diff options
199 files changed, 15647 insertions, 11864 deletions
diff --git a/.Rbuildignore b/.Rbuildignore index 208d9d46..24632401 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,13 +1,14 @@ +^_pkgdown\.yml$ +^\.travis\.yml$ +^codemeta\.json$ +^docs$ +^log$ +^mkin.Rcheck$ ^GNUmakefile$ -^build.log$ -^check.log$ -^check_dev.log$ -^test.log$ -^test_dev.log$ -^tests_slow.log$ -^test.R$ ^README.html$ -^mkin.Rcheck +^test.R$ +^mkin_.*\.tar\.gz +^mkin.tar$ ^vignettes/.build.timestamp$ ^vignettes/.*_cache$ ^vignettes/.*cache$ @@ -28,10 +29,3 @@ ^vignettes/mkin_benchmarks.rda$ ^vignettes/web_only/.build.timestamp$ ^vignettes/web_only/mkin_benchmarks.rda$ -^mkin_.*\.tar\.gz -^mkin.tar$ -^docs$ -^_pkgdown\.yml$ -^\.travis\.yml$ -^CRAN-RELEASE$ -^cran-comments.md$ diff --git a/.travis.yml b/.travis.yml index 77efef09..33070708 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,23 +1,39 @@ -language: r -r: - - 4.1.2 - - devel -addons: - apt: - packages: - - gcc - - libgit2-dev - - libmpfr-dev -cache: packages -repos: - CRAN: https://cloud.r-project.org -r_packages: - - devtools - - covr - - vdiffr +# Run CI for R using https://eddelbuettel.github.io/r-ci/ + +language: c +sudo: required +dist: focal + +jobs: + include: + - name: linux + os: linux + +env: + global: + - USE_BSPM="true" + - NOT_CRAN="true" + +before_install: + - curl -OLs https://eddelbuettel.github.io/r-ci/run.sh + - chmod 0755 run.sh + - ./run.sh bootstrap + +install: + - ./run.sh install_r nlme + - ./run.sh install_all + - ./run.sh install_github jranke/saemixextension@installable_dev_version + script: - - R CMD build . - - R CMD check --no-tests mkin_*.tar.gz - - Rscript -e 'devtools::test()' + - ./run.sh run_tests + +after_failure: + - ./run.sh dump_logs + after_success: - - travis_wait Rscript -e 'covr::codecov()' + - travis_wait ./run.sh coverage + +notifications: + email: + on_success: change + on_failure: change diff --git a/DESCRIPTION b/DESCRIPTION index 569fd2c7..d49c6b69 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,8 +1,8 @@ Package: mkin Type: Package Title: Kinetic Evaluation of Chemical Degradation Data -Version: 1.1.1 -Date: 2022-07-08 +Version: 1.1.2 +Date: 2022-09-16 Authors@R: c( person("Johannes", "Ranke", role = c("aut", "cre", "cph"), email = "johannes.ranke@jrwb.de", @@ -22,9 +22,9 @@ Description: Calculation routines based on the FOCUS Kinetics Report (2006, Ranke et al. (2021) <doi:10.3390/environments8080071>. Please note that no warranty is implied for correctness of results or fitness for a particular purpose. -Depends: R (>= 2.15.1), parallel -Imports: stats, graphics, methods, deSolve, R6, inline (>= 0.3.19), numDeriv, - lmtest, pkgbuild, nlme (>= 3.1-151), purrr, saemix (>= 3.0) +Depends: R (>= 2.15.1), +Imports: stats, graphics, methods, parallel, deSolve, R6, inline (>= 0.3.19), + numDeriv, lmtest, pkgbuild, nlme (>= 3.1-151), saemix (>= 3.1), rlang, vctrs Suggests: knitr, rbenchmark, tikzDevice, testthat, rmarkdown, covr, vdiffr, benchmarkme, tibble, stats4 License: GPL @@ -36,4 +36,4 @@ VignetteBuilder: knitr BugReports: https://github.com/jranke/mkin/issues/ URL: https://pkgdown.jrwb.de/mkin/ Roxygen: list(markdown = TRUE) -RoxygenNote: 7.2.0 +RoxygenNote: 7.2.1 diff --git a/GNUmakefile b/GNUmakefile index 569e10ea..114f7eef 100644 --- a/GNUmakefile +++ b/GNUmakefile @@ -30,8 +30,7 @@ pkgfiles = \ NEWS.md \ R/* \ tests/* \ - tests/testthat* \ - TODO + tests/testthat* all: build @@ -41,7 +40,7 @@ $(TGZ): $(pkgfiles) vignettes $(RM) -r vignettes/*.R $(RM) -r vignettes/web_only/*.R $(RM) Rplots.pdf - "$(RBIN)/R" CMD build . 2>&1 | tee build.log + "$(RBIN)/R" CMD build . 2>&1 | tee log/build.log roxygen: "$(RBIN)/Rscript" -e 'devtools::document()' @@ -64,10 +63,10 @@ quickinstall: build-no-vignettes "$(RBIN)/R" CMD INSTALL $(TGZVNR) check: roxygen build - _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(RBIN)/R" CMD check --as-cran --no-tests $(TGZ) 2>&1 | tee check.log + _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(RBIN)/R" CMD check --as-cran --no-tests $(TGZ) 2>&1 | tee log/check.log devcheck: roxygen build - _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(RDEVBIN)/R" CMD check --as-cran --no-tests $(TGZ) 2>&1 | tee check_dev.log + _R_CHECK_CRAN_INCOMING_REMOTE_=false "$(RDEVBIN)/R" CMD check --as-cran --no-tests $(TGZ) 2>&1 | tee log/check_dev.log quickcheck: roxygen build-no-vignettes mv $(TGZVNR) $(TGZ) @@ -82,16 +81,16 @@ clean: $(RM) Rplots.pdf test: install - "$(RBIN)/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee test.log - sed -i -e "s/.*\r.*\r//" test.log + "$(RBIN)/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee log/test.log + sed -i -e "s/.*\r.*\r//" log/test.log devtest: devinstall - "$(RDEVBIN)/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee test_dev.log - sed -i -e "s/\r.*\r//" test_dev.log + "$(RDEVBIN)/Rscript" -e 'options(cli.dynamic = TRUE); devtools::test()' 2>&1 | tee log/test_dev.log + sed -i -e "s/\r.*\r//" log/test_dev.log slowtests: install - NOT_CRAN=true "$(RBIN)/Rscript" -e 'cli.dynamic = TRUE); library(mkin); testthat::test_dir("tests/testthat/slow")' 2>&1 | tee tests_slow.log - sed -i -e "s/\r.*\r//" tests_slow.log + NOT_CRAN=true "$(RBIN)/Rscript" -e 'cli.dynamic = TRUE); library(mkin); testthat::test_dir("tests/testthat/slow")' 2>&1 | tee log/tests_slow.log + sed -i -e "s/\r.*\r//" log/tests_slow.log testcheck: roxygen test check @@ -106,7 +105,7 @@ vignettes: vignettes/mkin.html vignettes/FOCUS_D.html vignettes/FOCUS_L.html vig vignettes/web_only/%.html: vignettes/references.bib vignettes/web_only/%.rmd "$(RBIN)/Rscript" -e "tools::buildVignette(file = 'vignettes/web_only/$*.rmd', dir = 'vignettes/web_only', keep='mkin_benchmarks.rda')" -articles: vignettes/web_only/FOCUS_Z.html vignettes/web_only/compiled_models.html vignettes/web_only/benchmarks.html vignettes/web_only/dimethenamid_2018.html +articles: vignettes/web_only/FOCUS_Z.html vignettes/web_only/compiled_models.html vignettes/web_only/benchmarks.html vignettes/web_only/dimethenamid_2018.html vignettes/web_only/multistart.html pd: roxygen "$(RBIN)/Rscript" -e "pkgdown::build_site(run_dont_run = TRUE, lazy = TRUE)" @@ -1,48 +1,82 @@ # Generated by roxygen2: do not edit by hand +S3method("[",mhmkin) S3method("[",mmkin) +S3method(AIC,mhmkin) S3method(AIC,mmkin) +S3method(BIC,mhmkin) S3method(BIC,mmkin) +S3method(anova,saem.mmkin) +S3method(aw,mixed.mmkin) S3method(aw,mkinfit) S3method(aw,mmkin) +S3method(aw,multistart) +S3method(best,default) S3method(confint,mkinfit) S3method(f_time_norm_focus,mkindsg) S3method(f_time_norm_focus,numeric) +S3method(illparms,mhmkin) +S3method(illparms,mkinfit) +S3method(illparms,mmkin) +S3method(illparms,saem.mmkin) S3method(intervals,saem.mmkin) S3method(loftest,mkinfit) S3method(logLik,mkinfit) +S3method(logLik,saem.mmkin) S3method(lrtest,mkinfit) S3method(lrtest,mmkin) +S3method(mhmkin,list) S3method(mixed,mmkin) S3method(mkinpredict,mkinfit) S3method(mkinpredict,mkinmod) +S3method(multistart,saem.mmkin) S3method(nlme,mmkin) S3method(nobs,mkinfit) S3method(parms,mkinfit) S3method(parms,mmkin) +S3method(parms,multistart) +S3method(parms,saem.mmkin) +S3method(parplot,multistart.saem.mmkin) S3method(plot,mixed.mmkin) S3method(plot,mkinfit) S3method(plot,mmkin) S3method(plot,nafta) +S3method(print,illparms.mhmkin) +S3method(print,illparms.mmkin) +S3method(print,mhmkin) S3method(print,mixed.mmkin) S3method(print,mkinds) S3method(print,mkindsg) S3method(print,mkinmod) S3method(print,mmkin) +S3method(print,multistart) S3method(print,nafta) S3method(print,nlme.mmkin) S3method(print,saem.mmkin) +S3method(print,status.mhmkin) +S3method(print,status.mmkin) +S3method(print,status.multistart) S3method(print,summary.mkinfit) +S3method(print,summary.mmkin) S3method(print,summary.nlme.mmkin) S3method(print,summary.saem.mmkin) S3method(residuals,mkinfit) S3method(saem,mmkin) +S3method(status,mhmkin) +S3method(status,mmkin) +S3method(status,multistart) +S3method(status,multistart.saem.mmkin) S3method(summary,mkinfit) +S3method(summary,mmkin) S3method(summary,nlme.mmkin) S3method(summary,saem.mmkin) +S3method(update,mhmkin) S3method(update,mkinfit) S3method(update,mmkin) +S3method(update,multistart) S3method(update,nlme.mmkin) +S3method(update,saem.mmkin) +S3method(which.best,default) export(CAKE_export) export(DFOP.solution) export(FOMC.solution) @@ -53,13 +87,16 @@ export(SFORB.solution) export(add_err) export(aw) export(backtransform_odeparms) +export(best) export(create_deg_func) export(endpoints) export(f_time_norm_focus) export(get_deg_func) +export(illparms) export(ilr) export(intervals) export(invilr) +export(llhist) export(loftest) export(logistic.solution) export(lrtest) @@ -69,6 +106,7 @@ export(max_twa_hs) export(max_twa_parent) export(max_twa_sfo) export(mean_degparms) +export(mhmkin) export(mixed) export(mkin_long_to_wide) export(mkin_wide_to_long) @@ -84,34 +122,42 @@ export(mkinpredict) export(mkinresplot) export(mkinsub) export(mmkin) +export(multistart) export(nafta) export(nlme) export(nlme_data) export(nlme_function) export(parms) +export(parplot) export(plot_err) export(plot_res) export(plot_sep) export(saem) export(saemix_data) export(saemix_model) +export(set_nd_nq) +export(set_nd_nq_focus) export(sigma_twocomp) +export(status) export(transform_odeparms) +export(which.best) import(deSolve) import(graphics) import(nlme) importFrom(R6,R6Class) importFrom(grDevices,dev.cur) importFrom(lmtest,lrtest) +importFrom(methods,is) importFrom(methods,signature) importFrom(nlme,intervals) importFrom(parallel,detectCores) importFrom(parallel,mclapply) importFrom(parallel,parLapply) -importFrom(purrr,map_dfr) +importFrom(rlang,"!!!") importFrom(stats,AIC) importFrom(stats,BIC) importFrom(stats,aggregate) +importFrom(stats,anova) importFrom(stats,as.formula) importFrom(stats,coef) importFrom(stats,coefficients) @@ -120,10 +166,12 @@ importFrom(stats,dist) importFrom(stats,dnorm) importFrom(stats,lm) importFrom(stats,logLik) +importFrom(stats,median) importFrom(stats,na.fail) importFrom(stats,nlminb) importFrom(stats,nobs) importFrom(stats,optimize) +importFrom(stats,pchisq) importFrom(stats,plogis) importFrom(stats,predict) importFrom(stats,pt) @@ -135,8 +183,10 @@ importFrom(stats,qt) importFrom(stats,residuals) importFrom(stats,rnorm) importFrom(stats,shapiro.test) +importFrom(stats,terms) importFrom(stats,update) importFrom(stats,vcov) +importFrom(utils,capture.output) importFrom(utils,getFromNamespace) importFrom(utils,packageVersion) importFrom(utils,write.table) @@ -1,4 +1,20 @@ -# mkin 1.1.1 +# mkin 1.1.2 + +- 'R/multistart.R': New method for testing multiple start parameters for hierarchical model fits, with diagnostic plotting functions 'llhist' and 'parplot'. + +- 'R/mhmkin.R': New method for performing multiple hierarchical mkin fits in one function call, optionally in parallel. + +- 'R/saem.R': Implement and test saemix transformations for FOMC and HS. Also, error out if saemix transformations are requested but not supported. + +- 'R/saem.R': 'logLik' and 'update' methods for 'saem.mmkin' objects. + +- 'R/status.R': New generic to show status information for fit array objects with methods for 'mmkin' and 'mhmkin' objects. + +- 'R/illparms.R': New generic to show ill-defined parameters with methods for 'mkinfit', 'mmkin', 'saem.mmkin' and 'mhmkin' objects. + +- 'R/summary.mmkin.R': Summary method for mmkin objects. + +# mkin 1.1.1 (2022-07-12) - 'R/{mkinmod,mkinpredict}.R: Store DLL information in mkinmod objects and use that information in mkinpredict to avoid a performance regression brought by a bugfix in R 4.2.x. Thanks to Tomas Kalibera for his analysis of the problem on the r-package-devel list and his suggestion on how to fix it. diff --git a/R/anova.saem.mmkin.R b/R/anova.saem.mmkin.R new file mode 100644 index 00000000..9937a919 --- /dev/null +++ b/R/anova.saem.mmkin.R @@ -0,0 +1,106 @@ +#' Anova method for saem.mmkin objects +#' +#' Generate an anova object. The method to calculate the BIC is that from +#' the saemix package. As in other prominent anova methods, models are sorted +## by likelihood, and the test is relative to the model on the previous line. +#' +#' @param object An [saem.mmkin] object +#' @param ... further such objects +#' @param method Method for likelihood calculation: "is" (importance sampling), +#' "lin" (linear approximation), or "gq" (Gaussian quadrature). Passed +#' to [saemix::logLik.SaemixObject] +#' @param test Should a likelihood ratio test be performed? If TRUE, +#' the alternative models are tested against the first model. Should +#' only be done for nested models. +#' @param model.names Optional character vector of model names +#' @importFrom stats anova logLik update pchisq terms +#' @importFrom methods is +#' @importFrom utils capture.output +#' @export +#' @return an "anova" data frame; the traditional (S3) result of anova() +anova.saem.mmkin <- function(object, ..., + method = c("is", "lin", "gq"), test = FALSE, model.names = NULL) +{ + # The following code is heavily inspired by anova.lmer in the lme4 package + mCall <- match.call(expand.dots = TRUE) + dots <- list(...) + method <- match.arg(method) + + is_model <- sapply(dots, is, "saem.mmkin") + if (any(is_model)) { + mods <- c(list(object), dots[is_model]) + + # Ensure same data, ignoring covariates + same_data <- sapply(dots[is_model], function(x) { + identical(object$data[c("ds", "name", "time", "value")], + x$data[c("ds", "name", "time", "value")]) + }) + if (!all(same_data)) { + stop(sum(!same_data), " objects have not been fitted to the same data") + } + + if (is.null(model.names)) + model.names <- vapply(as.list(mCall)[c(FALSE, TRUE, is_model)], deparse1, "") + + # Sanitize model names + if (length(model.names) != length(mods)) + stop("Model names vector and model list have different lengths") + + if (any(duplicated(model.names))) + stop("Duplicate model names are not allowed") + + if (max(nchar(model.names)) > 200) { + warning("Model names longer than 200 characters, assigning generic names") + model.names <- paste0("MODEL",seq_along(model.names)) + } + names(mods) <- model.names + + llks <- lapply(model.names, function(x) { + llk <- try(logLik(mods[[x]], method = method)) + if (inherits(llk, "try-error")) + stop("Could not obtain log likelihood with '", method, "' method for ", x) + return(llk) + }) + + # Order models by increasing degrees of freedom: + npar <- vapply(llks, attr, FUN.VALUE=numeric(1), "df") + ii <- order(npar) + mods <- mods[ii] + llks <- llks[ii] + npar <- npar[ii] + + # Describe data for the header, as in summary.saem.mmkin + header <- paste("Data:", nrow(object$data), "observations of", + length(unique(object$data$name)), "variable(s) grouped in", + length(unique(object$data$ds)), "datasets\n") + + # Calculate statistics + llk <- unlist(llks) + chisq <- 2 * pmax(0, c(NA, diff(llk))) + dfChisq <- c(NA, diff(npar)) + + bic <- function(x, method) { + BIC(x$so, method = method) + } + val <- data.frame( + npar = npar, + AIC = sapply(llks, AIC), + BIC = sapply(mods, bic, method = method), # We use the saemix method here + Lik = llk, + row.names = names(mods), check.names = FALSE) + + if (test) { + testval <- data.frame( + Chisq = chisq, + Df = dfChisq, + "Pr(>Chisq)" = ifelse(dfChisq == 0, NA, + pchisq(chisq, dfChisq, lower.tail = FALSE)), + row.names = names(mods), check.names = FALSE) + val <- cbind(val, testval) + } + class(val) <- c("anova", class(val)) + structure(val, heading = c(header)) + } else { + stop("Currently, no anova method is implemented for the case of a single saem.mmkin object") + } +} @@ -30,6 +30,14 @@ #' @export aw <- function(object, ...) UseMethod("aw") +.aw <- function(all_objects) { + AIC_all <- sapply(all_objects, AIC) + delta_i <- AIC_all - min(AIC_all) + denom <- sum(exp(-delta_i/2)) + w_i <- exp(-delta_i/2) / denom + return(w_i) +} + #' @export #' @rdname aw aw.mkinfit <- function(object, ...) { @@ -43,11 +51,7 @@ aw.mkinfit <- function(object, ...) { } } all_objects <- list(object, ...) - AIC_all <- sapply(all_objects, AIC) - delta_i <- AIC_all - min(AIC_all) - denom <- sum(exp(-delta_i/2)) - w_i <- exp(-delta_i/2) / denom - return(w_i) + .aw(all_objects) } #' @export @@ -56,3 +60,25 @@ aw.mmkin <- function(object, ...) { if (ncol(object) > 1) stop("Please supply an mmkin column object") do.call(aw, object) } + +#' @export +#' @rdname aw +aw.mixed.mmkin <- function(object, ...) { + oo <- list(...) + data_object <- object$data[c("ds", "name", "time", "value")] + for (i in seq_along(oo)) { + if (!inherits(oo[[i]], "mixed.mmkin")) stop("Please supply objects inheriting from mixed.mmkin") + data_other_object <- oo[[i]]$data[c("ds", "name", "time", "value")] + if (!identical(data_object, data_other_object)) { + stop("It seems that the mixed.mmkin objects have not all been fitted to the same data") + } + } + all_objects <- list(object, ...) + .aw(all_objects) +} + +#' @export +#' @rdname aw +aw.multistart <- function(object, ...) { + do.call(aw, object) +} diff --git a/R/illparms.R b/R/illparms.R new file mode 100644 index 00000000..931d8f05 --- /dev/null +++ b/R/illparms.R @@ -0,0 +1,137 @@ +#' Method to get the names of ill-defined parameters +#' +#' The method for generalised nonlinear regression fits as obtained +#' with [mkinfit] and [mmkin] checks if the degradation parameters +#' pass the Wald test (in degradation kinetics often simply called t-test) for +#' significant difference from zero. For this test, the parameterisation +#' without parameter transformations is used. +#' +#' The method for hierarchical model fits, also known as nonlinear +#' mixed-effects model fits as obtained with [saem] and [mhmkin] +#' checks if any of the confidence intervals for the random +#' effects expressed as standard deviations include zero, and if +#' the confidence intervals for the error model parameters include +#' zero. +#' +#' @param object The object to investigate +#' @param x The object to be printed +#' @param conf.level The confidence level for checking p values +#' @param \dots For potential future extensions +#' @param random For hierarchical fits, should random effects be tested? +#' @param errmod For hierarchical fits, should error model parameters be +#' tested? +#' @return For [mkinfit] or [saem] objects, a character vector of parameter +#' names. For [mmkin] or [mhmkin] objects, a matrix like object of class +#' 'illparms.mmkin' or 'illparms.mhmkin'. The latter objects have a suitable +#' printing method. +#' @export +illparms <- function(object, ...) +{ + UseMethod("illparms", object) +} + +#' @rdname illparms +#' @export +#' @examples +#' fit <- mkinfit("FOMC", FOCUS_2006_A, quiet = TRUE) +#' illparms(fit) +illparms.mkinfit <- function(object, conf.level = 0.95, ...) { + p_values <- suppressWarnings(summary(object)$bpar[, "Pr(>t)"]) + na <- is.na(p_values) + failed <- p_values > 1 - conf.level + names(parms(object))[na | failed] +} + +#' @rdname illparms +#' @export +#' @examples +#' \dontrun{ +#' fits <- mmkin( +#' c("SFO", "FOMC"), +#' list("FOCUS A" = FOCUS_2006_A, +#' "FOCUS C" = FOCUS_2006_C), +#' quiet = TRUE) +#' illparms(fits) +#' } +illparms.mmkin <- function(object, conf.level = 0.95, ...) { + result <- lapply(object, + function(fit) { + if (inherits(fit, "try-error")) return("E") + ill <- illparms(fit, conf.level = conf.level) + if (length(ill) > 0) { + return(paste(ill, collapse = ", ")) + } else { + return("") + } + }) + result <- unlist(result) + dim(result) <- dim(object) + dimnames(result) <- dimnames(object) + class(result) <- "illparms.mmkin" + return(result) +} + +#' @rdname illparms +#' @export +print.illparms.mmkin <- function(x, ...) { + class(x) <- NULL + print(x, quote = FALSE) +} + +#' @rdname illparms +#' @export +illparms.saem.mmkin <- function(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) { + if (inherits(object, "try-error")) { + return(NA) + } else { + ints <- intervals(object, conf.level = conf.level) + failed <- NULL + if (random) { + failed_random <- ints$random[, "lower"] < 0 + failed <- c(failed, names(which(failed_random))) + } + if (errmod) { + failed_errmod <- ints$errmod[, "lower"] < 0 & ints$errmod[, "est."] > 0 + failed <- c(failed, names(which(failed_errmod))) + } + } + return(failed) +} + +#' @rdname illparms +#' @export +illparms.mhmkin <- function(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) { + if (inherits(object[[1]], "saem.mmkin")) { + check_failed <- function(x) if (inherits(x$so, "try-error")) TRUE else FALSE + } + result <- lapply(object, + function(fit) { + if (check_failed(fit)) { + return("E") + } else { + if (!is.null(fit$FIM_failed) && + "random effects and error model parameters" %in% fit$FIM_failed) { + return("NA") + } else { + ill <- illparms(fit, conf.level = conf.level, random = random, errmod = errmod) + if (length(ill) > 0) { + return(paste(ill, collapse = ", ")) + } else { + return("") + } + } + } + }) + result <- unlist(result) + dim(result) <- dim(object) + dimnames(result) <- dimnames(object) + class(result) <- "illparms.mhmkin" + return(result) +} + +#' @rdname illparms +#' @export +print.illparms.mhmkin <- function(x, ...) { + class(x) <- NULL + print(x, quote = FALSE) +} diff --git a/R/intervals.R b/R/intervals.R index 258eb4ad..705ef6eb 100644 --- a/R/intervals.R +++ b/R/intervals.R @@ -77,8 +77,9 @@ intervals.saem.mmkin <- function(object, level = 0.95, backtransform = TRUE, ... attr(confint_ret, "label") <- "Fixed effects:" # Random effects - ranef_ret <- as.matrix(conf.int[paste0("SD.", pnames), c("lower", "est.", "upper")]) - rownames(ranef_ret) <- paste0(gsub("SD\\.", "sd(", rownames(ranef_ret)), ")") + sdnames <- intersect(rownames(conf.int), paste("SD", pnames, sep = ".")) + ranef_ret <- as.matrix(conf.int[sdnames, c("lower", "est.", "upper")]) + rownames(ranef_ret) <- paste0(gsub("SD\\.", "sd(", sdnames), ")") attr(ranef_ret, "label") <- "Random effects:" diff --git a/R/llhist.R b/R/llhist.R new file mode 100644 index 00000000..e158495d --- /dev/null +++ b/R/llhist.R @@ -0,0 +1,43 @@ +#' Plot the distribution of log likelihoods from multistart objects +#' +#' Produces a histogram of log-likelihoods. In addition, the likelihood of the +#' original fit is shown as a red vertical line. +#' +#' @param object The [multistart] object +#' @param breaks Passed to [hist] +#' @param lpos Positioning of the legend. +#' @param main Title of the plot +#' @param \dots Passed to [hist] +#' @seealso [multistart] +#' @export +llhist <- function(object, breaks = "Sturges", lpos = "topleft", main = "", + ...) +{ + oldpar <- par(no.readonly = TRUE) + on.exit(par(oldpar, no.readonly = TRUE)) + + if (inherits(object, "multistart.saem.mmkin")) { + llfunc <- function(object) { + if (inherits(object$so, "try-error")) return(NA) + else return(logLik(object$so)) + } + } else { + stop("llhist is only implemented for multistart.saem.mmkin objects") + } + + ll_orig <- logLik(attr(object, "orig")) + ll <- stats::na.omit(sapply(object, llfunc)) + + par(las = 1) + h <- hist(ll, freq = TRUE, + xlab = "", main = main, + ylab = "Frequency of log likelihoods", breaks = breaks, ...) + + freq_factor <- h$counts[1] / h$density[1] + + abline(v = ll_orig, col = 2) + + legend(lpos, inset = c(0.05, 0.05), bty = "n", + lty = 1, col = c(2), + legend = "original fit") +} diff --git a/R/mhmkin.R b/R/mhmkin.R new file mode 100644 index 00000000..7f3ff9fa --- /dev/null +++ b/R/mhmkin.R @@ -0,0 +1,192 @@ +#' Fit nonlinear mixed-effects models built from one or more kinetic +#' degradation models and one or more error models +#' +#' The name of the methods expresses that (**m**ultiple) **h**ierarchichal +#' (also known as multilevel) **m**ulticompartment **kin**etic models are +#' fitted. Our kinetic models are nonlinear, so we can use various nonlinear +#' mixed-effects model fitting functions. +#' +#' @param objects A list of [mmkin] objects containing fits of the same +#' degradation models to the same data, but using different error models. +#' @param backend The backend to be used for fitting. Currently, only saemix is +#' supported +#' @param algorithm The algorithm to be used for fitting (currently not used) +#' @param \dots Further arguments that will be passed to the nonlinear mixed-effects +#' model fitting function. +#' @param cores The number of cores to be used for multicore processing. This +#' is only used when the \code{cluster} argument is \code{NULL}. On Windows +#' machines, cores > 1 is not supported, you need to use the \code{cluster} +#' argument to use multiple logical processors. Per default, all cores detected +#' by [parallel::detectCores()] are used, except on Windows where the default +#' is 1. +#' @param cluster A cluster as returned by [makeCluster] to be used for +#' parallel execution. +#' @importFrom parallel mclapply parLapply detectCores +#' @return A two-dimensional [array] of fit objects and/or try-errors that can +#' be indexed using the degradation model names for the first index (row index) +#' and the error model names for the second index (column index), with class +#' attribute 'mhmkin'. +#' @author Johannes Ranke +#' @seealso \code{\link{[.mhmkin}} for subsetting [mhmkin] objects +#' @export +mhmkin <- function(objects, backend = "saemix", algorithm = "saem", ...) { + UseMethod("mhmkin") +} + +#' @export +#' @rdname mhmkin +mhmkin.list <- function(objects, backend = "saemix", + ..., + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), cluster = NULL) +{ + call <- match.call() + dot_args <- list(...) + backend_function <- switch(backend, + saemix = "saem" + ) + + deg_models <- lapply(objects[[1]][, 1], function(x) x$mkinmod) + names(deg_models) <- dimnames(objects[[1]])$model + n.deg <- length(deg_models) + + ds <- lapply(objects[[1]][1, ], function(x) x$data) + + for (other in objects[-1]) { + # Check if the degradation models in all objects are the same + for (deg_model_name in names(deg_models)) { + if (!all.equal(other[[deg_model_name, 1]]$mkinmod$spec, + deg_models[[deg_model_name]]$spec)) + { + stop("The mmkin objects have to be based on the same degradation models") + } + } + # Check if they have been fitted to the same dataset + other_object_ds <- lapply(other[1, ], function(x) x$data) + for (i in 1:length(ds)) { + if (!all.equal(ds[[i]][c("time", "variable", "observed")], + other_object_ds[[i]][c("time", "variable", "observed")])) + { + stop("The mmkin objects have to be fitted to the same datasets") + } + } + } + + n.o <- length(objects) + + error_models = sapply(objects, function(x) x[[1]]$err_mod) + n.e <- length(error_models) + + n.fits <- n.deg * n.e + fit_indices <- matrix(1:n.fits, ncol = n.e) + dimnames(fit_indices) <- list(degradation = names(deg_models), + error = error_models) + + fit_function <- function(fit_index) { + w <- which(fit_indices == fit_index, arr.ind = TRUE) + deg_index <- w[1] + error_index <- w[2] + mmkin_row <- objects[[error_index]][deg_index, ] + res <- try(do.call(backend_function, args = c(list(mmkin_row), dot_args))) + return(res) + } + + fit_time <- system.time({ + if (is.null(cluster)) { + results <- parallel::mclapply(as.list(1:n.fits), fit_function, + mc.cores = cores, mc.preschedule = FALSE) + } else { + results <- parallel::parLapply(cluster, as.list(1:n.fits), fit_function) + } + }) + + attributes(results) <- attributes(fit_indices) + attr(results, "call") <- call + attr(results, "time") <- fit_time + class(results) <- "mhmkin" + return(results) +} + +#' Subsetting method for mhmkin objects +#' +#' @param x An [mhmkin] object. +#' @param i Row index selecting the fits for specific models +#' @param j Column index selecting the fits to specific datasets +#' @param drop If FALSE, the method always returns an mhmkin object, otherwise +#' either a list of fit objects or a single fit object. +#' @return An object of class \code{\link{mhmkin}}. +#' @rdname mhmkin +#' @export +`[.mhmkin` <- function(x, i, j, ..., drop = FALSE) { + class(x) <- NULL + x_sub <- x[i, j, drop = drop] + + if (!drop) { + class(x_sub) <- "mhmkin" + } + return(x_sub) +} + +#' Print method for mhmkin objects +#' +#' @rdname mhmkin +#' @export +print.mhmkin <- function(x, ...) { + cat("<mhmkin> object\n") + cat("Status of individual fits:\n\n") + print(status(x)) +} + +#' @export +AIC.mhmkin <- function(object, ..., k = 2) { + if (inherits(object[[1]], "saem.mmkin")) { + check_failed <- function(x) if (inherits(x$so, "try-error")) TRUE else FALSE + } + res <- sapply(object, function(x) { + if (check_failed(x)) return(NA) + else return(AIC(x$so, k = k)) + }) + dim(res) <- dim(object) + dimnames(res) <- dimnames(object) + return(res) +} + +#' @export +BIC.mhmkin <- function(object, ...) { + if (inherits(object[[1]], "saem.mmkin")) { + check_failed <- function(x) if (inherits(x$so, "try-error")) TRUE else FALSE + } + res <- sapply(object, function(x) { + if (check_failed(x)) return(NA) + else return(BIC(x$so)) + }) + dim(res) <- dim(object) + dimnames(res) <- dimnames(object) + return(res) +} + +#' @export +update.mhmkin <- function(object, ..., evaluate = TRUE) { + call <- attr(object, "call") + # For some reason we get mhkin.list in call[[1]] when using mhmkin from the + # loaded package so we need to fix this so we do not have to export + # mhmkin.list in addition to the S3 method mhmkin + call[[1]] <- mhmkin + + update_arguments <- match.call(expand.dots = FALSE)$... + + if (length(update_arguments) > 0) { + update_arguments_in_call <- !is.na(match(names(update_arguments), names(call))) + } + + for (a in names(update_arguments)[update_arguments_in_call]) { + call[[a]] <- update_arguments[[a]] + } + + update_arguments_not_in_call <- !update_arguments_in_call + if(any(update_arguments_not_in_call)) { + call <- c(as.list(call), update_arguments[update_arguments_not_in_call]) + call <- as.call(call) + } + if(evaluate) eval(call, parent.frame()) + else call +} diff --git a/R/mixed.mmkin.R b/R/mixed.mmkin.R index 682a9a34..fd6d975f 100644 --- a/R/mixed.mmkin.R +++ b/R/mixed.mmkin.R @@ -1,5 +1,6 @@ #' Create a mixed effects model from an mmkin row object #' +#' @importFrom rlang !!! #' @param object An [mmkin] row object #' @param method The method to be used #' @param \dots Currently not used @@ -65,7 +66,7 @@ mixed.mmkin <- function(object, method = c("none"), ...) { function(x) x$data[c("variable", "time", "observed", "predicted", "residual")]) names(ds_list) <- ds_names - res$data <- purrr::map_dfr(ds_list, function(x) x, .id = "ds") + res$data <- vctrs::vec_rbind(!!!ds_list, .names_to = "ds") names(res$data)[1:4] <- c("ds", "name", "time", "value") res$data$name <- as.character(res$data$name) res$data$ds <- ordered(res$data$ds, levels = unique(res$data$ds)) diff --git a/R/mkinfit.R b/R/mkinfit.R index 1c2f8b5e..693778fd 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -844,8 +844,13 @@ mkinfit <- function(mkinmod, observed, } } + dim_hessian <- length(c(degparms, errparms)) + fit$hessian <- try(numDeriv::hessian(cost_function, c(degparms, errparms), OLS = FALSE, update_data = FALSE), silent = TRUE) + if (inherits(fit$hessian, "try-error")) { + fit$hessian <- matrix(NA, nrow = dim_hessian, ncol = dim_hessian) + } dimnames(fit$hessian) <- list(names(c(degparms, errparms)), names(c(degparms, errparms))) @@ -858,7 +863,9 @@ mkinfit <- function(mkinmod, observed, fit$hessian_notrans <- try(numDeriv::hessian(cost_function, c(bparms.optim, errparms), OLS = FALSE, trans = FALSE, update_data = FALSE), silent = TRUE) - + if (inherits(fit$hessian_notrans, "try-error")) { + fit$hessian_notrans <- matrix(NA, nrow = dim_hessian, ncol = dim_hessian) + } dimnames(fit$hessian_notrans) <- list(names(c(bparms.optim, errparms)), names(c(bparms.optim, errparms))) }) @@ -114,15 +114,18 @@ mmkin <- function(models = c("SFO", "FOMC", "DFOP"), datasets, return(res) } - if (is.null(cluster)) { - results <- parallel::mclapply(as.list(1:n.fits), fit_function, - mc.cores = cores, mc.preschedule = FALSE) - } else { - results <- parallel::parLapply(cluster, as.list(1:n.fits), fit_function) - } + fit_time <- system.time({ + if (is.null(cluster)) { + results <- parallel::mclapply(as.list(1:n.fits), fit_function, + mc.cores = cores, mc.preschedule = FALSE) + } else { + results <- parallel::parLapply(cluster, as.list(1:n.fits), fit_function) + } + }) attributes(results) <- attributes(fit_indices) attr(results, "call") <- call + attr(results, "time") <- fit_time class(results) <- "mmkin" return(results) } @@ -168,41 +171,7 @@ mmkin <- function(models = c("SFO", "FOMC", "DFOP"), datasets, print.mmkin <- function(x, ...) { cat("<mmkin> object\n") cat("Status of individual fits:\n\n") - all_summary_warnings <- character() - sww <- 0 # Counter for Shapiro-Wilks warnings - - display <- lapply(x, - function(fit) { - if (inherits(fit, "try-error")) return("E") - sw <- fit$summary_warnings - swn <- names(sw) - if (length(sw) > 0) { - if (any(grepl("S", swn))) { - sww <<- sww + 1 - swn <- gsub("S", paste0("S", sww), swn) - } - warnstring <- paste(swn, collapse = ", ") - names(sw) <- swn - all_summary_warnings <<- c(all_summary_warnings, sw) - return(warnstring) - } else { - return("OK") - } - }) - display <- unlist(display) - dim(display) <- dim(x) - dimnames(display) <- dimnames(x) - print(display, quote = FALSE) - - cat("\n") - if (any(display == "OK")) cat("OK: No warnings\n") - if (any(display == "E")) cat("E: Error\n") - u_swn <- unique(names(all_summary_warnings)) - u_w <- all_summary_warnings[u_swn] - for (i in seq_along(u_w)) { - cat(names(u_w)[i], ": ", u_w[i], "\n", sep = "") - } - + print(status(x)) } #' @export diff --git a/R/multistart.R b/R/multistart.R new file mode 100644 index 00000000..61ef43dc --- /dev/null +++ b/R/multistart.R @@ -0,0 +1,224 @@ +#' Perform a hierarchical model fit with multiple starting values +#' +#' The purpose of this method is to check if a certain algorithm for fitting +#' nonlinear hierarchical models (also known as nonlinear mixed-effects models) +#' will reliably yield results that are sufficiently similar to each other, if +#' started with a certain range of reasonable starting parameters. It is +#' inspired by the article on practical identifiabiliy in the frame of nonlinear +#' mixed-effects models by Duchesne et al (2021). +#' +#' @param object The fit object to work with +#' @param n How many different combinations of starting parameters should be +#' used? +#' @param cores How many fits should be run in parallel (only on posix platforms)? +#' @param cluster A cluster as returned by [parallel::makeCluster] to be used +#' for parallel execution. +#' @param \dots Passed to the update function. +#' @param x The multistart object to print +#' @return A list of [saem.mmkin] objects, with class attributes +#' 'multistart.saem.mmkin' and 'multistart'. +#' @seealso [parplot], [llhist] +#' +#' @references Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +#' identifiability in the frame of nonlinear mixed effects models: the example +#' of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +#' doi: 10.1186/s12859-021-04373-4. +#' @export +#' @examples +#' \dontrun{ +#' library(mkin) +#' dmta_ds <- lapply(1:7, function(i) { +#' ds_i <- dimethenamid_2018$ds[[i]]$data +#' ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" +#' ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] +#' ds_i +#' }) +#' names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) +#' dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) +#' dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL +#' +#' f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE) +#' f_saem_full <- saem(f_mmkin) +#' f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16) +#' parplot(f_saem_full_multi, lpos = "topleft") +#' illparms(f_saem_full) +#' +#' f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") +#' illparms(f_saem_reduced) +#' # On Windows, we need to create a cluster first. When working with +#' # such a cluster, we need to export the mmkin object to the cluster +#' # nodes, as it is referred to when updating the saem object on the nodes. +#' library(parallel) +#' cl <- makePSOCKcluster(12) +#' f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl) +#' parplot(f_saem_reduced_multi, lpos = "topright") +#' stopCluster(cl) +#' } +multistart <- function(object, n = 50, + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), + cluster = NULL, ...) +{ + UseMethod("multistart", object) +} + +#' @rdname multistart +#' @export +multistart.saem.mmkin <- function(object, n = 50, cores = 1, + cluster = NULL, ...) { + call <- match.call() + if (n <= 1) stop("Please specify an n of at least 2") + + mmkin_object <- object$mmkin + + mmkin_parms <- parms(mmkin_object, errparms = FALSE, + transformed = object$transformations == "mkin") + start_parms <- apply( + mmkin_parms, 1, + function(x) stats::runif(n, min(x), max(x))) + + saem_call <- object$call + saem_call[[1]] <- saem + saem_call[[2]] <- mmkin_object + i_startparms <- which(names(saem_call) == "degparms_start") + + fit_function <- function(x) { + + new_startparms <- str2lang( + paste0(capture.output(dput(start_parms[x, ])), + collapse = "")) + + if (length(i_startparms) == 0) { + saem_call <- c(as.list(saem_call), degparms_start = new_startparms) + saem_call <- as.call(saem_call) + } else { + saem_call[i_startparms] <- new_startparms + } + + ret <- eval(saem_call) + + return(ret) + } + + if (is.null(cluster)) { + res <- parallel::mclapply(1:n, fit_function, mc.cores = cores) + } else { + res <- parallel::parLapply(cluster, 1:n, fit_function) + } + attr(res, "orig") <- object + attr(res, "start_parms") <- start_parms + attr(res, "call") <- call + class(res) <- c("multistart.saem.mmkin", "multistart") + return(res) +} + +#' @export +status.multistart <- function(object, ...) { + all_summary_warnings <- character() + + result <- lapply(object, + function(fit) { + if (inherits(fit, "try-error")) return("E") + else { + return("OK") + } + }) + result <- unlist(result) + + class(result) <- "status.multistart" + return(result) +} + +#' @export +status.multistart.saem.mmkin <- function(object, ...) { + all_summary_warnings <- character() + + result <- lapply(object, + function(fit) { + if (inherits(fit$so, "try-error")) return("E") + else { + return("OK") + } + }) + result <- unlist(result) + + class(result) <- "status.multistart" + return(result) +} + +#' @export +print.status.multistart <- function(x, ...) { + class(x) <- NULL + print(table(x, dnn = NULL)) + if (any(x == "OK")) cat("OK: Fit terminated successfully\n") + if (any(x == "E")) cat("E: Error\n") +} + +#' @rdname multistart +#' @export +print.multistart <- function(x, ...) { + cat("<multistart> object with", length(x), "fits:\n") + print(status(x)) +} + +#' @rdname multistart +#' @export +best <- function(object, ...) +{ + UseMethod("best", object) +} + +#' @export +#' @return The object with the highest likelihood +#' @rdname multistart +best.default <- function(object, ...) +{ + return(object[[which.best(object)]]) +} + +#' @return The index of the object with the highest likelihood +#' @rdname multistart +#' @export +which.best <- function(object, ...) +{ + UseMethod("which.best", object) +} + +#' @rdname multistart +#' @export +which.best.default <- function(object, ...) +{ + llfunc <- function(object) { + ret <- try(logLik(object)) + if (inherits(ret, "try-error")) return(NA) + else return(ret) + } + ll <- sapply(object, llfunc) + return(which.max(ll)) +} + +#' @export +update.multistart <- function(object, ..., evaluate = TRUE) { + call <- attr(object, "call") + # For some reason we get multistart.saem.mmkin in call[[1]] when using multistart + # from the loaded package so we need to fix this so we do not have to export + # multistart.saem.mmkin + call[[1]] <- multistart + + update_arguments <- match.call(expand.dots = FALSE)$... + + if (length(update_arguments) > 0) { + update_arguments_in_call <- !is.na(match(names(update_arguments), names(call))) + } + + for (a in names(update_arguments)[update_arguments_in_call]) { + call[[a]] <- update_arguments[[a]] + } + + update_arguments_not_in_call <- !update_arguments_in_call + if(any(update_arguments_not_in_call)) { + call <- c(as.list(call), update_arguments[update_arguments_not_in_call]) + call <- as.call(call) + } + if(evaluate) eval(call, parent.frame()) + else call +} @@ -125,7 +125,7 @@ nlme_function <- function(object) { } #' @rdname nlme -#' @importFrom purrr map_dfr +#' @importFrom rlang !!! #' @return A \code{\link{groupedData}} object #' @export nlme_data <- function(object) { @@ -134,7 +134,7 @@ nlme_data <- function(object) { ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")]) names(ds_list) <- ds_names - ds_nlme <- purrr::map_dfr(ds_list, function(x) x, .id = "ds") + ds_nlme <- vctrs::vec_rbind(!!!ds_list, .names_to = "ds") ds_nlme$variable <- as.character(ds_nlme$variable) ds_nlme$ds <- ordered(ds_nlme$ds, levels = unique(ds_nlme$ds)) ds_nlme_renamed <- data.frame(ds = ds_nlme$ds, name = ds_nlme$variable, diff --git a/R/parms.R b/R/parms.R new file mode 100644 index 00000000..bd4e479b --- /dev/null +++ b/R/parms.R @@ -0,0 +1,82 @@ +#' Extract model parameters +#' +#' This function returns degradation model parameters as well as error +#' model parameters per default, in order to avoid working with a fitted model +#' without considering the error structure that was assumed for the fit. +#' +#' @param object A fitted model object. +#' @param \dots Not used +#' @return Depending on the object, a numeric vector of fitted model parameters, +#' a matrix (e.g. for mmkin row objects), or a list of matrices (e.g. for +#' mmkin objects with more than one row). +#' @seealso [saem], [multistart] +#' @examples +#' # mkinfit objects +#' fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE) +#' parms(fit) +#' parms(fit, transformed = TRUE) +#' +#' # mmkin objects +#' ds <- lapply(experimental_data_for_UBA_2019[6:10], +#' function(x) subset(x$data[c("name", "time", "value")])) +#' names(ds) <- paste("Dataset", 6:10) +#' \dontrun{ +#' fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1) +#' parms(fits["SFO", ]) +#' parms(fits[, 2]) +#' parms(fits) +#' parms(fits, transformed = TRUE) +#' } +#' @export +parms <- function(object, ...) +{ + UseMethod("parms", object) +} + +#' @param transformed Should the parameters be returned as used internally +#' during the optimisation? +#' @param errparms Should the error model parameters be returned +#' in addition to the degradation parameters? +#' @rdname parms +#' @export +parms.mkinfit <- function(object, transformed = FALSE, errparms = TRUE, ...) +{ + res <- if (transformed) object$par + else c(object$bparms.optim, object$errparms) + if (!errparms) { + res[setdiff(names(res), names(object$errparms))] + } + else return(res) +} + +#' @rdname parms +#' @export +parms.mmkin <- function(object, transformed = FALSE, errparms = TRUE, ...) +{ + if (nrow(object) == 1) { + res <- sapply(object, parms, transformed = transformed, + errparms = errparms, ...) + colnames(res) <- colnames(object) + } else { + res <- list() + for (i in 1:nrow(object)) { + res[[i]] <- parms(object[i, ], transformed = transformed, + errparms = errparms, ...) + } + names(res) <- rownames(object) + } + return(res) +} + +#' @param exclude_failed For [multistart] objects, should rows for failed fits +#' be removed from the returned parameter matrix? +#' @rdname parms +#' @export +parms.multistart <- function(object, exclude_failed = TRUE, ...) { + res <- t(sapply(object, parms)) + successful <- which(!is.na(res[, 1])) + first_success <- successful[1] + colnames(res) <- names(parms(object[[first_success]])) + if (exclude_failed) res <- res[successful, ] + return(res) +} diff --git a/R/parms.mkinfit.R b/R/parms.mkinfit.R deleted file mode 100644 index a1f2d209..00000000 --- a/R/parms.mkinfit.R +++ /dev/null @@ -1,62 +0,0 @@ -#' Extract model parameters from mkinfit models -#' -#' This function always returns degradation model parameters as well as error -#' model parameters, in order to avoid working with a fitted model without -#' considering the error structure that was assumed for the fit. -#' -#' @param object A fitted model object. Methods are implemented for -#' [mkinfit()] objects and for [mmkin()] objects. -#' @param \dots Not used -#' @return For mkinfit objects, a numeric vector of fitted model parameters. -#' For mmkin row objects, a matrix with the parameters with a -#' row for each dataset. If the mmkin object has more than one row, a list of -#' such matrices is returned. -#' @examples -#' # mkinfit objects -#' fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE) -#' parms(fit) -#' parms(fit, transformed = TRUE) -#' -#' # mmkin objects -#' ds <- lapply(experimental_data_for_UBA_2019[6:10], -#' function(x) subset(x$data[c("name", "time", "value")])) -#' names(ds) <- paste("Dataset", 6:10) -#' \dontrun{ -#' fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1) -#' parms(fits["SFO", ]) -#' parms(fits[, 2]) -#' parms(fits) -#' parms(fits, transformed = TRUE) -#' } -#' @export -parms <- function(object, ...) -{ - UseMethod("parms", object) -} - -#' @param transformed Should the parameters be returned -#' as used internally during the optimisation? -#' @rdname parms -#' @export -parms.mkinfit <- function(object, transformed = FALSE, ...) -{ - if (transformed) object$par - else c(object$bparms.optim, object$errparms) -} - -#' @rdname parms -#' @export -parms.mmkin <- function(object, transformed = FALSE, ...) -{ - if (nrow(object) == 1) { - res <- sapply(object, parms, transformed = transformed, ...) - colnames(res) <- colnames(object) - } else { - res <- list() - for (i in 1:nrow(object)) { - res[[i]] <- parms(object[i, ], transformed = transformed, ...) - } - names(res) <- rownames(object) - } - return(res) -} diff --git a/R/parplot.R b/R/parplot.R new file mode 100644 index 00000000..627a4eb8 --- /dev/null +++ b/R/parplot.R @@ -0,0 +1,105 @@ +#' Plot parameter variability of multistart objects +#' +#' Produces a boxplot with all parameters from the multiple runs, scaled +#' either by the parameters of the run with the highest likelihood, +#' or by their medians as proposed in the paper by Duchesne et al. (2021). +#' +#' @param object The [multistart] object +#' @param llmin The minimum likelihood of objects to be shown +#' @param scale By default, scale parameters using the best available fit. +#' If 'median', parameters are scaled using the median parameters from all fits. +#' @param main Title of the plot +#' @param lpos Positioning of the legend. +#' @param \dots Passed to [boxplot] +#' @references Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +#' identifiability in the frame of nonlinear mixed effects models: the example +#' of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +#' doi: 10.1186/s12859-021-04373-4. +#' @seealso [multistart] +#' @importFrom stats median +#' @export +parplot <- function(object, ...) { + UseMethod("parplot") +} + +#' @rdname parplot +#' @export +parplot.multistart.saem.mmkin <- function(object, llmin = -Inf, scale = c("best", "median"), + lpos = "bottomleft", main = "", ...) +{ + oldpar <- par(no.readonly = TRUE) + on.exit(par(oldpar, no.readonly = TRUE)) + + orig <- attr(object, "orig") + orig_parms <- parms(orig) + start_parms <- orig$mean_dp_start + all_parms <- parms(object) + + if (inherits(object, "multistart.saem.mmkin")) { + llfunc <- function(object) { + if (inherits(object$so, "try-error")) return(NA) + else return(logLik(object$so)) + } + } else { + stop("parplot is only implemented for multistart.saem.mmkin objects") + } + ll <- sapply(object, llfunc) + selected <- which(ll > llmin) + selected_parms <- all_parms[selected, ] + + par(las = 1) + if (orig$transformations == "mkin") { + degparm_names_transformed <- names(start_parms) + degparm_index <- which(names(orig_parms) %in% degparm_names_transformed) + orig_parms[degparm_names_transformed] <- backtransform_odeparms( + orig_parms[degparm_names_transformed], + orig$mmkin[[1]]$mkinmod, + transform_rates = orig$mmkin[[1]]$transform_rates, + transform_fractions = orig$mmkin[[1]]$transform_fractions) + start_parms <- backtransform_odeparms(start_parms, + orig$mmkin[[1]]$mkinmod, + transform_rates = orig$mmkin[[1]]$transform_rates, + transform_fractions = orig$mmkin[[1]]$transform_fractions) + degparm_names <- names(start_parms) + + names(orig_parms) <- c(degparm_names, names(orig_parms[-degparm_index])) + + selected_parms[, degparm_names_transformed] <- + t(apply(selected_parms[, degparm_names_transformed], 1, backtransform_odeparms, + orig$mmkin[[1]]$mkinmod, + transform_rates = orig$mmkin[[1]]$transform_rates, + transform_fractions = orig$mmkin[[1]]$transform_fractions)) + colnames(selected_parms)[1:length(degparm_names)] <- degparm_names + } + + scale <- match.arg(scale) + parm_scale <- switch(scale, + best = selected_parms[which.best(object[selected]), ], + median = apply(selected_parms, 2, median) + ) + + # Boxplots of all scaled parameters + selected_scaled_parms <- t(apply(selected_parms, 1, function(x) x / parm_scale)) + boxplot(selected_scaled_parms, log = "y", main = main, , + ylab = "Normalised parameters", ...) + + # Show starting parameters + start_scaled_parms <- rep(NA_real_, length(orig_parms)) + names(start_scaled_parms) <- names(orig_parms) + start_scaled_parms[names(start_parms)] <- + start_parms / parm_scale[names(start_parms)] + points(start_scaled_parms, col = 3, cex = 3) + + # Show parameters of original run + orig_scaled_parms <- orig_parms / parm_scale + points(orig_scaled_parms, col = 2, cex = 2) + + abline(h = 1, lty = 2) + + legend(lpos, inset = c(0.05, 0.05), bty = "n", + pch = 1, col = 3:1, lty = c(NA, NA, 1), + legend = c( + "Starting parameters", + "Original run", + "Multistart runs")) +} diff --git a/R/plot.mixed.mmkin.R b/R/plot.mixed.mmkin.R index 3a444253..6815bfd2 100644 --- a/R/plot.mixed.mmkin.R +++ b/R/plot.mixed.mmkin.R @@ -153,7 +153,7 @@ plot.mixed.mmkin <- function(x, outtimes <- sort(unique(c(x$data$time, seq(xlim[1], xlim[2], length.out = 50)))) - pred_ds <- purrr::map_dfr(i, function(ds_i) { + pred_list <- lapply(i, function(ds_i) { odeparms_trans <- degparms_all[ds_i, odeparms_names] names(odeparms_trans) <- odeparms_names # needed if only one odeparm if (backtransform) { @@ -171,8 +171,9 @@ plot.mixed.mmkin <- function(x, out <- mkinpredict(x$mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, atol = fit_1$atol, rtol = fit_1$rtol) - return(cbind(as.data.frame(out), ds = ds_names[ds_i])) }) + names(pred_list) <- ds_names[i] + pred_ds <- vctrs::vec_rbind(!!!pred_list, .names_to = "ds") odeparms_pop_trans <- degparms_all_pop[odeparms_names] @@ -15,35 +15,46 @@ utils::globalVariables(c("predicted", "std")) #' #' @importFrom utils packageVersion #' @param object An [mmkin] row object containing several fits of the same -#' [mkinmod] model to different datasets +#' [mkinmod] model to different datasets #' @param verbose Should we print information about created objects of -#' type [saemix::SaemixModel] and [saemix::SaemixData]? +#' type [saemix::SaemixModel] and [saemix::SaemixData]? #' @param transformations Per default, all parameter transformations are done -#' in mkin. If this argument is set to 'saemix', parameter transformations -#' are done in 'saemix' for the supported cases. Currently this is only -#' supported in cases where the initial concentration of the parent is not fixed, -#' SFO or DFOP is used for the parent and there is either no metabolite or one. +#' in mkin. If this argument is set to 'saemix', parameter transformations +#' are done in 'saemix' for the supported cases, i.e. (as of version 1.1.2) +#' SFO, FOMC, DFOP and HS without fixing `parent_0`, and SFO or DFOP with +#' one SFO metabolite. #' @param degparms_start Parameter values given as a named numeric vector will -#' be used to override the starting values obtained from the 'mmkin' object. +#' be used to override the starting values obtained from the 'mmkin' object. #' @param test_log_parms If TRUE, an attempt is made to use more robust starting -#' values for population parameters fitted as log parameters in mkin (like -#' rate constants) by only considering rate constants that pass the t-test -#' when calculating mean degradation parameters using [mean_degparms]. +#' values for population parameters fitted as log parameters in mkin (like +#' rate constants) by only considering rate constants that pass the t-test +#' when calculating mean degradation parameters using [mean_degparms]. #' @param conf.level Possibility to adjust the required confidence level -#' for parameter that are tested if requested by 'test_log_parms'. +#' for parameter that are tested if requested by 'test_log_parms'. #' @param solution_type Possibility to specify the solution type in case the -#' automatic choice is not desired +#' automatic choice is not desired +#' @param no_random_effect Character vector of degradation parameters for +#' which there should be no variability over the groups. Only used +#' if the covariance model is not explicitly specified. +#' @param covariance.model Will be passed to [saemix::SaemixModel()]. Per +#' default, uncorrelated random effects are specified for all degradation +#' parameters. +#' @param covariates A data frame with covariate data for use in +#' 'covariate_models', with dataset names as row names. +#' @param covariate_models A list containing linear model formulas with one explanatory +#' variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available +#' in the 'covariates' data frame. #' @param fail_with_errors Should a failure to compute standard errors -#' from the inverse of the Fisher Information Matrix be a failure? +#' from the inverse of the Fisher Information Matrix be a failure? #' @param quiet Should we suppress the messages saemix prints at the beginning -#' and the end of the optimisation process? +#' and the end of the optimisation process? #' @param nbiter.saemix Convenience option to increase the number of -#' iterations +#' iterations #' @param control Passed to [saemix::saemix]. #' @param \dots Further parameters passed to [saemix::saemixModel]. #' @return An S3 object of class 'saem.mmkin', containing the fitted -#' [saemix::SaemixObject] as a list component named 'so'. The -#' object also inherits from 'mixed.mmkin'. +#' [saemix::SaemixObject] as a list component named 'so'. The +#' object also inherits from 'mixed.mmkin'. #' @seealso [summary.saem.mmkin] [plot.mixed.mmkin] #' @examples #' \dontrun{ @@ -58,7 +69,13 @@ utils::globalVariables(c("predicted", "std")) #' f_saem_sfo <- saem(f_mmkin_parent["SFO", ]) #' f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) #' f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +#' anova(f_saem_sfo, f_saem_fomc, f_saem_dfop) +#' anova(f_saem_sfo, f_saem_dfop, test = TRUE) +#' illparms(f_saem_dfop) +#' f_saem_dfop_red <- update(f_saem_dfop, no_random_effect = "g_qlogis") +#' anova(f_saem_dfop, f_saem_dfop_red, test = TRUE) #' +#' anova(f_saem_sfo, f_saem_fomc, f_saem_dfop) #' # The returned saem.mmkin object contains an SaemixObject, therefore we can use #' # functions from saemix #' library(saemix) @@ -70,7 +87,7 @@ utils::globalVariables(c("predicted", "std")) #' #' f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") #' f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ]) -#' compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so) +#' anova(f_saem_fomc, f_saem_fomc_tc, test = TRUE) #' #' sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), #' A1 = mkinsub("SFO")) @@ -118,6 +135,10 @@ saem.mmkin <- function(object, test_log_parms = TRUE, conf.level = 0.6, solution_type = "auto", + covariance.model = "auto", + covariates = NULL, + covariate_models = NULL, + no_random_effect = NULL, nbiter.saemix = c(300, 100), control = list(displayProgress = FALSE, print = FALSE, nbiter.saemix = nbiter.saemix, @@ -125,56 +146,68 @@ saem.mmkin <- function(object, fail_with_errors = TRUE, verbose = FALSE, quiet = FALSE, ...) { + call <- match.call() transformations <- match.arg(transformations) m_saemix <- saemix_model(object, verbose = verbose, degparms_start = degparms_start, test_log_parms = test_log_parms, conf.level = conf.level, solution_type = solution_type, - transformations = transformations, ...) - d_saemix <- saemix_data(object, verbose = verbose) + transformations = transformations, + covariance.model = covariance.model, + covariates = covariates, + covariate_models = covariate_models, + no_random_effect = no_random_effect, + ...) + d_saemix <- saemix_data(object, covariates = covariates, verbose = verbose) + fit_failed <- FALSE + FIM_failed <- NULL fit_time <- system.time({ - utils::capture.output(f_saemix <- saemix::saemix(m_saemix, d_saemix, control), split = !quiet) - FIM_failed <- NULL + utils::capture.output(f_saemix <- try(saemix::saemix(m_saemix, d_saemix, control)), split = !quiet) + if (inherits(f_saemix, "try-error")) fit_failed <- TRUE + }) + + return_data <- nlme_data(object) + + if (!fit_failed) { if (any(is.na(f_saemix@results@se.fixed))) FIM_failed <- c(FIM_failed, "fixed effects") if (any(is.na(c(f_saemix@results@se.omega, f_saemix@results@se.respar)))) { - FIM_failed <- c(FIM_failed, "random effects and residual error parameters") + FIM_failed <- c(FIM_failed, "random effects and error model parameters") } if (!is.null(FIM_failed) & fail_with_errors) { stop("Could not invert FIM for ", paste(FIM_failed, collapse = " and ")) } - }) - transparms_optim <- f_saemix@results@fixed.effects - names(transparms_optim) <- f_saemix@results@name.fixed + transparms_optim <- f_saemix@results@fixed.effects + names(transparms_optim) <- f_saemix@results@name.fixed - if (transformations == "mkin") { - bparms_optim <- backtransform_odeparms(transparms_optim, - object[[1]]$mkinmod, - object[[1]]$transform_rates, - object[[1]]$transform_fractions) - } else { - bparms_optim <- transparms_optim - } + if (transformations == "mkin") { + bparms_optim <- backtransform_odeparms(transparms_optim, + object[[1]]$mkinmod, + object[[1]]$transform_rates, + object[[1]]$transform_fractions) + } else { + bparms_optim <- transparms_optim + } - return_data <- nlme_data(object) - saemix_data_ds <- f_saemix@data@data$ds - mkin_ds_order <- as.character(unique(return_data$ds)) - saemix_ds_order <- unique(saemix_data_ds) - - psi <- saemix::psi(f_saemix) - rownames(psi) <- saemix_ds_order - return_data$predicted <- f_saemix@model@model( - psi = psi[mkin_ds_order, ], - id = as.numeric(return_data$ds), - xidep = return_data[c("time", "name")]) - - return_data <- transform(return_data, - residual = value - predicted, - std = sigma_twocomp(predicted, - f_saemix@results@respar[1], f_saemix@results@respar[2])) - return_data <- transform(return_data, - standardized = residual / std) + saemix_data_ds <- f_saemix@data@data$ds + mkin_ds_order <- as.character(unique(return_data$ds)) + saemix_ds_order <- unique(saemix_data_ds) + + psi <- saemix::psi(f_saemix) + rownames(psi) <- saemix_ds_order + return_data$predicted <- f_saemix@model@model( + psi = psi[mkin_ds_order, ], + id = as.numeric(return_data$ds), + xidep = return_data[c("time", "name")]) + + return_data <- transform(return_data, + residual = value - predicted, + std = sigma_twocomp(predicted, + f_saemix@results@respar[1], f_saemix@results@respar[2])) + return_data <- transform(return_data, + standardized = residual / std) + } result <- list( mkinmod = object[[1]]$mkinmod, @@ -183,14 +216,14 @@ saem.mmkin <- function(object, transformations = transformations, transform_rates = object[[1]]$transform_rates, transform_fractions = object[[1]]$transform_fractions, + sm = m_saemix, so = f_saemix, + call = call, time = fit_time, + FIM_failed = FIM_failed, mean_dp_start = attr(m_saemix, "mean_dp_start"), - bparms.optim = bparms_optim, bparms.fixed = object[[1]]$bparms.fixed, data = return_data, - mkin_ds_order = mkin_ds_order, - saemix_ds_order = saemix_ds_order, err_mod = object[[1]]$err_mod, date.fit = date(), saemixversion = as.character(utils::packageVersion("saemix")), @@ -198,6 +231,12 @@ saem.mmkin <- function(object, Rversion = paste(R.version$major, R.version$minor, sep=".") ) + if (!fit_failed) { + result$mkin_ds_order <- mkin_ds_order + result$saemix_ds_order <- saemix_ds_order + result$bparms.optim <- bparms_optim + } + class(result) <- c("saem.mmkin", "mixed.mmkin") return(result) } @@ -217,18 +256,20 @@ print.saem.mmkin <- function(x, digits = max(3, getOption("digits") - 3), ...) { length(unique(x$data$name)), "variable(s) grouped in", length(unique(x$data$ds)), "datasets\n") - cat("\nLikelihood computed by importance sampling\n") - print(data.frame( - AIC = AIC(x$so, type = "is"), - BIC = BIC(x$so, type = "is"), - logLik = logLik(x$so, type = "is"), - row.names = " "), digits = digits) - - cat("\nFitted parameters:\n") - conf.int <- x$so@results@conf.int[c("estimate", "lower", "upper")] - rownames(conf.int) <- x$so@results@conf.int[["name"]] - conf.int.var <- grepl("^Var\\.", rownames(conf.int)) - print(conf.int[!conf.int.var, ], digits = digits) + if (inherits(x$so, "try-error")) { + cat("\nFit did not terminate successfully\n") + } else { + cat("\nLikelihood computed by importance sampling\n") + print(data.frame( + AIC = AIC(x$so, type = "is"), + BIC = BIC(x$so, type = "is"), + logLik = logLik(x$so, type = "is"), + row.names = " "), digits = digits) + + cat("\nFitted parameters:\n") + conf.int <- parms(x, ci = TRUE) + print(conf.int, digits = digits) + } invisible(x) } @@ -236,14 +277,23 @@ print.saem.mmkin <- function(x, digits = max(3, getOption("digits") - 3), ...) { #' @rdname saem #' @return An [saemix::SaemixModel] object. #' @export -saemix_model <- function(object, solution_type = "auto", transformations = c("mkin", "saemix"), - degparms_start = numeric(), test_log_parms = FALSE, conf.level = 0.6, verbose = FALSE, ...) +saemix_model <- function(object, solution_type = "auto", + transformations = c("mkin", "saemix"), degparms_start = numeric(), + covariance.model = "auto", no_random_effect = NULL, + covariates = NULL, covariate_models = NULL, + test_log_parms = FALSE, conf.level = 0.6, verbose = FALSE, ...) { if (nrow(object) > 1) stop("Only row objects allowed") mkin_model <- object[[1]]$mkinmod degparms_optim <- mean_degparms(object, test_log_parms = test_log_parms) + na_degparms <- names(which(is.na(degparms_optim))) + if (length(na_degparms) > 0) { + message("Did not find valid starting values for ", paste(na_degparms, collapse = ", "), "\n", + "Now trying with test_log_parms = FALSE") + degparms_optim <- mean_degparms(object, test_log_parms = FALSE) + } if (transformations == "saemix") { degparms_optim <- backtransform_odeparms(degparms_optim, object[[1]]$mkinmod, @@ -252,7 +302,8 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk } degparms_fixed <- object[[1]]$bparms.fixed - # Transformations are done in the degradation function + # Transformations are done in the degradation function by default + # (transformations = "mkin") transform.par = rep(0, length(degparms_optim)) odeini_optim_parm_names <- grep('_0$', names(degparms_optim), value = TRUE) @@ -275,7 +326,10 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk # Parent only if (length(mkin_model$spec) == 1) { parent_type <- mkin_model$spec[[1]]$type - if (length(odeini_fixed) == 1) { + if (length(odeini_fixed) == 1 && !grepl("_bound$", names(odeini_fixed))) { + if (transformations == "saemix") { + stop("saemix transformations are not supported for parent fits with fixed initial parent value") + } if (parent_type == "SFO") { stop("saemix needs at least two parameters to work on.") } @@ -303,6 +357,9 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk } } } else { + if (length(odeini_fixed) == 2) { + stop("SFORB with fixed initial parent value is not supported") + } if (parent_type == "SFO") { if (transformations == "mkin") { model_function <- function(psi, id, xidep) { @@ -316,8 +373,15 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk } } if (parent_type == "FOMC") { - model_function <- function(psi, id, xidep) { - psi[id, 