 1.0418 0.0725
+#> 311: 92.1931 -5.8976 -2.1349 -4.2139 -0.9346 0.2052 0.0349 3.6416 1.0207 2.5820 0.1437 0.1982 1.4015 0.0370 1.0411 0.0726
+#> 312: 92.1928 -5.8995 -2.1350 -4.2149 -0.9349 0.2053 0.0350 3.6472 1.0222 2.5902 0.1437 0.1972 1.4018 0.0370 1.0412 0.0727
+#> 313: 92.1922 -5.8999 -2.1350 -4.2159 -0.9352 0.2055 0.0350 3.6450 1.0236 2.5989 0.1436 0.1962 1.4017 0.0369 1.0407 0.0728
+#> 314: 92.1913 -5.9021 -2.1353 -4.2171 -0.9353 0.2055 0.0350 3.6532 1.0244 2.6086 0.1437 0.1951 1.4019 0.0369 1.0409 0.0728
+#> 315: 92.1905 -5.9033 -2.1358 -4.2178 -0.9354 0.2055 0.0351 3.6591 1.0252 2.6142 0.1438 0.1941 1.4018 0.0369 1.0420 0.0728
+#> 316: 92.1895 -5.9043 -2.1358 -4.2186 -0.9352 0.2053 0.0352 3.6648 1.0266 2.6207 0.1441 0.1934 1.4016 0.0369 1.0420 0.0729
+#> 317: 92.1888 -5.9041 -2.1359 -4.2200 -0.9352 0.2052 0.0352 3.6673 1.0278 2.6312 0.1444 0.1926 1.4014 0.0369 1.0416 0.0729
+#> 318: 92.1879 -5.9039 -2.1360 -4.2212 -0.9352 0.2052 0.0354 3.6670 1.0292 2.6380 0.1446 0.1919 1.4010 0.0369 1.0403 0.0730
+#> 319: 92.1871 -5.9046 -2.1361 -4.2222 -0.9353 0.2052 0.0354 3.6709 1.0306 2.6432 0.1448 0.1912 1.4008 0.0369 1.0394 0.0731
+#> 320: 92.1863 -5.9023 -2.1365 -4.2229 -0.9355 0.2052 0.0355 3.6602 1.0318 2.6466 0.1448 0.1903 1.4011 0.0369 1.0398 0.0731
+#> 321: 92.1855 -5.8996 -2.1368 -4.2236 -0.9354 0.2053 0.0355 3.6491 1.0329 2.6505 0.1448 0.1895 1.4017 0.0369 1.0402 0.0731
+#> 322: 92.1850 -5.8979 -2.1370 -4.2243 -0.9353 0.2057 0.0356 3.6399 1.0341 2.6534 0.1447 0.1888 1.4020 0.0368 1.0394 0.0732
+#> 323: 92.1844 -5.8984 -2.1371 -4.2251 -0.9352 0.2059 0.0356 3.6431 1.0346 2.6566 0.1447 0.1882 1.4026 0.0368 1.0389 0.0733
+#> 324: 92.1838 -5.8967 -2.1372 -4.2257 -0.9353 0.2062 0.0356 3.6392 1.0351 2.6598 0.1445 0.1875 1.4031 0.0368 1.0382 0.0734
+#> 325: 92.1835 -5.8936 -2.1374 -4.2264 -0.9351 0.2066 0.0355 3.6288 1.0352 2.6633 0.1444 0.1869 1.4043 0.0367 1.0391 0.0734
+#> 326: 92.1837 -5.8936 -2.1376 -4.2276 -0.9350 0.2071 0.0354 3.6296 1.0354 2.6684 0.1444 0.1865 1.4043 0.0367 1.0380 0.0735
+#> 327: 92.1837 -5.8943 -2.1378 -4.2289 -0.9347 0.2076 0.0354 3.6348 1.0357 2.6746 0.1444 0.1860 1.4043 0.0366 1.0380 0.0735
+#> 328: 92.1838 -5.8953 -2.1380 -4.2297 -0.9345 0.2081 0.0354 3.6456 1.0360 2.6776 0.1444 0.1856 1.4043 0.0366 1.0379 0.0735
+#> 329: 92.1836 -5.8974 -2.1383 -4.2305 -0.9342 0.2085 0.0356 3.6591 1.0361 2.6802 0.1444 0.1852 1.4043 0.0366 1.0385 0.0735
+#> 330: 92.1832 -5.8994 -2.1387 -4.2305 -0.9342 0.2088 0.0358 3.6715 1.0364 2.6798 0.1443 0.1849 1.4037 0.0367 1.0378 0.0736
+#> 331: 92.1826 -5.8983 -2.1391 -4.2302 -0.9342 0.2091 0.0357 3.6670 1.0368 2.6800 0.1442 0.1845 1.4038 0.0367 1.0379 0.0736
+#> 332: 92.1824 -5.8959 -2.1396 -4.2301 -0.9341 0.2097 0.0357 3.6576 1.0375 2.6792 0.1442 0.1842 1.4034 0.0367 1.0372 0.0737
+#> 333: 92.1826 -5.8937 -2.1401 -4.2304 -0.9340 0.2104 0.0356 3.6487 1.0383 2.6798 0.1442 0.1838 1.4029 0.0367 1.0360 0.0738
+#> 334: 92.1825 -5.8911 -2.1407 -4.2311 -0.9339 0.2112 0.0355 3.6378 1.0390 2.6825 0.1444 0.1834 1.4025 0.0367 1.0349 0.0739
+#> 335: 92.1830 -5.8887 -2.1411 -4.2317 -0.9336 0.2118 0.0355 3.6294 1.0396 2.6850 0.1444 0.1830 1.4022 0.0367 1.0338 0.0740
+#> 336: 92.1834 -5.8872 -2.1413 -4.2324 -0.9334 0.2124 0.0356 3.6249 1.0402 2.6880 0.1444 0.1825 1.4024 0.0367 1.0339 0.0740
+#> 337: 92.1835 -5.8869 -2.1416 -4.2334 -0.9332 0.2131 0.0356 3.6252 1.0411 2.6926 0.1443 0.1821 1.4029 0.0366 1.0330 0.0741
+#> 338: 92.1839 -5.8882 -2.1418 -4.2346 -0.9333 0.2137 0.0357 3.6332 1.0421 2.6972 0.1441 0.1815 1.4036 0.0366 1.0324 0.0742
+#> 339: 92.1845 -5.8869 -2.1420 -4.2358 -0.9332 0.2143 0.0357 3.6261 1.0428 2.7021 0.1439 0.1810 1.4043 0.0366 1.0322 0.0742
+#> 340: 92.1846 -5.8863 -2.1421 -4.2367 -0.9331 0.2147 0.0357 3.6242 1.0436 2.7060 0.1439 0.1804 1.4049 0.0365 1.0328 0.0743
+#> 341: 92.1848 -5.8847 -2.1421 -4.2378 -0.9330 0.2150 0.0356 3.6177 1.0442 2.7099 0.1439 0.1798 1.4056 0.0366 1.0334 0.0743
+#> 342: 92.1848 -5.8838 -2.1421 -4.2390 -0.9330 0.2154 0.0355 3.6114 1.0449 2.7151 0.1438 0.1792 1.4064 0.0365 1.0332 0.0743
+#> 343: 92.1849 -5.8840 -2.1423 -4.2398 -0.9330 0.2157 0.0353 3.6109 1.0459 2.7191 0.1438 0.1785 1.4060 0.0366 1.0334 0.0743
+#> 344: 92.1851 -5.8839 -2.1423 -4.2406 -0.9330 0.2159 0.0352 3.6092 1.0467 2.7229 0.1440 0.1779 1.4060 0.0365 1.0338 0.0743
+#> 345: 92.1850 -5.8841 -2.1424 -4.2414 -0.9331 0.2162 0.0352 3.6070 1.0472 2.7263 0.1441 0.1774 1.4056 0.0365 1.0341 0.0743
+#> 346: 92.1848 -5.8839 -2.1424 -4.2420 -0.9333 0.2164 0.0352 3.6048 1.0479 2.7292 0.1443 0.1769 1.4058 0.0365 1.0344 0.0743
+#> 347: 92.1846 -5.8835 -2.1425 -4.2427 -0.9334 0.2166 0.0353 3.6017 1.0495 2.7330 0.1444 0.1763 1.4053 0.0365 1.0343 0.0743
+#> 348: 92.1846 -5.8825 -2.1427 -4.2434 -0.9336 0.2168 0.0353 3.5968 1.0508 2.7362 0.1445 0.1757 1.4051 0.0365 1.0343 0.0743
+#> 349: 92.1846 -5.8820 -2.1432 -4.2444 -0.9337 0.2172 0.0352 3.5937 1.0519 2.7412 0.1446 0.1752 1.4047 0.0365 1.0343 0.0743
+#> 350: 92.1845 -5.8817 -2.1435 -4.2454 -0.9338 0.2179 0.0351 3.5899 1.0526 2.7460 0.1448 0.1747 1.4042 0.0365 1.0339 0.0744
+#> 351: 92.1844 -5.8824 -2.1439 -4.2468 -0.9338 0.2184 0.0350 3.5917 1.0535 2.7531 0.1448 0.1740 1.4041 0.0365 1.0336 0.0744
+#> 352: 92.1840 -5.8840 -2.1442 -4.2482 -0.9338 0.2189 0.0350 3.6013 1.0543 2.7603 0.1450 0.1734 1.4044 0.0364 1.0342 0.0744
+#> 353: 92.1838 -5.8848 -2.1445 -4.2492 -0.9336 0.2194 0.0349 3.6030 1.0552 2.7652 0.1451 0.1730 1.4043 0.0364 1.0338 0.0744
+#> 354: 92.1838 -5.8835 -2.1449 -4.2501 -0.9336 0.2197 0.0349 3.5961 1.0563 2.7697 0.1452 0.1723 1.4044 0.0364 1.0342 0.0744
+#> 355: 92.1837 -5.8826 -2.1453 -4.2511 -0.9335 0.2199 0.0348 3.5910 1.0569 2.7757 0.1451 0.1718 1.4053 0.0364 1.0348 0.0744
+#> 356: 92.1835 -5.8826 -2.1456 -4.2520 -0.9334 0.2198 0.0348 3.5922 1.0577 2.7815 0.1451 0.1712 1.4054 0.0364 1.0352 0.0744
+#> 357: 92.1834 -5.8818 -2.1457 -4.2525 -0.9334 0.2198 0.0349 3.5894 1.0588 2.7852 0.1449 0.1706 1.4058 0.0364 1.0354 0.0744
+#> 358: 92.1834 -5.8808 -2.1459 -4.2531 -0.9334 0.2197 0.0348 3.5861 1.0600 2.7891 0.1449 0.1701 1.4062 0.0364 1.0361 0.0744
+#> 359: 92.1833 -5.8799 -2.1459 -4.2533 -0.9333 0.2197 0.0350 3.5822 1.0607 2.7903 0.1448 0.1696 1.4063 0.0364 1.0360 0.0744
+#> 360: 92.1831 -5.8792 -2.1460 -4.2534 -0.9332 0.2196 0.0351 3.5787 1.0613 2.7914 0.1446 0.1691 1.4065 0.0364 1.0361 0.0744
+#> 361: 92.1831 -5.8785 -2.1460 -4.2542 -0.9331 0.2196 0.0351 3.5771 1.0620 2.7969 0.1445 0.1688 1.4072 0.0364 1.0366 0.0744
+#> 362: 92.1832 -5.8780 -2.1462 -4.2547 -0.9331 0.2195 0.0351 3.5750 1.0625 2.8017 0.1443 0.1683 1.4079 0.0363 1.0369 0.0744
+#> 363: 92.1830 -5.8788 -2.1464 -4.2551 -0.9331 0.2192 0.0351 3.5785 1.0630 2.8057 0.1443 0.1677 1.4081 0.0363 1.0377 0.0743