1] / (xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id, 2]) + if (transformations == "mkin") { + model_function <- function(psi, id, xidep) { + psi[id, 1] / (xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id, 2]) + } + } else { + model_function <- function(psi, id, xidep) { + psi[id, 1] / (xidep[, "time"]/psi[id, 3] + 1)^psi[id, 2] + } + transform.par = c(0, 1, 1) } } if (parent_type == "DFOP") { @@ -338,14 +402,57 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk transform.par = c(0, 1, 1, 3) } } + if (parent_type == "SFORB") { + if (transformations == "mkin") { + model_function <- function(psi, id, xidep) { + k_12 <- exp(psi[id, 3]) + k_21 <- exp(psi[id, 4]) + k_1output <- exp(psi[id, 2]) + t <- xidep[, "time"] + + sqrt_exp = sqrt(1/4 * (k_12 + k_21 + k_1output)^2 + k_12 * k_21 - (k_12 + k_1output) * k_21) + b1 = 0.5 * (k_12 + k_21 + k_1output) + sqrt_exp + b2 = 0.5 * (k_12 + k_21 + k_1output) - sqrt_exp + + psi[id, 1] * (((k_12 + k_21 - b1)/(b2 - b1)) * exp(-b1 * t) + + ((k_12 + k_21 - b2)/(b1 - b2)) * exp(-b2 * t)) + } + } else { + model_function <- function(psi, id, xidep) { + k_12 <- psi[id, 3] + k_21 <- psi[id, 4] + k_1output <- psi[id, 2] + t <- xidep[, "time"] + + sqrt_exp = sqrt(1/4 * (k_12 + k_21 + k_1output)^2 + k_12 * k_21 - (k_12 + k_1output) * k_21) + b1 = 0.5 * (k_12 + k_21 + k_1output) + sqrt_exp + b2 = 0.5 * (k_12 + k_21 + k_1output) - sqrt_exp + + psi[id, 1] * (((k_12 + k_21 - b1)/(b2 - b1)) * exp(-b1 * t) + + ((k_12 + k_21 - b2)/(b1 - b2)) * exp(-b2 * t)) + } + transform.par = c(0, 1, 1, 1) + } + } if (parent_type == "HS") { - model_function <- function(psi, id, xidep) { - tb <- exp(psi[id, 4]) - t <- xidep[, "time"] - k1 = exp(psi[id, 2]) - psi[id, 1] * ifelse(t <= tb, - exp(- k1 * t), - exp(- k1 * tb) * exp(- exp(psi[id, 3]) * (t - tb))) + if (transformations == "mkin") { + model_function <- function(psi, id, xidep) { + tb <- exp(psi[id, 4]) + t <- xidep[, "time"] + k1 <- exp(psi[id, 2]) + psi[id, 1] * ifelse(t <= tb, + exp(- k1 * t), + exp(- k1 * tb) * exp(- exp(psi[id, 3]) * (t - tb))) + } + } else { + model_function <- function(psi, id, xidep) { + tb <- psi[id, 4] + t <- xidep[, "time"] + psi[id, 1] * ifelse(t <= tb, + exp(- psi[id, 2] * t), + exp(- psi[id, 2] * tb) * exp(- psi[id, 3] * (t - tb))) + } + transform.par = c(0, 1, 1, 1) } } } @@ -518,8 +625,52 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk degparms_psi0 <- degparms_optim degparms_psi0[names(degparms_start)] <- degparms_start - psi0_matrix <- matrix(degparms_psi0, nrow = 1) - colnames(psi0_matrix) <- names(degparms_psi0) + psi0_matrix <- matrix(degparms_psi0, nrow = 1, + dimnames = list("(Intercept)", names(degparms_psi0))) + + if (covariance.model[1] == "auto") { + covariance_diagonal <- rep(1, length(degparms_optim)) + if (!is.null(no_random_effect)) { + degparms_no_random <- which(names(degparms_psi0) %in% no_random_effect) + covariance_diagonal[degparms_no_random] <- 0 + } + covariance.model = diag(covariance_diagonal) + } + + if (is.null(covariate_models)) { + covariate.model <- matrix(nrow = 0, ncol = 0) # default in saemixModel() + } else { + degparms_dependent <- sapply(covariate_models, function(x) as.character(x[[2]])) + covariates_in_models = unique(unlist(lapply( + covariate_models, function(x) + colnames(attr(terms(x), "factors")) + ))) + covariates_not_available <- setdiff(covariates_in_models, names(covariates)) + if (length(covariates_not_available) > 0) { + stop("Covariate(s) ", paste(covariates_not_available, collapse = ", "), + " used in the covariate models not available in the covariate data") + } + psi0_matrix <- rbind(psi0_matrix, + matrix(0, nrow = length(covariates), ncol = ncol(psi0_matrix), + dimnames = list(names(covariates), colnames(psi0_matrix)))) + covariate.model <- matrix(0, nrow = length(covariates), + ncol = ncol(psi0_matrix), + dimnames = list( + covariates = names(covariates), + degparms = colnames(psi0_matrix))) + if (transformations == "saemix") { + stop("Covariate models with saemix transformations currently not supported") + } + parms_trans <- as.data.frame(t(sapply(object, parms, transformed = TRUE))) + for (covariate_model in covariate_models) { + covariate_name <- as.character(covariate_model[[2]]) + model_data <- cbind(parms_trans, covariates) + ini_model <- lm(covariate_model, data = model_data) + ini_coef <- coef(ini_model) + psi0_matrix[names(ini_coef), covariate_name] <- ini_coef + covariate.model[names(ini_coef)[-1], covariate_name] <- as.numeric(as.logical(ini_coef[-1])) + } + } res <- saemix::saemixModel(model_function, psi0 = psi0_matrix, @@ -527,6 +678,8 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk transform.par = transform.par, error.model = error.model, verbose = verbose, + covariance.model = covariance.model, + covariate.model = covariate.model, ... ) attr(res, "mean_dp_start") <- degparms_optim @@ -534,26 +687,107 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mk } #' @rdname saem +#' @importFrom rlang !!! #' @return An [saemix::SaemixData] object. #' @export -saemix_data <- function(object, verbose = FALSE, ...) { +saemix_data <- function(object, covariates = NULL, verbose = FALSE, ...) { if (nrow(object) > 1) stop("Only row objects allowed") ds_names <- colnames(object) ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")]) names(ds_list) <- ds_names - ds_saemix_all <- purrr::map_dfr(ds_list, function(x) x, .id = "ds") + ds_saemix_all <- vctrs::vec_rbind(!!!ds_list, .names_to = "ds") ds_saemix <- data.frame(ds = ds_saemix_all$ds, name = as.character(ds_saemix_all$variable), time = ds_saemix_all$time, value = ds_saemix_all$observed, stringsAsFactors = FALSE) + if (!is.null(covariates)) { + name.covariates <- names(covariates) + covariates$ds <- rownames(covariates) + ds_saemix <- merge(ds_saemix, covariates, sort = FALSE) + } else { + name.covariates <- character(0) + } res <- saemix::saemixData(ds_saemix, name.group = "ds", name.predictors = c("time", "name"), name.response = "value", + name.covariates = name.covariates, verbose = verbose, ...) return(res) } + +#' logLik method for saem.mmkin objects +#' +#' @param object The fitted [saem.mmkin] object +#' @param \dots Passed to [saemix::logLik.SaemixObject] +#' @param method Passed to [saemix::logLik.SaemixObject] +#' @export +logLik.saem.mmkin <- function(object, ..., method = c("is", "lin", "gq")) { + method <- match.arg(method) + return(logLik(object$so, method = method)) +} + +#' @export +update.saem.mmkin <- function(object, ..., evaluate = TRUE) { + call <- object$call + # For some reason we get saem.mmkin in the call when using mhmkin + # so we need to fix this so we do not have to export saem.mmkin in + # addition to the S3 method + call[[1]] <- saem + + # We also need to provide the mmkin object in the call, so it + # will also be found when called by testthat or pkgdown + call[[2]] <- object$mmkin + + update_arguments <- match.call(expand.dots = FALSE)$... + + if (length(update_arguments) > 0) { + update_arguments_in_call <- !is.na(match(names(update_arguments), names(call))) + } + + for (a in names(update_arguments)[update_arguments_in_call]) { + call[[a]] <- update_arguments[[a]] + } + + update_arguments_not_in_call <- !update_arguments_in_call + if(any(update_arguments_not_in_call)) { + call <- c(as.list(call), update_arguments[update_arguments_not_in_call]) + call <- as.call(call) + } + if(evaluate) eval(call, parent.frame()) + else call +} + +#' @export +#' @rdname saem +#' @param ci Should a matrix with estimates and confidence interval boundaries +#' be returned? If FALSE (default), a vector of estimates is returned. +parms.saem.mmkin <- function(object, ci = FALSE, ...) { + cov.mod <- object$sm@covariance.model + n_cov_mod_parms <- sum(cov.mod[upper.tri(cov.mod, diag = TRUE)]) + n_parms <- length(object$sm@name.modpar) + + n_cov_mod_parms + + length(object$sm@name.sigma) + + if (inherits(object$so, "try-error")) { + conf.int <- matrix(rep(NA, 3 * n_parms), ncol = 3) + colnames(conf.int) <- c("estimate", "lower", "upper") + } else { + conf.int <- object$so@results@conf.int[c("estimate", "lower", "upper")] + rownames(conf.int) <- object$so@results@conf.int[["name"]] + conf.int.var <- grepl("^Var\\.", rownames(conf.int)) + conf.int <- conf.int[!conf.int.var, ] + conf.int.cov <- grepl("^Cov\\.", rownames(conf.int)) + conf.int <- conf.int[!conf.int.cov, ] + } + estimate <- conf.int[, "estimate"] + + names(estimate) <- rownames(conf.int) + + if (ci) return(conf.int) + else return(estimate) +} diff --git a/R/set_nd_nq.R b/R/set_nd_nq.R new file mode 100644 index 00000000..37b9a894 --- /dev/null +++ b/R/set_nd_nq.R @@ -0,0 +1,164 @@ +#' Set non-detects and unquantified values in residue series without replicates +#' +#' This function automates replacing unquantified values in residue time and +#' depth series. For time series, the function performs part of the residue +#' processing proposed in the FOCUS kinetics guidance for parent compounds +#' and metabolites. For two-dimensional residue series over time and depth, +#' it automates the proposal of Boesten et al (2015). +#' +#' @param res_raw Character vector of a residue time series, or matrix of +#' residue values with rows representing depth profiles for a specific sampling +#' time, and columns representing time series of residues at the same depth. +#' Values below the limit of detection (lod) have to be coded as "nd", values +#' between the limit of detection and the limit of quantification, if any, have +#' to be coded as "nq". Samples not analysed have to be coded as "na". All +#' values that are not "na", "nd" or "nq" have to be coercible to numeric +#' @param lod Limit of detection (numeric) +#' @param loq Limit of quantification(numeric). Must be specified if the FOCUS rule to +#' stop after the first non-detection is to be applied +#' @param time_zero_presence Do we assume that residues occur at time zero? +#' This only affects samples from the first sampling time that have been +#' reported as "nd" (not detected). +#' @references Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H. +#' J. and Pol, J. W. (2015). Leaching of plant protection products and their +#' transformation products; Proposals for improving the assessment of leaching +#' to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra +#' Wageningen UR (University & Research centre) +#' @references FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation +#' Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +#' 18 December 2014, p. 251 +#' @return A numeric vector, if a vector was supplied, or a numeric matrix otherwise +#' @export +#' @examples +#' # FOCUS (2014) p. 75/76 and 131/132 +#' parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd") +#' set_nd_nq(parent_1, 0.02) +#' parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd") +#' set_nd_nq(parent_2, 0.02) +#' set_nd_nq_focus(parent_2, 0.02, loq = 0.05) +#' parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd") +#' set_nd_nq(parent_3, 0.02) +#' set_nd_nq_focus(parent_3, 0.02, loq = 0.05) +#' metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd") +#' set_nd_nq(metabolite, 0.02) +#' set_nd_nq_focus(metabolite, 0.02, 0.05) +#' # +#' # Boesten et al. (2015), p. 57/58 +#' table_8 <- matrix( +#' c(10, 10, rep("nd", 4), +#' 10, 10, rep("nq", 2), rep("nd", 2), +#' 10, 10, 10, "nq", "nd", "nd", +#' "nq", 10, "nq", rep("nd", 3), +#' "nd", "nq", "nq", rep("nd", 3), +#' rep("nd", 6), rep("nd", 6)), +#' ncol = 6, byrow = TRUE) +#' set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE) +#' table_10 <- matrix( +#' c(10, 10, rep("nd", 4), +#' 10, 10, rep("nd", 4), +#' 10, 10, 10, rep("nd", 3), +#' "nd", 10, rep("nd", 4), +#' rep("nd", 18)), +#' ncol = 6, byrow = TRUE) +#' set_nd_nq(table_10, 0.5, time_zero_presence = TRUE) +set_nd_nq <- function(res_raw, lod, loq = NA, time_zero_presence = FALSE) { + if (!is.character(res_raw)) { + stop("Please supply a vector or a matrix of character values") + } + if (is.vector(res_raw)) { + was_vector <- TRUE + res_raw <- as.matrix(res_raw) + } else { + was_vector <- FALSE + if (!is.matrix(res_raw)) { + stop("Please supply a vector or a matrix of character values") + } + } + nq <- 0.5 * (loq + lod) + nda <- 0.5 * lod # not detected but adjacent to detection + res_raw[res_raw == "nq"] <- nq + + if (!time_zero_presence) { + for (j in 1:ncol(res_raw)) { + if (res_raw[1, j] == "nd") res_raw[1, j] <- "na" + } + } + res_raw[res_raw == "na"] <- NA + + not_nd_na <- function(value) !(grepl("nd", value) | is.na(value)) + + for (i in 1:nrow(res_raw)) { + for (j in 1:ncol(res_raw)) { + if (!is.na(res_raw[i, j]) && res_raw[i, j] == "nd") { + if (i > 1) { # check earlier sample in same layer + if (not_nd_na(res_raw[i - 1, j])) res_raw[i, j] <- "nda" + } + if (i < nrow(res_raw)) { # check later sample + if (not_nd_na(res_raw[i + 1, j])) res_raw[i, j] <- "nda" + } + if (j > 1) { # check above sample at the same time + if (not_nd_na(res_raw[i, j - 1])) res_raw[i, j] <- "nda" + } + if (j < ncol(res_raw)) { # check sample below at the same time + if (not_nd_na(res_raw[i, j + 1])) res_raw[i, j] <- "nda" + } + } + } + } + res_raw[res_raw == "nda"] <- nda + res_raw[res_raw == "nd"] <- NA + + result <- as.numeric(res_raw) + dim(result) <- dim(res_raw) + dimnames(result) <- dimnames(res_raw) + if (was_vector) result <- as.vector(result) + return(result) +} + +#' @describeIn set_nd_nq Set non-detects in residue time series according to FOCUS rules +#' @param set_first_sample_nd Should the first sample be set to "first_sample_nd_value" +#' in case it is a non-detection? +#' @param first_sample_nd_value Value to be used for the first sample if it is a non-detection +#' @param ignore_below_loq_after_first_nd Should we ignore values below the LOQ after the first +#' non-detection that occurs after the quantified values? +#' @export +set_nd_nq_focus <- function(res_raw, lod, loq = NA, + set_first_sample_nd = TRUE, first_sample_nd_value = 0, + ignore_below_loq_after_first_nd = TRUE) +{ + + if (!is.vector(res_raw)) stop("FOCUS rules are only specified for one-dimensional time series") + + if (ignore_below_loq_after_first_nd & is.na(loq)) { + stop("You need to specify an LOQ") + } + + n <- length(res_raw) + if (ignore_below_loq_after_first_nd) { + for (i in 3:n) { + if (!res_raw[i - 2] %in% c("na", "nd")) { + if (res_raw[i - 1] == "nd") { + res_remaining <- res_raw[i:n] + res_remaining_unquantified <- ifelse(res_remaining == "na", TRUE, + ifelse(res_remaining == "nd", TRUE, + ifelse(res_remaining == "nq", TRUE, + ifelse(suppressWarnings(as.numeric(res_remaining)) < loq, TRUE, FALSE)))) + res_remaining_numeric <- suppressWarnings(as.numeric(res_remaining)) + res_remaining_below_loq <- ifelse(res_remaining == "nq", TRUE, + ifelse(!is.na(res_remaining_numeric) & res_remaining_numeric < loq, TRUE, FALSE)) + if (all(res_remaining_unquantified)) { + res_raw[i:n] <- ifelse(res_remaining_below_loq, "nd", res_remaining) + } + } + } + } + } + + result <- set_nd_nq(res_raw, lod = lod, loq = loq) + + if (set_first_sample_nd) { + if (res_raw[1] == "nd") result[1] <- first_sample_nd_value + } + + return(result) +} diff --git a/R/status.R b/R/status.R new file mode 100644 index 00000000..8bcd3a16 --- /dev/null +++ b/R/status.R @@ -0,0 +1,113 @@ +#' Method to get status information for fit array objects +#' +#' @param object The object to investigate +#' @param x The object to be printed +#' @param \dots For potential future extensions +#' @return An object with the same dimensions as the fit array +#' suitable printing method. +#' @export +status <- function(object, ...) +{ + UseMethod("status", object) +} + +#' @rdname status +#' @export +#' @examples +#' \dontrun{ +#' fits <- mmkin( +#' c("SFO", "FOMC"), +#' list("FOCUS A" = FOCUS_2006_A, +#' "FOCUS B" = FOCUS_2006_C), +#' quiet = TRUE) +#' status(fits) +#' } +status.mmkin <- function(object, ...) { + all_summary_warnings <- character() + sww <- 0 # Counter for Shapiro-Wilks warnings + + result <- lapply(object, + function(fit) { + if (inherits(fit, "try-error")) return("E") + sw <- fit$summary_warnings + swn <- names(sw) + if (length(sw) > 0) { + if (any(grepl("S", swn))) { + sww <<- sww + 1 + swn <- gsub("S", paste0("S", sww), swn) + } + warnstring <- paste(swn, collapse = ", ") + names(sw) <- swn + all_summary_warnings <<- c(all_summary_warnings, sw) + return(warnstring) + } else { + return("OK") + } + }) + result <- unlist(result) + dim(result) <- dim(object) + dimnames(result) <- dimnames(object) + + u_swn <- unique(names(all_summary_warnings)) + attr(result, "unique_warnings") <- all_summary_warnings[u_swn] + class(result) <- "status.mmkin" + return(result) +} + +#' @rdname status +#' @export +print.status.mmkin <- function(x, ...) { + u_w <- attr(x, "unique_warnings") + attr(x, "unique_warnings") <- NULL + class(x) <- NULL + print(x, quote = FALSE) + cat("\n") + for (i in seq_along(u_w)) { + cat(names(u_w)[i], ": ", u_w[i], "\n", sep = "") + } + if (any(x == "OK")) cat("OK: No warnings\n") + if (any(x == "E")) cat("E: Error\n") +} + +#' @rdname status +#' @export +status.mhmkin <- function(object, ...) { + if (inherits(object[[1]], "saem.mmkin")) { + test_func <- function(fit) { + if (inherits(fit$so, "try-error")) { + return("E") + } else { + if (!is.null(fit$FIM_failed)) { + return_values <- c("fixed effects" = "Fth", + "random effects and error model parameters" = "FO") + return(paste(return_values[fit$FIM_failed], collapse = ", ")) + } else { + return("OK") + } + } + } + } else { + stop("Only mhmkin objects containing saem.mmkin objects currently supported") + } + result <- lapply(object, test_func) + result <- unlist(result) + dim(result) <- dim(object) + dimnames(result) <- dimnames(object) + + class(result) <- "status.mhmkin" + return(result) +} + +#' @rdname status +#' @export +print.status.mhmkin <- function(x, ...) { + class(x) <- NULL + print(x, quote = FALSE) + cat("\n") + if (any(x == "OK")) cat("OK: Fit terminated successfully\n") + if (any(x == "Fth")) cat("Fth: Could not invert FIM for fixed effects\n") + if (any(x == "FO")) cat("FO: Could not invert FIM for random effects and error model parameters\n") + if (any(x == "Fth, FO")) cat("Fth, FO: Could not invert FIM for fixed effects, nor for random effects and error model parameters\n") + if (any(x == "E")) cat("E: Error\n") +} + diff --git a/R/summary.mkinfit.R b/R/summary.mkinfit.R index f9858c32..4122873f 100644 --- a/R/summary.mkinfit.R +++ b/R/summary.mkinfit.R @@ -47,7 +47,7 @@ #' \url{http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics} #' @examples #' -#' summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE)) +#' summary(mkinfit("SFO", FOCUS_2006_A, quiet = TRUE)) #' #' @export summary.mkinfit <- function(object, data = TRUE, distimes = TRUE, alpha = 0.05, ...) { @@ -172,7 +172,7 @@ summary.mkinfit <- function(object, data = TRUE, distimes = TRUE, alpha = 0.05, if (distimes) ans$distimes <- ep$distimes if (length(ep$SFORB) != 0) ans$SFORB <- ep$SFORB if (!is.null(object$d_3_message)) ans$d_3_message <- object$d_3_message - class(ans) <- c("summary.mkinfit", "summary.modFit") + class(ans) <- "summary.mkinfit" return(ans) } diff --git a/R/summary.mmkin.R b/R/summary.mmkin.R new file mode 100644 index 00000000..06472e18 --- /dev/null +++ b/R/summary.mmkin.R @@ -0,0 +1,56 @@ +#' Summary method for class "mmkin" +#' +#' Shows status information on the [mkinfit] objects contained in the object +#' and gives an overview of ill-defined parameters calculated by [illparms]. +#' +#' @param object an object of class [mmkin] +#' @param x an object of class \code{summary.mmkin}. +#' @param conf.level confidence level for testing parameters +#' @param digits number of digits to use for printing +#' @param \dots optional arguments passed to methods like \code{print}. +#' @examples +#' +#' fits <- mmkin( +#' c("SFO", "FOMC"), +#' list("FOCUS A" = FOCUS_2006_A, +#' "FOCUS C" = FOCUS_2006_C), +#' quiet = TRUE, cores = 1) +#' summary(fits) +#' +#' @export +summary.mmkin <- function(object, conf.level = 0.95, ...) { + + ans <- list( + err_mod = object[[1, 1]]$err_mod, + time = attr(object, "time"), + illparms = illparms(object), + status = status(object) + ) + + class(ans) <- c("summary.mmkin") + return(ans) +} + +#' @rdname summary.mmkin +#' @export +print.summary.mmkin <- function(x, digits = max(3, getOption("digits") - 3), ...) { + if (!is.null(x$err_mod)) { + cat("Error model: ") + cat(switch(x$err_mod, + const = "Constant variance", + obs = "Variance unique to each observed variable", + tc = "Two-component variance function"), "\n") + } + cat("Fitted in", x$time[["elapsed"]], "s\n") + + cat("\nStatus:\n") + print(x$status) + + if (any(x$illparms != "")) { + cat("\nIll-defined parameters:\n") + print(x$illparms) + } + + invisible(x) +} + diff --git a/R/summary.saem.mmkin.R b/R/summary.saem.mmkin.R index fa52a579..651cc29e 100644 --- a/R/summary.saem.mmkin.R +++ b/R/summary.saem.mmkin.R @@ -73,7 +73,12 @@ #' f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo, #' quiet = TRUE, error_model = "tc", cores = 5) #' f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo) -#' summary(f_saem_dfop_sfo, data = TRUE) +#' print(f_saem_dfop_sfo) +#' illparms(f_saem_dfop_sfo) +#' f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo, covariance.model = diag(c(0, 0, 1, 1, 1, 0))) +#' illparms(f_saem_dfop_sfo_2) +#' intervals(f_saem_dfop_sfo_2) +#' summary(f_saem_dfop_sfo_2, data = TRUE) #' } #' #' @export @@ -82,18 +87,19 @@ summary.saem.mmkin <- function(object, data = FALSE, verbose = FALSE, distimes = mod_vars <- names(object$mkinmod$diffs) pnames <- names(object$mean_dp_start) - np <- length(pnames) + names_fixed_effects <- object$so@results@name.fixed + n_fixed <- length(names_fixed_effects) conf.int <- object$so@results@conf.int rownames(conf.int) <- conf.int$name - confint_trans <- as.matrix(conf.int[pnames, c("estimate", "lower", "upper")]) + confint_trans <- as.matrix(parms(object, ci = TRUE)) colnames(confint_trans)[1] <- "est." # In case objects were produced by earlier versions of saem if (is.null(object$transformations)) object$transformations <- "mkin" if (object$transformations == "mkin") { - bp <- backtransform_odeparms(confint_trans[, "est."], object$mkinmod, + bp <- backtransform_odeparms(confint_trans[pnames, "est."], object$mkinmod, object$transform_rates, object$transform_fractions) bpnames <- names(bp) @@ -126,20 +132,20 @@ summary.saem.mmkin <- function(object, data = FALSE, verbose = FALSE, distimes = } } } else { - confint_back <- confint_trans + confint_back <- confint_trans[names_fixed_effects, ] } # Correlation of fixed effects (inspired by summary.nlme) - varFix <- vcov(object$so)[1:np, 1:np] + varFix <- vcov(object$so)[1:n_fixed, 1:n_fixed] stdFix <- sqrt(diag(varFix)) object$corFixed <- array( t(varFix/stdFix)/stdFix, dim(varFix), - list(pnames, pnames)) + list(names_fixed_effects, names_fixed_effects)) # Random effects - rnames <- paste0("SD.", pnames) - confint_ranef <- as.matrix(conf.int[rnames, c("estimate", "lower", "upper")]) + sdnames <- intersect(rownames(conf.int), paste0("SD.", pnames)) + confint_ranef <- as.matrix(conf.int[sdnames, c("estimate", "lower", "upper")]) colnames(confint_ranef)[1] <- "est." # Error model @@ -147,7 +153,6 @@ summary.saem.mmkin <- function(object, data = FALSE, verbose = FALSE, distimes = confint_errmod <- as.matrix(conf.int[enames, c("estimate", "lower", "upper")]) colnames(confint_errmod)[1] <- "est." - object$confint_trans <- confint_trans object$confint_ranef <- confint_ranef object$confint_errmod <- confint_errmod @@ -202,7 +207,7 @@ print.summary.saem.mmkin <- function(x, digits = max(3, getOption("digits") - 3) cat("\nModel predictions using solution type", x$solution_type, "\n") cat("\nFitted in", x$time[["elapsed"]], "s\n") - cat("Using", paste(x$so@options$nbiter.saemix, collapse = ", "), + cat("Using", paste(x$so@options$nbiter.saemix, collapse = ", "), "iterations and", x$so@options$nb.chains, "chains\n") cat("\nVariance model: ") diff --git a/README.html b/README.html index cdd68210..53303bfc 100644 --- a/README.html +++ b/README.html @@ -367,7 +367,7 @@ pre code { <div id="mkin" class="section level1"> <h1>mkin</h1> -<p><a href="https://cran.r-project.org/package=mkin"><img src="data:image/svg+xml; 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alt="Build Status" /></a> <a href="https://codecov.io/github/jranke/mkin"><img 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alt="Build Status" /></a> <a href="https://codecov.io/github/jranke/mkin"><img src="data:image/svg+xml;base64,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" alt="codecov" /></a></p> <p>The R package <strong>mkin</strong> provides calculation routines for the analysis of chemical degradation data, including <b>m</b>ulticompartment <b>kin</b>etics as needed for modelling the formation and decline of transformation products, or if several degradation compartments are involved.</p> <div id="installation" class="section level2"> <h2>Installation</h2> @@ -396,7 +396,7 @@ pre code { <li>The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.</li> <li>Summary and plotting functions. The <code>summary</code> of an <code>mkinfit</code> object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.</li> <li>The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.</li> -<li>The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) should now be specified as <code>error_model = "obs"</code>.</li> +<li>The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) can be specified as <code>error_model = "obs"</code>.</li> </ul> </div> <div id="unique-in-mkin" class="section level3"> @@ -1,6 +1,7 @@ # mkin [](https://cran.r-project.org/package=mkin) +[](https://jranke.r-universe.dev/ui#package:mkin) [](https://app.travis-ci.com/github/jranke/mkin) [](https://codecov.io/github/jranke/mkin) @@ -1,7 +0,0 @@ -Nice to have: -- Get starting values for formation fractions from data -- Calculate confidence intervals for more than one formation fraction using Monte Carlo simulations -- Calculate confidence intervals for DT50 and DT90 values when only one - parameter is involved -- Calculate transformation only DT50 values (exclude pathways to sink) as - additional information diff --git a/_pkgdown.yml b/_pkgdown.yml index 77cb0323..cf9e292d 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -1,8 +1,8 @@ url: https://pkgdown.jrwb.de/mkin development: - mode: release - version_label: default + mode: devel + version_label: info template: bootswatch: spacelab @@ -17,20 +17,25 @@ reference: - mkinmod - mkinfit - mmkin - - nafta + - mhmkin + - title: Generics + desc: Generic functions introduced by the package + contents: + - parms + - status + - illparms + - endpoints + - aw - title: Show results desc: Functions working with mkinfit objects contents: - plot.mkinfit - summary.mkinfit - - parms.mkinfit - confint.mkinfit - update.mkinfit - lrtest.mkinfit - loftest - mkinerrmin - - endpoints - - aw - CAKE_export - title: Work with mmkin objects desc: Functions working with aggregated results @@ -38,20 +43,27 @@ reference: - "`[.mmkin`" - plot.mmkin - AIC.mmkin + - summary.mmkin - title: Mixed models - desc: Create and work with nonlinear mixed effects models + desc: Create and work with nonlinear hierarchical models contents: - nlme.mmkin - saem.mmkin + - "`[.mhmkin`" - plot.mixed.mmkin - summary.nlme.mmkin - summary.saem.mmkin + - anova.saem.mmkin + - logLik.saem.mmkin - nlme_function - get_deg_func - saemix_model - mixed - intervals - intervals.saem.mmkin + - multistart + - llhist + - parplot - title: Datasets and known results contents: - focus_soil_moisture @@ -79,6 +91,7 @@ reference: - title: Utility functions contents: - f_time_norm_focus + - set_nd_nq - max_twa_parent - mkin_wide_to_long - mkin_long_to_wide @@ -130,10 +143,12 @@ navbar: href: articles/FOCUS_L.html - text: Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models href: articles/web_only/dimethenamid_2018.html - - text: Example evaluation of FOCUS Example Dataset Z - href: articles/web_only/FOCUS_Z.html + - text: Short demo of the multistart method + href: articles/web_only/multistart.html - text: Performance benefit by using compiled model definitions in mkin href: articles/web_only/compiled_models.html + - text: Example evaluation of FOCUS Example Dataset Z + href: articles/web_only/FOCUS_Z.html - text: Calculation of time weighted average concentrations with mkin href: articles/twa.html - text: Example evaluation of NAFTA SOP Attachment examples diff --git a/docs/404.html b/docs/404.html index 7a6ede72..89c41d21 100644 --- a/docs/404.html +++ b/docs/404.html @@ -32,7 +32,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="https://pkgdown.jrwb.de/mkin/index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -124,7 +124,7 @@ Content not found. Please use links in the navbar. <div class="pkgdown"> <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer> diff --git a/docs/articles/index.html b/docs/articles/index.html index 9cdfa9de..c3a39708 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -112,7 +112,7 @@ </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html index 4e0cbba7..0b14fea2 100644 --- a/docs/articles/web_only/benchmarks.html +++ b/docs/articles/web_only/benchmarks.html @@ -33,7 +33,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -105,7 +105,7 @@ <h1 data-toc-skip>Benchmark timings for mkin</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 data-toc-skip class="date">Last change 1 July 2022 (rebuilt 2022-07-12)</h4> + <h4 data-toc-skip class="date">Last change 14 July 2022 (rebuilt 2022-07-22)</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/benchmarks.rmd" class="external-link"><code>vignettes/web_only/benchmarks.rmd</code></a></small> <div class="hidden name"><code>benchmarks.rmd</code></div> @@ -116,20 +116,32 @@ <p>Each system is characterized by the operating system type, the CPU type, the mkin version, and, as in June 2022 the current R version lead to worse performance, the R version. A compiler was available, so if no analytical solution was available, compiled ODE models are used.</p> <p>Every fit is only performed once, so the accuracy of the benchmarks is limited.</p> +<p>The following wrapper function for <code>mmkin</code> is used because the way the error model is specified was changed in mkin version 0.9.49.1.