+#> 364: 92.1829 -5.8778 -2.1466 -4.2554 -0.9332 0.2193 0.0350 3.5747 1.0634 2.8092 0.1443 0.1672 1.4084 0.0363 1.0386 0.0743
+#> 365: 92.1830 -5.8782 -2.1466 -4.2558 -0.9332 0.2192 0.0350 3.5771 1.0638 2.8135 0.1443 0.1667 1.4086 0.0363 1.0385 0.0743
+#> 366: 92.1830 -5.8795 -2.1465 -4.2564 -0.9332 0.2190 0.0350 3.5838 1.0645 2.8190 0.1444 0.1661 1.4086 0.0363 1.0390 0.0743
+#> 367: 92.1826 -5.8801 -2.1465 -4.2569 -0.9333 0.2191 0.0349 3.5867 1.0652 2.8232 0.1445 0.1657 1.4086 0.0362 1.0388 0.0744
+#> 368: 92.1824 -5.8799 -2.1465 -4.2571 -0.9333 0.2193 0.0348 3.5859 1.0654 2.8252 0.1445 0.1653 1.4088 0.0362 1.0385 0.0744
+#> 369: 92.1822 -5.8803 -2.1467 -4.2572 -0.9333 0.2193 0.0348 3.5846 1.0653 2.8261 0.1444 0.1648 1.4086 0.0362 1.0393 0.0744
+#> 370: 92.1820 -5.8802 -2.1469 -4.2575 -0.9333 0.2195 0.0348 3.5822 1.0653 2.8273 0.1444 0.1645 1.4088 0.0362 1.0396 0.0744
+#> 371: 92.1818 -5.8806 -2.1470 -4.2575 -0.9333 0.2198 0.0348 3.5819 1.0649 2.8277 0.1443 0.1642 1.4091 0.0362 1.0403 0.0743
+#> 372: 92.1818 -5.8804 -2.1473 -4.2580 -0.9332 0.2202 0.0348 3.5795 1.0645 2.8300 0.1441 0.1640 1.4096 0.0362 1.0418 0.0743
+#> 373: 92.1816 -5.8812 -2.1475 -4.2580 -0.9332 0.2203 0.0348 3.5816 1.0644 2.8298 0.1441 0.1639 1.4100 0.0362 1.0439 0.0741
+#> 374: 92.1815 -5.8817 -2.1477 -4.2578 -0.9333 0.2203 0.0349 3.5819 1.0641 2.8282 0.1440 0.1641 1.4099 0.0362 1.0443 0.0741
+#> 375: 92.1817 -5.8828 -2.1479 -4.2574 -0.9335 0.2204 0.0351 3.5853 1.0636 2.8267 0.1440 0.1642 1.4100 0.0362 1.0457 0.0740
+#> 376: 92.1819 -5.8826 -2.1479 -4.2573 -0.9338 0.2206 0.0353 3.5843 1.0634 2.8246 0.1440 0.1643 1.4100 0.0362 1.0464 0.0740
+#> 377: 92.1819 -5.8826 -2.1480 -4.2572 -0.9339 0.2206 0.0354 3.5819 1.0633 2.8225 0.1440 0.1644 1.4097 0.0363 1.0470 0.0739
+#> 378: 92.1819 -5.8821 -2.1481 -4.2571 -0.9340 0.2205 0.0355 3.5777 1.0633 2.8206 0.1440 0.1644 1.4093 0.0363 1.0468 0.0739
+#> 379: 92.1819 -5.8823 -2.1481 -4.2573 -0.9340 0.2205 0.0356 3.5746 1.0633 2.8201 0.1439 0.1645 1.4092 0.0363 1.0468 0.0739
+#> 380: 92.1820 -5.8809 -2.1481 -4.2570 -0.9340 0.2205 0.0356 3.5665 1.0634 2.8178 0.1439 0.1647 1.4093 0.0363 1.0463 0.0739
+#> 381: 92.1823 -5.8795 -2.1481 -4.2568 -0.9338 0.2204 0.0357 3.5586 1.0635 2.8170 0.1439 0.1648 1.4095 0.0363 1.0456 0.0740
+#> 382: 92.1828 -5.8783 -2.1481 -4.2571 -0.9339 0.2203 0.0357 3.5514 1.0636 2.8183 0.1441 0.1649 1.4093 0.0363 1.0462 0.0740
+#> 383: 92.1827 -5.8773 -2.1480 -4.2569 -0.9340 0.2202 0.0357 3.5459 1.0633 2.8173 0.1441 0.1650 1.4094 0.0363 1.0465 0.0739
+#> 384: 92.1825 -5.8763 -2.1482 -4.2568 -0.9341 0.2202 0.0357 3.5397 1.0636 2.8165 0.1441 0.1650 1.4094 0.0363 1.0467 0.0739
+#> 385: 92.1822 -5.8761 -2.1483 -4.2567 -0.9341 0.2201 0.0357 3.5363 1.0641 2.8160 0.1440 0.1650 1.4094 0.0363 1.0469 0.0739
+#> 386: 92.1820 -5.8763 -2.1485 -4.2567 -0.9342 0.2200 0.0356 3.5365 1.0645 2.8157 0.1441 0.1648 1.4092 0.0364 1.0478 0.0738
+#> 387: 92.1819 -5.8767 -2.1486 -4.2567 -0.9343 0.2201 0.0358 3.5383 1.0652 2.8156 0.1442 0.1646 1.4090 0.0364 1.0480 0.0738
+#> 388: 92.1818 -5.8772 -2.1488 -4.2569 -0.9344 0.2202 0.0359 3.5400 1.0656 2.8153 0.1443 0.1645 1.4086 0.0364 1.0480 0.0738
+#> 389: 92.1816 -5.8765 -2.1489 -4.2569 -0.9344 0.2203 0.0359 3.5369 1.0660 2.8145 0.1443 0.1644 1.4083 0.0364 1.0476 0.0738
+#> 390: 92.1815 -5.8761 -2.1490 -4.2569 -0.9343 0.2205 0.0359 3.5349 1.0664 2.8136 0.1444 0.1644 1.4080 0.0364 1.0472 0.0738
+#> 391: 92.1814 -5.8749 -2.1492 -4.2572 -0.9343 0.2207 0.0359 3.5313 1.0668 2.8153 0.1445 0.1643 1.4077 0.0364 1.0465 0.0739
+#> 392: 92.1812 -5.8733 -2.1494 -4.2571 -0.9344 0.2210 0.0359 3.5248 1.0674 2.8141 0.1445 0.1642 1.4073 0.0364 1.0457 0.0739
+#> 393: 92.1811 -5.8727 -2.1497 -4.2570 -0.9345 0.2212 0.0359 3.5226 1.0679 2.8127 0.1445 0.1642 1.4071 0.0364 1.0457 0.0739
+#> 394: 92.1811 -5.8712 -2.1500 -4.2572 -0.9346 0.2214 0.0360 3.5174 1.0684 2.8132 0.1446 0.1641 1.4067 0.0364 1.0456 0.0739
+#> 395: 92.1810 -5.8714 -2.1501 -4.2579 -0.9348 0.2217 0.0361 3.5182 1.0685 2.8171 0.1445 0.1641 1.4065 0.0364 1.0452 0.0740
+#> 396: 92.1809 -5.8711 -2.1501 -4.2582 -0.9350 0.2220 0.0363 3.5161 1.0681 2.8184 0.1446 0.1639 1.4063 0.0364 1.0447 0.0740
+#> 397: 92.1809 -5.8707 -2.1503 -4.2585 -0.9352 0.2222 0.0363 3.5119 1.0684 2.8197 0.1446 0.1637 1.4065 0.0364 1.0442 0.0740
+#> 398: 92.1808 -5.8703 -2.1503 -4.2591 -0.9354 0.2224 0.0363 3.5084 1.0689 2.8218 0.1447 0.1634 1.4064 0.0364 1.0445 0.0740
+#> 399: 92.1806 -5.8711 -2.1503 -4.2596 -0.9355 0.2226 0.0364 3.5114 1.0691 2.8234 0.1447 0.1629 1.4061 0.0364 1.0447 0.0740
+#> 400: 92.1806 -5.8713 -2.1503 -4.2601 -0.9356 0.2229 0.0366 3.5113 1.0695 2.8253 0.1448 0.1626 1.4059 0.0364 1.0440 0.0740
+#> 401: 92.1804 -5.8709 -2.1503 -4.2604 -0.9357 0.2231 0.0367 3.5089 1.0696 2.8266 0.1448 0.1624 1.4058 0.0364 1.0440 0.0740
+#> 402: 92.1801 -5.8705 -2.1502 -4.2606 -0.9358 0.2232 0.0368 3.5071 1.0695 2.8268 0.1447 0.1621 1.4060 0.0364 1.0447 0.0740
+#> 403: 92.1800 -5.8708 -2.1503 -4.2610 -0.9359 0.2234 0.0369 3.5083 1.0697 2.8271 0.1447 0.1618 1.4056 0.0365 1.0448 0.0739
+#> 404: 92.1798 -5.8709 -2.1505 -4.2612 -0.9360 0.2237 0.0369 3.5085 1.0699 2.8262 0.1447 0.1616 1.4055 0.0365 1.0449 0.0739
+#> 405: 92.1795 -5.8705 -2.1503 -4.2613 -0.9360 0.2239 0.0370 3.5059 1.0698 2.8254 0.1448 0.1615 1.4052 0.0364 1.0449 0.0739
+#> 406: 92.1792 -5.8710 -2.1504 -4.2613 -0.9359 0.2243 0.0371 3.5069 1.0696 2.8244 0.1449 0.1614 1.4049 0.0364 1.0447 0.0739
+#> 407: 92.1788 -5.8718 -2.1505 -4.2614 -0.9359 0.2243 0.0372 3.5092 1.0697 2.8234 0.1449 0.1614 1.4046 0.0364 1.0448 0.0739
+#> 408: 92.1786 -5.8729 -2.1505 -4.2615 -0.9360 0.2245 0.0373 3.5140 1.0699 2.8223 0.1449 0.1612 1.4045 0.0365 1.0455 0.0739
+#> 409: 92.1784 -5.8740 -2.1506 -4.2615 -0.9360 0.2246 0.0373 3.5192 1.0700 2.8213 0.1450 0.1610 1.4042 0.0365 1.0462 0.0738
+#> 410: 92.1782 -5.8753 -2.1505 -4.2616 -0.9361 0.2246 0.0373 3.5248 1.0705 2.8205 0.1450 0.1607 1.4040 0.0365 1.0465 0.0738
+#> 411: 92.1780 -5.8758 -2.1503 -4.2619 -0.9362 0.2247 0.0374 3.5249 1.0707 2.8204 0.1449 0.1605 1.4043 0.0364 1.0467 0.0738
+#> 412: 92.1778 -5.8759 -2.1502 -4.2621 -0.9363 0.2248 0.0374 3.5238 1.0707 2.8209 0.1448 0.1602 1.4045 0.0364 1.0466 0.0738
+#> 413: 92.1779 -5.8759 -2.1501 -4.2623 -0.9364 0.2249 0.0374 3.5225 1.0711 2.8213 0.1448 0.1600 1.4043 0.0364 1.0460 0.0738
+#> 414: 92.1781 -5.8754 -2.1500 -4.2622 -0.9364 0.2250 0.0374 3.5205 1.0710 2.8203 0.1448 0.1599 1.4047 0.0364 1.0456 0.0738
+#> 415: 92.1781 -5.8750 -2.1499 -4.2623 -0.9363 0.2251 0.0374 3.5187 1.0709 2.8190 0.1448 0.1598 1.4050 0.0364 1.0448 0.0738
+#> 416: 92.1783 -5.8747 -2.1500 -4.2624 -0.9363 0.2252 0.0375 3.5216 1.0708 2.8187 0.1448 0.1598 1.4052 0.0364 1.0440 0.0738