</p> +<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/utils/packageDescription.html" class="external-link">packageVersion</a></span><span class="op">(</span><span class="st">"mkin"</span><span class="op">)</span> <span class="op">></span> <span class="st">"0.9.48.1"</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="va">mmkin_bench</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, <span class="va">error_model</span> <span class="op">=</span> <span class="st">"const"</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, error_model <span class="op">=</span> <span class="va">error_model</span>, cores <span class="op">=</span> <span class="fl">1</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span> <span class="op">}</span></span> +<span><span class="op">}</span> <span class="kw">else</span> <span class="op">{</span></span> +<span> <span class="va">mmkin_bench</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, <span class="va">error_model</span> <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, reweight.method <span class="op">=</span> <span class="va">error_model</span>, cores <span class="op">=</span> <span class="fl">1</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span> <span class="op">}</span></span> +<span><span class="op">}</span></span></code></pre></div> <div class="section level2"> <h2 id="test-cases">Test cases<a class="anchor" aria-label="anchor" href="#test-cases"></a> </h2> <p>Parent only:</p> -<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">FOCUS_C</span> <span class="op"><-</span> <span class="va">FOCUS_2006_C</span></span> <span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span> <span><span class="va">parent_datasets</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_C</span>, <span class="va">FOCUS_D</span><span class="op">)</span></span> <span></span> +<span></span> <span><span class="va">t1</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> <span><span class="va">t2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span>,</span> <span> error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> <p>One metabolite:</p> -<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span></span> <span> parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> <span> m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> @@ -145,7 +157,7 @@ <span><span class="va">t5</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span>,</span> <span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> <p>Two metabolites, synthetic data:</p> -<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> +<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> <code class="sourceCode R"><span><span class="va">m_synth_SFO_lin</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M1"</span><span class="op">)</span>,</span> <span> M1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M2"</span><span class="op">)</span>,</span> <span> M2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> @@ -172,12 +184,6 @@ <span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> <span><span class="va">t11</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span>,</span> <span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> -<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span><span class="va">mkin_benchmarks</span><span class="op">[</span><span class="va">system_string</span>, <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="st">"t"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">11</span><span class="op">)</span><span class="op">]</span> <span class="op"><-</span></span> -<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="va">t1</span>, <span class="va">t2</span>, <span class="va">t3</span>, <span class="va">t4</span>, <span class="va">t5</span>, <span class="va">t6</span>, <span class="va">t7</span>, <span class="va">t8</span>, <span class="va">t9</span>, <span class="va">t10</span>, <span class="va">t11</span><span class="op">)</span></span> -<span><span class="fu"><a href="https://rdrr.io/r/base/save.html" class="external-link">save</a></span><span class="op">(</span><span class="va">mkin_benchmarks</span>, file <span class="op">=</span> <span class="va">benchmark_path</span><span class="op">)</span></span> -<span><span class="co"># Hide rownames from kable for results section</span></span> -<span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">rownames</a></span><span class="op">(</span><span class="va">mkin_benchmarks</span><span class="op">)</span> <span class="op"><-</span> <span class="cn">NULL</span></span></code></pre></div> </div> <div class="section level2"> <h2 id="results">Results<a class="anchor" aria-label="anchor" href="#results"></a> @@ -322,8 +328,16 @@ <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">1.809</td> -<td align="right">3.468</td> +<td align="right">1.770</td> +<td align="right">3.377</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">1.962</td> +<td align="right">3.606</td> </tr> </tbody> </table> @@ -483,9 +497,18 @@ <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">1.336</td> -<td align="right">5.820</td> -<td align="right">2.621</td> +<td align="right">1.308</td> +<td align="right">5.758</td> +<td align="right">2.558</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">1.465</td> +<td align="right">6.184</td> +<td align="right">2.752</td> </tr> </tbody> </table> @@ -693,12 +716,24 @@ <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">0.707</td> -<td align="right">1.148</td> -<td align="right">1.339</td> -<td align="right">2.812</td> -<td align="right">1.752</td> -<td align="right">2.594</td> +<td align="right">0.696</td> +<td align="right">1.124</td> +<td align="right">1.321</td> +<td align="right">2.786</td> +<td align="right">1.744</td> +<td align="right">2.566</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">0.857</td> +<td align="right">1.298</td> +<td align="right">1.504</td> +<td align="right">3.011</td> +<td align="right">1.888</td> +<td align="right">2.756</td> </tr> </tbody> </table> diff --git a/docs/authors.html b/docs/authors.html index afa0d11c..ab436c86 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -109,13 +109,13 @@ <p>Ranke J (2022). <em>mkin: Kinetic Evaluation of Chemical Degradation Data</em>. -R package version 1.1.1, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown.jrwb.de/mkin/</a>. +R package version 1.1.2, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown.jrwb.de/mkin/</a>. </p> <pre>@Manual{, title = {mkin: Kinetic Evaluation of Chemical Degradation Data}, author = {Johannes Ranke}, year = {2022}, - note = {R package version 1.1.1}, + note = {R package version 1.1.2}, url = {https://pkgdown.jrwb.de/mkin/}, }</pre> @@ -130,7 +130,7 @@ R package version 1.1.1, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/articles/FOCUS_L.html b/docs/dev/articles/FOCUS_L.html index 547ec630..43ed0f69 100644 --- a/docs/dev/articles/FOCUS_L.html +++ b/docs/dev/articles/FOCUS_L.html @@ -20,6 +20,8 @@ <![endif]--> </head> <body data-spy="scroll" data-target="#toc"> + + <div class="container template-article"> <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> @@ -32,7 +34,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -42,7 +44,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -58,6 +60,9 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -80,7 +85,7 @@ </ul> <ul class="nav navbar-nav navbar-right"> <li> - <a href="https://github.com/jranke/mkin/"> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> @@ -95,693 +100,693 @@ - </header><script src="FOCUS_L_files/header-attrs-2.6/header-attrs.js"></script><script src="FOCUS_L_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> + </header><script src="FOCUS_L_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> <div class="col-md-9 contents"> <div class="page-header toc-ignore"> <h1 data-toc-skip>Example evaluation of FOCUS Laboratory Data L1 to L3</h1> - <h4 class="author">Johannes Ranke</h4> + <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 class="date">Last change 17 November 2016 (rebuilt 2021-02-15)</h4> + <h4 data-toc-skip class="date">Last change 18 May 2022 (rebuilt 2022-09-16)</h4> - <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/master/vignettes/FOCUS_L.rmd"><code>vignettes/FOCUS_L.rmd</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/FOCUS_L.rmd" class="external-link"><code>vignettes/FOCUS_L.rmd</code></a></small> <div class="hidden name"><code>FOCUS_L.rmd</code></div> </div> -<div id="laboratory-data-l1" class="section level1"> -<h1 class="hasAnchor"> -<a href="#laboratory-data-l1" class="anchor"></a>Laboratory Data L1</h1> +<div class="section level2"> +<h2 id="laboratory-data-l1">Laboratory Data L1<a class="anchor" aria-label="anchor" href="#laboratory-data-l1"></a> +</h2> <p>The following code defines example dataset L1 from the FOCUS kinetics report, p. 284:</p> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="st"><a href="https://pkgdown.jrwb.de/mkin/">"mkin"</a></span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="va">FOCUS_2006_L1</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span> - t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>, <span class="fl">5</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">21</span>, <span class="fl">30</span><span class="op">)</span>, each <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>, - parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">88.3</span>, <span class="fl">91.4</span>, <span class="fl">85.6</span>, <span class="fl">84.5</span>, <span class="fl">78.9</span>, <span class="fl">77.6</span>, - <span class="fl">72.0</span>, <span class="fl">71.9</span>, <span class="fl">50.3</span>, <span class="fl">59.4</span>, <span class="fl">47.0</span>, <span class="fl">45.1</span>, - <span class="fl">27.7</span>, <span class="fl">27.3</span>, <span class="fl">10.0</span>, <span class="fl">10.4</span>, <span class="fl">2.9</span>, <span class="fl">4.0</span><span class="op">)</span><span class="op">)</span> -<span class="va">FOCUS_2006_L1_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L1</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="st"><a href="https://pkgdown.jrwb.de/mkin/">"mkin"</a></span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="va">FOCUS_2006_L1</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> +<span> t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">2</span>, <span class="fl">3</span>, <span class="fl">5</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">21</span>, <span class="fl">30</span><span class="op">)</span>, each <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>,</span> +<span> parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">88.3</span>, <span class="fl">91.4</span>, <span class="fl">85.6</span>, <span class="fl">84.5</span>, <span class="fl">78.9</span>, <span class="fl">77.6</span>,</span> +<span> <span class="fl">72.0</span>, <span class="fl">71.9</span>, <span class="fl">50.3</span>, <span class="fl">59.4</span>, <span class="fl">47.0</span>, <span class="fl">45.1</span>,</span> +<span> <span class="fl">27.7</span>, <span class="fl">27.3</span>, <span class="fl">10.0</span>, <span class="fl">10.4</span>, <span class="fl">2.9</span>, <span class="fl">4.0</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">FOCUS_2006_L1_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L1</span><span class="op">)</span></span></code></pre></div> <p>Here we use the assumptions of simple first order (SFO), the case of declining rate constant over time (FOMC) and the case of two different phases of the kinetics (DFOP). For a more detailed discussion of the models, please see the FOCUS kinetics report.</p> <p>Since mkin version 0.9-32 (July 2014), we can use shorthand notation like <code>"SFO"</code> for parent only degradation models. The following two lines fit the model and produce the summary report of the model fit. This covers the numerical analysis given in the FOCUS report.</p> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m.L1.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">m.L1.SFO</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:39 2021 -## Date of summary: Mon Feb 15 17:13:39 2021 -## -## Equations: -## d_parent/dt = - k_parent * parent -## -## Model predictions using solution type analytical -## -## Fitted using 133 model solutions performed in 0.032 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 89.85 state -## k_parent 0.10 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 89.850000 -Inf Inf -## log_k_parent -2.302585 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 93.88778 96.5589 -43.94389 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 92.470 1.28200 89.740 95.200 -## log_k_parent -2.347 0.03763 -2.428 -2.267 -## sigma 2.780 0.46330 1.792 3.767 -## -## Parameter correlation: -## parent_0 log_k_parent sigma -## parent_0 1.000e+00 6.186e-01 -1.516e-09 -## log_k_parent 6.186e-01 1.000e+00 -3.124e-09 -## sigma -1.516e-09 -3.124e-09 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 92.47000 72.13 8.824e-21 89.74000 95.2000 -## k_parent 0.09561 26.57 2.487e-14 0.08824 0.1036 -## sigma 2.78000 6.00 1.216e-05 1.79200 3.7670 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 3.424 2 7 -## parent 3.424 2 7 -## -## Estimated disappearance times: -## DT50 DT90 -## parent 7.249 24.08 -## -## Data: -## time variable observed predicted residual -## 0 parent 88.3 92.471 -4.1710 -## 0 parent 91.4 92.471 -1.0710 -## 1 parent 85.6 84.039 1.5610 -## 1 parent 84.5 84.039 0.4610 -## 2 parent 78.9 76.376 2.5241 -## 2 parent 77.6 76.376 1.2241 -## 3 parent 72.0 69.412 2.5884 -## 3 parent 71.9 69.412 2.4884 -## 5 parent 50.3 57.330 -7.0301 -## 5 parent 59.4 57.330 2.0699 -## 7 parent 47.0 47.352 -0.3515 -## 7 parent 45.1 47.352 -2.2515 -## 14 parent 27.7 24.247 3.4528 -## 14 parent 27.3 24.247 3.0528 -## 21 parent 10.0 12.416 -2.4163 -## 21 parent 10.4 12.416 -2.0163 -## 30 parent 2.9 5.251 -2.3513 -## 30 parent 4.0 5.251 -1.2513</code></pre> +<code class="sourceCode R"><span><span class="va">m.L1.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L1.SFO</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:35 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:35 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - k_parent * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 133 model solutions performed in 0.032 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 89.85 state</span></span> +<span><span class="co">## k_parent 0.10 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 89.850000 -Inf Inf</span></span> +<span><span class="co">## log_k_parent -2.302585 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 93.88778 96.5589 -43.94389</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 92.470 1.28200 89.740 95.200</span></span> +<span><span class="co">## log_k_parent -2.347 0.03763 -2.428 -2.267</span></span> +<span><span class="co">## sigma 2.780 0.46330 1.792 3.767</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_k_parent sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 6.186e-01 -1.516e-09</span></span> +<span><span class="co">## log_k_parent 6.186e-01 1.000e+00 -3.124e-09</span></span> +<span><span class="co">## sigma -1.516e-09 -3.124e-09 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 92.47000 72.13 8.824e-21 89.74000 95.2000</span></span> +<span><span class="co">## k_parent 0.09561 26.57 2.487e-14 0.08824 0.1036</span></span> +<span><span class="co">## sigma 2.78000 6.00 1.216e-05 1.79200 3.7670</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 3.424 2 7</span></span> +<span><span class="co">## parent 3.424 2 7</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90</span></span> +<span><span class="co">## parent 7.249 24.08</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Data:</span></span> +<span><span class="co">## time variable observed predicted residual</span></span> +<span><span class="co">## 0 parent 88.3 92.471 -4.1710</span></span> +<span><span class="co">## 0 parent 91.4 92.471 -1.0710</span></span> +<span><span class="co">## 1 parent 85.6 84.039 1.5610</span></span> +<span><span class="co">## 1 parent 84.5 84.039 0.4610</span></span> +<span><span class="co">## 2 parent 78.9 76.376 2.5241</span></span> +<span><span class="co">## 2 parent 77.6 76.376 1.2241</span></span> +<span><span class="co">## 3 parent 72.0 69.412 2.5884</span></span> +<span><span class="co">## 3 parent 71.9 69.412 2.4884</span></span> +<span><span class="co">## 5 parent 50.3 57.330 -7.0301</span></span> +<span><span class="co">## 5 parent 59.4 57.330 2.0699</span></span> +<span><span class="co">## 7 parent 47.0 47.352 -0.3515</span></span> +<span><span class="co">## 7 parent 45.1 47.352 -2.2515</span></span> +<span><span class="co">## 14 parent 27.7 24.247 3.4528</span></span> +<span><span class="co">## 14 parent 27.3 24.247 3.0528</span></span> +<span><span class="co">## 21 parent 10.0 12.416 -2.4163</span></span> +<span><span class="co">## 21 parent 10.4 12.416 -2.0163</span></span> +<span><span class="co">## 30 parent 2.9 5.251 -2.3513</span></span> +<span><span class="co">## 30 parent 4.0 5.251 -1.2513</span></span></code></pre> <p>A plot of the fit is obtained with the plot function for mkinfit objects.