+#> 417: 92.1783 -5.8738 -2.1500 -4.2625 -0.9362 0.2252 0.0375 3.5219 1.0712 2.8188 0.1447 0.1597 1.4055 0.0364 1.0438 0.0739
+#> 418: 92.1784 -5.8735 -2.1501 -4.2627 -0.9360 0.2254 0.0375 3.5222 1.0715 2.8193 0.1448 0.1596 1.4057 0.0364 1.0438 0.0739
+#> 419: 92.1784 -5.8725 -2.1501 -4.2629 -0.9358 0.2255 0.0376 3.5190 1.0719 2.8202 0.1447 0.1594 1.4060 0.0364 1.0436 0.0739
+#> 420: 92.1785 -5.8713 -2.1500 -4.2633 -0.9357 0.2256 0.0377 3.5152 1.0723 2.8213 0.1447 0.1592 1.4065 0.0364 1.0439 0.0738
+#> 421: 92.1786 -5.8697 -2.1500 -4.2639 -0.9355 0.2257 0.0377 3.5100 1.0728 2.8232 0.1448 0.1592 1.4068 0.0364 1.0436 0.0739
+#> 422: 92.1787 -5.8683 -2.1502 -4.2645 -0.9352 0.2260 0.0377 3.5051 1.0732 2.8258 0.1448 0.1592 1.4069 0.0364 1.0432 0.0739
+#> 423: 92.1788 -5.8667 -2.1504 -4.2653 -0.9350 0.2262 0.0377 3.4992 1.0736 2.8292 0.1448 0.1592 1.4071 0.0364 1.0435 0.0738
+#> 424: 92.1789 -5.8659 -2.1505 -4.2661 -0.9349 0.2263 0.0378 3.4972 1.0739 2.8324 0.1448 0.1591 1.4069 0.0364 1.0439 0.0738
+#> 425: 92.1788 -5.8649 -2.1505 -4.2669 -0.9349 0.2263 0.0378 3.4947 1.0740 2.8358 0.1448 0.1590 1.4071 0.0364 1.0438 0.0738
+#> 426: 92.1788 -5.8643 -2.1506 -4.2677 -0.9348 0.2265 0.0377 3.4922 1.0743 2.8389 0.1448 0.1589 1.4070 0.0365 1.0437 0.0738
+#> 427: 92.1785 -5.8637 -2.1506 -4.2683 -0.9347 0.2266 0.0378 3.4895 1.0747 2.8425 0.1448 0.1588 1.4068 0.0365 1.0434 0.0738
+#> 428: 92.1783 -5.8627 -2.1507 -4.2689 -0.9347 0.2268 0.0378 3.4870 1.0749 2.8464 0.1447 0.1586 1.4070 0.0365 1.0434 0.0738
+#> 429: 92.1782 -5.8617 -2.1509 -4.2696 -0.9347 0.2271 0.0379 3.4845 1.0752 2.8500 0.1446 0.1584 1.4072 0.0365 1.0439 0.0738
+#> 430: 92.1783 -5.8608 -2.1510 -4.2701 -0.9347 0.2274 0.0379 3.4830 1.0755 2.8526 0.1446 0.1582 1.4075 0.0365 1.0443 0.0738
+#> 431: 92.1784 -5.8606 -2.1511 -4.2704 -0.9348 0.2275 0.0379 3.4825 1.0757 2.8532 0.1446 0.1580 1.4076 0.0365 1.0439 0.0738
+#> 432: 92.1784 -5.8610 -2.1512 -4.2707 -0.9350 0.2275 0.0378 3.4833 1.0761 2.8539 0.1447 0.1578 1.4079 0.0365 1.0443 0.0738
+#> 433: 92.1783 -5.8618 -2.1512 -4.2711 -0.9351 0.2276 0.0378 3.4867 1.0768 2.8554 0.1447 0.1577 1.4078 0.0366 1.0440 0.0738
+#> 434: 92.1784 -5.8612 -2.1513 -4.2714 -0.9350 0.2278 0.0378 3.4858 1.0774 2.8564 0.1448 0.1577 1.4074 0.0365 1.0430 0.0739
+#> 435: 92.1783 -5.8610 -2.1513 -4.2718 -0.9348 0.2279 0.0377 3.4874 1.0779 2.8581 0.1448 0.1576 1.4072 0.0366 1.0423 0.0739
+#> 436: 92.1781 -5.8610 -2.1513 -4.2721 -0.9346 0.2280 0.0376 3.4879 1.0789 2.8598 0.1448 0.1575 1.4070 0.0365 1.0417 0.0739
+#> 437: 92.1781 -5.8610 -2.1511 -4.2726 -0.9345 0.2279 0.0376 3.4886 1.0794 2.8618 0.1449 0.1574 1.4071 0.0365 1.0417 0.0739
+#> 438: 92.1781 -5.8609 -2.1510 -4.2730 -0.9345 0.2280 0.0375 3.4893 1.0797 2.8641 0.1449 0.1573 1.4075 0.0365 1.0420 0.0739
+#> 439: 92.1781 -5.8608 -2.1509 -4.2734 -0.9343 0.2280 0.0374 3.4894 1.0803 2.8659 0.1449 0.1573 1.4076 0.0365 1.0421 0.0739
+#> 440: 92.1780 -5.8603 -2.1510 -4.2737 -0.9343 0.2279 0.0374 3.4885 1.0808 2.8674 0.1448 0.1573 1.4079 0.0365 1.0430 0.0738
+#> 441: 92.1779 -5.8600 -2.1510 -4.2738 -0.9342 0.2279 0.0373 3.4899 1.0811 2.8686 0.1447 0.1574 1.4086 0.0365 1.0445 0.0737
+#> 442: 92.1779 -5.8600 -2.1509 -4.2737 -0.9343 0.2278 0.0372 3.4925 1.0814 2.8691 0.1447 0.1575 1.4088 0.0365 1.0451 0.0737
+#> 443: 92.1780 -5.8598 -2.1509 -4.2739 -0.9341 0.2278 0.0372 3.4949 1.0819 2.8705 0.1447 0.1576 1.4092 0.0365 1.0453 0.0737
+#> 444: 92.1779 -5.8593 -2.1510 -4.2742 -0.9340 0.2277 0.0371 3.4951 1.0824 2.8717 0.1447 0.1576 1.4096 0.0365 1.0455 0.0737
+#> 445: 92.1777 -5.8593 -2.1511 -4.2744 -0.9338 0.2275 0.0371 3.4999 1.0828 2.8729 0.1448 0.1576 1.4100 0.0365 1.0461 0.0736
+#> 446: 92.1774 -5.8600 -2.1511 -4.2748 -0.9338 0.2274 0.0372 3.5051 1.0837 2.8747 0.1449 0.1576 1.4099 0.0365 1.0464 0.0736
+#> 447: 92.1771 -5.8604 -2.1512 -4.2751 -0.9338 0.2273 0.0373 3.5087 1.0844 2.8758 0.1449 0.1575 1.4097 0.0365 1.0467 0.0736
+#> 448: 92.1769 -5.8607 -2.1513 -4.2756 -0.9336 0.2272 0.0374 3.5124 1.0849 2.8778 0.1449 0.1575 1.4098 0.0365 1.0470 0.0735
+#> 449: 92.1768 -5.8611 -2.1515 -4.2759 -0.9337 0.2270 0.0374 3.5165 1.0853 2.8789 0.1449 0.1575 1.4101 0.0365 1.0473 0.0735
+#> 450: 92.1766 -5.8611 -2.1515 -4.2762 -0.9337 0.2269 0.0374 3.5158 1.0859 2.8800 0.1448 0.1576 1.4102 0.0365 1.0474 0.0735
+#> 451: 92.1762 -5.8615 -2.1514 -4.2765 -0.9337 0.2267 0.0374 3.5202 1.0866 2.8812 0.1447 0.1576 1.4104 0.0365 1.0477 0.0735
+#> 452: 92.1761 -5.8622 -2.1514 -4.2767 -0.9337 0.2264 0.0374 3.5232 1.0871 2.8824 0.1447 0.1576 1.4103 0.0365 1.0479 0.0734
+#> 453: 92.1760 -5.8621 -2.1514 -4.2776 -0.9336 0.2261 0.0373 3.5247 1.0878 2.8901 0.1447 0.1576 1.4103 0.0365 1.0480 0.0734
+#> 454: 92.1759 -5.8611 -2.1513 -4.2781 -0.9335 0.2259 0.0373 3.5206 1.0882 2.8939 0.1448 0.1575 1.4104 0.0365 1.0483 0.0734
+#> 455: 92.1758 -5.8599 -2.1513 -4.2788 -0.9336 0.2258 0.0372 3.5151 1.0887 2.9010 0.1448 0.1575 1.4104 0.0365 1.0485 0.0734
+#> 456: 92.1760 -5.8583 -2.1512 -4.2797 -0.9335 0.2258 0.0372 3.5086 1.0892 2.9081 0.1448 0.1574 1.4105 0.0365 1.0483 0.0734
+#> 457: 92.1761 -5.8575 -2.1513 -4.2804 -0.9334 0.2257 0.0371 3.5041 1.0896 2.9144 0.1449 0.1574 1.4103 0.0365 1.0480 0.0733
+#> 458: 92.1763 -5.8569 -2.1512 -4.2813 -0.9334 0.2257 0.0370 3.5014 1.0901 2.9227 0.1449 0.1574 1.4102 0.0365 1.0476 0.0734
+#> 459: 92.1763 -5.8565 -2.1512 -4.2816 -0.9334 0.2256 0.0370 3.4991 1.0908 2.9248 0.1449 0.1573 1.4100 0.0365 1.0471 0.0734
+#> 460: 92.1764 -5.8557 -2.1513 -4.2818 -0.9333 0.2256 0.0370 3.4957 1.0915 2.9258 0.1449 0.1572 1.4097 0.0365 1.0466 0.0734
+#> 461: 92.1765 -5.8550 -2.1515 -4.2822 -0.9333 0.2255 0.0370 3.4923 1.0921 2.9296 0.1449 0.1571 1.4097 0.0365 1.0464 0.0734
+#> 462: 92.1764 -5.8546 -2.1517 -4.2824 -0.9333 0.2256 0.0370 3.4897 1.0925 2.9319 0.1448 0.1569 1.4093 0.0365 1.0463 0.0733
+#> 463: 92.1763 -5.8539 -2.1519 -4.2830 -0.9333 0.2256 0.0369 3.4863 1.0928 2.9373 0.1449 0.1568 1.4093 0.0366 1.0463 0.0733
+#> 464: 92.1763 -5.8532 -2.1520 -4.2833 -0.9333 0.2257 0.0370 3.4825 1.0933 2.9405 0.1448 0.1567 1.4093 0.0366 1.0462 0.0733
+#> 465: 92.1762 -5.8528 -2.1521 -4.2837 -0.9335 0.2257 0.0370 3.4795 1.0938 2.9433 0.1448 0.1567 1.4093 0.0366 1.0464 0.0733
+#> 466: 92.1762 -5.8530 -2.1523 -4.2840 -0.9336 0.2256 0.0370 3.4780 1.0943 2.9462 0.1448 0.1566 1.4089 0.0366 1.0466 0.0733
+#> 467: 92.1764 -5.8529 -2.1524 -4.2846 -0.9337 0.2256 0.0371 3.4751 1.0948 2.9506 0.1447 0.1565 1.4087 0.0366 1.0465 0.0733
+#> 468: 92.1765 -5.8531 -2.1525 -4.2849 -0.9337 0.2255 0.0371 3.4734 1.0952 2.9523 0.1447 0.1563 1.4087 0.0366 1.0465 0.0733
+#> 469: 92.1767 -5.8533 -2.1525 -4.2853 -0.9337 0.2254 0.0372 3.4754 1.0958 2.9540 0.1447 0.1561 1.4090 0.0366 1.0472 0.0733
+#> 470: 92.1767 -5.8536 -2.1525 -4.2858 -0.9338 0.2254 0.0373 3.4780 1.0965 2.9571 0.1448 0.1559 1.4094 0.0366 1.0478 0.0732
+#> 471: 92.1767 -5.8540 -2.1525 -4.2864 -0.9338 0.2254 0.0373 3.4812 1.0970 2.9606 0.1447 0.1558 1.4099 0.0366 1.0482 0.0732
+#> 472: 92.1766 -5.8547 -2.1526 -4.2871 -0.9339 0.2255 0.0373 3.4844 1.0975 2.9645 0.1446 0.1556 1.4101 0.0366 1.0482 0.0732
+#> 473: 92.1764 -5.8549 -2.1527 -4.2875 -0.9339 0.2255 0.0373 3.4848 1.0977 2.9672 0.1446 0.1554 1.4100 0.0366 1.0482 0.0732
+#> 474: 92.1762 -5.8553 -2.1528 -4.2880 -0.9338 0.2256 0.0373 3.4855 1.0979 2.9700 0.1445 0.1552 1.4104 0.0366 1.0484 0.0732
+#> 475: 92.1763 -5.8561 -2.1530 -4.2884 -0.9338 0.2256 0.0374 3.4885 1.0981 2.9726 0.1445 0.1549 1.4103 0.0366 1.0484 0.0731
+#> 476: 92.1763 -5.8564 -2.1530 -4.2885 -0.9339 0.2258 0.0374 3.4914 1.0983 2.9734 0.1444 0.1548 1.4106 0.0366 1.0484 0.0731
+#> 477: 92.1763 -5.8565 -2.1531 -4.2888 -0.9340 0.2259 0.0373 3.4941 1.0985 2.9755 0.1443 0.1546 1.4108 0.0366 1.0487 0.0731
+#> 478: 92.1763 -5.8576 -2.1532 -4.2889 -0.9340 0.2258 0.0373 3.4995 1.0987 2.9772 0.1442 0.1544 1.4111 0.0366 1.0490 0.0731
+#> 479: 92.1765 -5.8593 -2.1533 -4.2890 -0.9342 0.2259 0.0372 3.5086 1.0990 2.9787 0.1442 0.1544 1.4113 0.0366 1.0495 0.0731
+#> 480: 92.1766 -5.8613 -2.1535 -4.2892 -0.9342 0.2260 0.0372 3.5233 1.0991 2.9800 0.1442 0.1543 1.4116 0.0367 1.0496 0.0730
+#> 481: 92.1768 -5.8624 -2.1536 -4.2894 -0.9341 0.2260 0.0371 3.5309 1.0993 2.9820 0.1442 0.1542 1.4117 0.0367 1.0497 0.0730
+#> 482: 92.1766 -5.8634 -2.1537 -4.2896 -0.9341 0.2260 0.0371 3.5393 1.0995 2.9833 0.1443 0.1542 1.4116 0.0367 1.0496 0.0730
+#> 483: 92.1762 -5.8645 -2.1538 -4.2896 -0.9340 0.2260 0.0372 3.5472 1.0997 2.9840 0.1443 0.1542 1.4115 0.0367 1.0498 0.0730
+#> 484: 92.1757 -5.8648 -2.1538 -4.2896 -0.9340 0.2261 0.0373 3.5508 1.0998 2.9843 0.1445 0.1542 1.4115 0.0366 1.0498 0.0730
+#> 485: 92.1752 -5.8648 -2.1539 -4.2896 -0.9340 0.2262 0.0374 3.5516 1.1000 2.9846 0.1445 0.1542 1.4115 0.0366 1.0497 0.0730
+#> 486: 92.1747 -5.8649 -2.1539 -4.2897 -0.9340 0.2262 0.0375 3.5517 1.1003 2.9856 0.1446 0.1541 1.4113 0.0366 1.0498 0.0730
+#> 487: 92.1743 -5.8649 -2.1539 -4.2896 -0.9340 0.2262 0.0376 3.5502 1.1006 2.9856 0.1447 0.1539 1.4110 0.0367 1.0498 0.0730
+#> 488: 92.1739 -5.8645 -2.1540 -4.2893 -0.9340 0.2261 0.0377 3.5475 1.1008 2.9848 0.1447 0.1537 1.4106 0.0367 1.0497 0.0729
+#> 489: 92.1736 -5.8640 -2.1539 -4.2892 -0.9340 0.2260 0.0376 3.5445 1.1011 2.9844 0.1448 0.1536 1.4105 0.0367 1.0496 0.0729
+#> 490: 92.1736 -5.8631 -2.1539 -4.2889 -0.9340 0.2260 0.0376 3.5402 1.1014 2.9835 0.1448 0.1534 1.4103 0.0366 1.0496 0.0729
+#> 491: 92.1735 -5.8617 -2.1539 -4.2887 -0.9339 0.2260 0.0375 3.5343 1.1016 2.9825 0.1449 0.1532 1.4103 0.0366 1.0497 0.0729
+#> 492: 92.1736 -5.8609 -2.1539 -4.2884 -0.9339 0.2259 0.0375 3.5298 1.1017 2.9816 0.1449 0.1530 1.4101 0.0367 1.0499 0.0729
+#> 493: 92.1737 -5.8605 -2.1539 -4.2882 -0.9339 0.2260 0.0375 3.5266 1.1018 2.9807 0.1450 0.1529 1.4098 0.0367 1.0496 0.0729
+#> 494: 92.1739 -5.8609 -2.1539 -4.2881 -0.9340 0.2261 0.0375 3.5273 1.1018 2.9802 0.1450 0.1528 1.4097 0.0367 1.0495 0.0729
+#> 495: 92.1741 -5.8614 -2.1540 -4.2880 -0.9340 0.2262 0.0376 3.5290 1.1019 2.9797 0.1450 0.1526 1.4096 0.0367 1.0492 0.0729
+#> 496: 92.1742 -5.8623 -2.1540 -4.2879 -0.9341 0.2262 0.0376 3.5348 1.1020 2.9791 0.1449 0.1525 1.4096 0.0367 1.0491 0.0729
+#> 497: 92.1742 -5.8634 -2.1541 -4.2879 -0.9341 0.2264 0.0377 3.5402 1.1020 2.9789 0.1449 0.1524 1.4097 0.0367 1.0493 0.0729
+#> 498: 92.1744 -5.8637 -2.1543 -4.2879 -0.9341 0.2266 0.0377 3.5406 1.1019 2.9787 0.1449 0.1524 1.4096 0.0367 1.0496 0.0729
+#> 499: 92.1744 -5.8635 -2.1544 -4.2880 -0.9341 0.2268 0.0376 3.5400 1.1019 2.9789 0.1450 0.1523 1.4095 0.0367 1.0500 0.0728
+#> 500: 92.1744 -5.8628 -2.1545 -4.2882 -0.9341 0.2270 0.0377 3.5381 1.1020 2.9795 0.1450 0.1522 1.4096 0.0367 1.0503 0.0728
#> Calculating covariance matrix
#>
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>
#> ✔ done
#> Needed Covariates:
#> [1] "CMT"
#> Calculating residuals/tables
#> done
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#>
#> → calculate sensitivities
#>
#> → calculate ∂(f)/∂(η)
#>
#> → calculate ∂(R²)/∂(η)
#>
#> → finding duplicate expressions in inner model...
#>
#> → optimizing duplicate expressions in inner model...
#>
#> → finding duplicate expressions in EBE model...
#>
#> → optimizing duplicate expressions in EBE model...
#>
#> → compiling inner model...
#>
#> ✔ done
#> → finding duplicate expressions in FD model...
#>
#> → optimizing duplicate expressions in FD model...
#>
#> → compiling EBE model...
#>
#> ✔ done
#> → compiling events FD model...
#>
#> ✔ done
#> Needed Covariates:
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: using R matrix to calculate covariance, can check sandwich or S matrix with $covRS and $covS
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
#>
#> df AIC
-#> f_nlmixr_sfo_sfo_focei_const$nm 9 1082.4868
-#> f_nlmixr_fomc_sfo_focei_const$nm 11 814.4317
-#> f_nlmixr_dfop_sfo_focei_const$nm 13 866.0485
-#> f_nlmixr_fomc_sfo_saem_obs$nm 12 791.7256
-#> f_nlmixr_fomc_sfo_focei_obs$nm 12 794.5998
-#> f_nlmixr_dfop_sfo_saem_obs$nm 14 812.0463
-#> f_nlmixr_dfop_sfo_focei_obs$nm 14 846.9228
-#> f_nlmixr_fomc_sfo_focei_tc$nm 12 812.3585
-#> f_nlmixr_dfop_sfo_focei_tc$nm 14 842.3479
-#> f_nlmixr_fomc_sfo_saem_obs_tc$nm 14 817.1261
-#> f_nlmixr_fomc_sfo_focei_obs_tc$nm 14 787.4863
-#> f_nlmixr_dfop_sfo_saem_obs_tc$nm 16 858.3213
-#> f_nlmixr_dfop_sfo_focei_obs_tc$nm 16 811.0630
# Currently, FOMC-SFO with two-component error by variable fitted by focei gives the
+#> f_nlmixr_sfo_sfo_focei_const$nm 9 1082.4605
+#> f_nlmixr_fomc_sfo_focei_const$nm 11 814.4261
+#> f_nlmixr_dfop_sfo_focei_const$nm 13 870.2659
+#> f_nlmixr_fomc_sfo_saem_obs$nm 12 788.8373
+#> f_nlmixr_fomc_sfo_focei_obs$nm 12 794.5194
+#> f_nlmixr_dfop_sfo_saem_obs$nm 14 815.0797
+#> f_nlmixr_dfop_sfo_focei_obs$nm 14 834.8474
+#> f_nlmixr_fomc_sfo_focei_tc$nm 12 812.3296
+#> f_nlmixr_dfop_sfo_focei_tc$nm 14 819.4103
+#> f_nlmixr_fomc_sfo_saem_obs_tc$nm 14 814.4248
+#> f_nlmixr_fomc_sfo_focei_obs_tc$nm 14 787.4355
+#> f_nlmixr_dfop_sfo_saem_obs_tc$nm 16 828.5143
+#> f_nlmixr_dfop_sfo_focei_obs_tc$nm 16 811.1191
#> nlmixr version used for fitting: 2.0.5
#> mkin version used for pre-fitting: 1.1.0
-#> R version used for fitting: 4.1.1
-#> Date of fit: Tue Oct 5 17:25:02 2021
-#> Date of summary: Tue Oct 5 17:26:23 2021
+#> R version used for fitting: 4.1.2
+#> Date of fit: Tue Jan 11 19:40:06 2022
+#> Date of summary: Tue Jan 11 19:41:47 2022
#>
#> Equations:
#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
@@ -9635,7 +12454,7 @@ obtained by fitting the same model to a list of datasets using
# }
+#> parent 11.46 127.3 38.31
+#> A1 385.05 1279.1 NA
# }