</p> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">m.L1.SFO</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, main <span class="op">=</span> <span class="st">"FOCUS L1 - SFO"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L1.SFO</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, main <span class="op">=</span> <span class="st">"FOCUS L1 - SFO"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-4-1.png" width="576"></p> <p>The residual plot can be easily obtained by</p> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="../reference/mkinresplot.html">mkinresplot</a></span><span class="op">(</span><span class="va">m.L1.SFO</span>, ylab <span class="op">=</span> <span class="st">"Observed"</span>, xlab <span class="op">=</span> <span class="st">"Time"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="../reference/mkinresplot.html">mkinresplot</a></span><span class="op">(</span><span class="va">m.L1.SFO</span>, ylab <span class="op">=</span> <span class="st">"Observed"</span>, xlab <span class="op">=</span> <span class="st">"Time"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-5-1.png" width="576"></p> <p>For comparison, the FOMC model is fitted as well, and the <span class="math inline">\(\chi^2\)</span> error level is checked.</p> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m.L1.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></code></pre></div> -<pre><code>## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge: -## false convergence (8)</code></pre> +<code class="sourceCode R"><span><span class="va">m.L1.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L1_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge:</span></span> +<span><span class="co">## false convergence (8)</span></span></code></pre> <div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">m.L1.FOMC</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, main <span class="op">=</span> <span class="st">"FOCUS L1 - FOMC"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L1.FOMC</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, main <span class="op">=</span> <span class="st">"FOCUS L1 - FOMC"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-6-1.png" width="576"></p> <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">m.L1.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> -<pre><code>## Warning in sqrt(diag(covar)): NaNs produced</code></pre> -<pre><code>## Warning in sqrt(1/diag(V)): NaNs produced</code></pre> -<pre><code>## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is -## doubtful</code></pre> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:40 2021 -## Date of summary: Mon Feb 15 17:13:40 2021 -## -## Equations: -## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -## -## Model predictions using solution type analytical -## -## Fitted using 369 model solutions performed in 0.084 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 89.85 state -## alpha 1.00 deparm -## beta 10.00 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 89.850000 -Inf Inf -## log_alpha 0.000000 -Inf Inf -## log_beta 2.302585 -Inf Inf -## -## Fixed parameter values: -## None -## -## -## Warning(s): -## Optimisation did not converge: -## false convergence (8) -## -## Results: -## -## AIC BIC logLik -## 95.88781 99.44929 -43.9439 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 92.47 1.2820 89.720 95.220 -## log_alpha 13.78 NaN NaN NaN -## log_beta 16.13 NaN NaN NaN -## sigma 2.78 0.4598 1.794 3.766 -## -## Parameter correlation: -## parent_0 log_alpha log_beta sigma -## parent_0 1.0000000 NaN NaN 0.0001671 -## log_alpha NaN 1 NaN NaN -## log_beta NaN NaN 1 NaN -## sigma 0.0001671 NaN NaN 1.0000000 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 9.247e+01 NA NA 89.720 95.220 -## alpha 9.658e+05 NA NA NA NA -## beta 1.010e+07 NA NA NA NA -## sigma 2.780e+00 NA NA 1.794 3.766 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 3.619 3 6 -## parent 3.619 3 6 -## -## Estimated disappearance times: -## DT50 DT90 DT50back -## parent 7.25 24.08 7.25</code></pre> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L1.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## Warning in sqrt(diag(covar)): NaNs produced</span></span></code></pre> +<pre><code><span><span class="co">## Warning in sqrt(1/diag(V)): NaNs produced</span></span></code></pre> +<pre><code><span><span class="co">## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is</span></span> +<span><span class="co">## doubtful</span></span></code></pre> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:36 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:36 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 369 model solutions performed in 0.081 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 89.85 state</span></span> +<span><span class="co">## alpha 1.00 deparm</span></span> +<span><span class="co">## beta 10.00 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 89.850000 -Inf Inf</span></span> +<span><span class="co">## log_alpha 0.000000 -Inf Inf</span></span> +<span><span class="co">## log_beta 2.302585 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Warning(s): </span></span> +<span><span class="co">## Optimisation did not converge:</span></span> +<span><span class="co">## false convergence (8)</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 95.88781 99.44929 -43.9439</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 92.47 1.2820 89.720 95.220</span></span> +<span><span class="co">## log_alpha 13.78 NaN NaN NaN</span></span> +<span><span class="co">## log_beta 16.13 NaN NaN NaN</span></span> +<span><span class="co">## sigma 2.78 0.4598 1.794 3.766</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_alpha log_beta sigma</span></span> +<span><span class="co">## parent_0 1.0000000 NaN NaN 0.0001671</span></span> +<span><span class="co">## log_alpha NaN 1 NaN NaN</span></span> +<span><span class="co">## log_beta NaN NaN 1 NaN</span></span> +<span><span class="co">## sigma 0.0001671 NaN NaN 1.0000000</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 9.247e+01 NA NA 89.720 95.220</span></span> +<span><span class="co">## alpha 9.658e+05 NA NA NA NA</span></span> +<span><span class="co">## beta 1.010e+07 NA NA NA NA</span></span> +<span><span class="co">## sigma 2.780e+00 NA NA 1.794 3.766</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 3.619 3 6</span></span> +<span><span class="co">## parent 3.619 3 6</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90 DT50back</span></span> +<span><span class="co">## parent 7.25 24.08 7.25</span></span></code></pre> <p>We get a warning that the default optimisation algorithm <code>Port</code> did not converge, which is an indication that the model is overparameterised, <em>i.e.</em> contains too many parameters that are ill-defined as a consequence.</p> <p>And in fact, due to the higher number of parameters, and the lower number of degrees of freedom of the fit, the <span class="math inline">\(\chi^2\)</span> error level is actually higher for the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the parameters <code>log_alpha</code> and <code>log_beta</code> internally fitted in the model have excessive confidence intervals, that span more than 25 orders of magnitude (!) when backtransformed to the scale of <code>alpha</code> and <code>beta</code>. Also, the t-test for significant difference from zero does not indicate such a significant difference, with p-values greater than 0.1, and finally, the parameter correlation of <code>log_alpha</code> and <code>log_beta</code> is 1.000, clearly indicating that the model is overparameterised.</p> <p>The <span class="math inline">\(\chi^2\)</span> error levels reported in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to integer percentages and partly deviate by one percentage point from the results calculated by mkin. The reason for this is not known. However, mkin gives the same <span class="math inline">\(\chi^2\)</span> error levels as the kinfit package and the calculation routines of the kinfit package have been extensively compared to the results obtained by the KinGUI software, as documented in the kinfit package vignette. KinGUI was the first widely used standard package in this field. Also, the calculation of <span class="math inline">\(\chi^2\)</span> error levels was compared with KinGUII, CAKE and DegKin manager in a project sponsored by the German Umweltbundesamt <span class="citation">(Ranke 2014)</span>.</p> </div> -<div id="laboratory-data-l2" class="section level1"> -<h1 class="hasAnchor"> -<a href="#laboratory-data-l2" class="anchor"></a>Laboratory Data L2</h1> +<div class="section level2"> +<h2 id="laboratory-data-l2">Laboratory Data L2<a class="anchor" aria-label="anchor" href="#laboratory-data-l2"></a> +</h2> <p>The following code defines example dataset L2 from the FOCUS kinetics report, p. 287:</p> <div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">FOCUS_2006_L2</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span> - t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html">rep</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span><span class="op">)</span>, each <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>, - parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">96.1</span>, <span class="fl">91.8</span>, <span class="fl">41.4</span>, <span class="fl">38.7</span>, - <span class="fl">19.3</span>, <span class="fl">22.3</span>, <span class="fl">4.6</span>, <span class="fl">4.6</span>, - <span class="fl">2.6</span>, <span class="fl">1.2</span>, <span class="fl">0.3</span>, <span class="fl">0.6</span><span class="op">)</span><span class="op">)</span> -<span class="va">FOCUS_2006_L2_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L2</span><span class="op">)</span></code></pre></div> -<div id="sfo-fit-for-l2" class="section level2"> -<h2 class="hasAnchor"> -<a href="#sfo-fit-for-l2" class="anchor"></a>SFO fit for L2</h2> +<code class="sourceCode R"><span><span class="va">FOCUS_2006_L2</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> +<span> t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span><span class="op">)</span>, each <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>,</span> +<span> parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">96.1</span>, <span class="fl">91.8</span>, <span class="fl">41.4</span>, <span class="fl">38.7</span>,</span> +<span> <span class="fl">19.3</span>, <span class="fl">22.3</span>, <span class="fl">4.6</span>, <span class="fl">4.6</span>,</span> +<span> <span class="fl">2.6</span>, <span class="fl">1.2</span>, <span class="fl">0.3</span>, <span class="fl">0.6</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">FOCUS_2006_L2_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L2</span><span class="op">)</span></span></code></pre></div> +<div class="section level3"> +<h3 id="sfo-fit-for-l2">SFO fit for L2<a class="anchor" aria-label="anchor" href="#sfo-fit-for-l2"></a> +</h3> <p>Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument <code>show_residuals</code> to the plot command.</p> <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m.L2.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">m.L2.SFO</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, - main <span class="op">=</span> <span class="st">"FOCUS L2 - SFO"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">m.L2.SFO</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet<span class="op">=</span><span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.SFO</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> main <span class="op">=</span> <span class="st">"FOCUS L2 - SFO"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-8-1.png" width="672"></p> <p>The <span class="math inline">\(\chi^2\)</span> error level of 14% suggests that the model does not fit very well. This is also obvious from the plots of the fit, in which we have included the residual plot.</p> <p>In the FOCUS kinetics report, it is stated that there is no apparent systematic error observed from the residual plot up to the measured DT90 (approximately at day 5), and there is an underestimation beyond that point.</p> <p>We may add that it is difficult to judge the random nature of the residuals just from the three samplings at days 0, 1 and 3. Also, it is not clear <em>a priori</em> why a consistent underestimation after the approximate DT90 should be irrelevant. However, this can be rationalised by the fact that the FOCUS fate models generally only implement SFO kinetics.</p> </div> -<div id="fomc-fit-for-l2" class="section level2"> -<h2 class="hasAnchor"> -<a href="#fomc-fit-for-l2" class="anchor"></a>FOMC fit for L2</h2> +<div class="section level3"> +<h3 id="fomc-fit-for-l2">FOMC fit for L2<a class="anchor" aria-label="anchor" href="#fomc-fit-for-l2"></a> +</h3> <p>For comparison, the FOMC model is fitted as well, and the <span class="math inline">\(\chi^2\)</span> error level is checked.</p> <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m.L2.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, - main <span class="op">=</span> <span class="st">"FOCUS L2 - FOMC"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">m.L2.FOMC</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> main <span class="op">=</span> <span class="st">"FOCUS L2 - FOMC"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-9-1.png" width="672"></p> <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:40 2021 -## Date of summary: Mon Feb 15 17:13:40 2021 -## -## Equations: -## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -## -## Model predictions using solution type analytical -## -## Fitted using 239 model solutions performed in 0.05 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 93.95 state -## alpha 1.00 deparm -## beta 10.00 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 93.950000 -Inf Inf -## log_alpha 0.000000 -Inf Inf -## log_beta 2.302585 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 61.78966 63.72928 -26.89483 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 93.7700 1.6130 90.05000 97.4900 -## log_alpha 0.3180 0.1559 -0.04149 0.6776 -## log_beta 0.2102 0.2493 -0.36460 0.7850 -## sigma 2.2760 0.4645 1.20500 3.3470 -## -## Parameter correlation: -## parent_0 log_alpha log_beta sigma -## parent_0 1.000e+00 -1.151e-01 -2.085e-01 -7.828e-09 -## log_alpha -1.151e-01 1.000e+00 9.741e-01 -1.602e-07 -## log_beta -2.085e-01 9.741e-01 1.000e+00 -1.372e-07 -## sigma -7.828e-09 -1.602e-07 -1.372e-07 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 93.770 58.120 4.267e-12 90.0500 97.490 -## alpha 1.374 6.414 1.030e-04 0.9594 1.969 -## beta 1.234 4.012 1.942e-03 0.6945 2.192 -## sigma 2.276 4.899 5.977e-04 1.2050 3.347 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 6.205 3 3 -## parent 6.205 3 3 -## -## Estimated disappearance times: -## DT50 DT90 DT50back -## parent 0.8092 5.356 1.612</code></pre> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L2.FOMC</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:36 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:36 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 239 model solutions performed in 0.049 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 93.95 state</span></span> +<span><span class="co">## alpha 1.00 deparm</span></span> +<span><span class="co">## beta 10.00 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 93.950000 -Inf Inf</span></span> +<span><span class="co">## log_alpha 0.000000 -Inf Inf</span></span> +<span><span class="co">## log_beta 2.302585 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 61.78966 63.72928 -26.89483</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 93.7700 1.6130 90.05000 97.4900</span></span> +<span><span class="co">## log_alpha 0.3180 0.1559 -0.04149 0.6776</span></span> +<span><span class="co">## log_beta 0.2102 0.2493 -0.36460 0.7850</span></span> +<span><span class="co">## sigma 2.2760 0.4645 1.20500 3.3470</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_alpha log_beta sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 -1.151e-01 -2.085e-01 -7.828e-09</span></span> +<span><span class="co">## log_alpha -1.151e-01 1.000e+00 9.741e-01 -1.602e-07</span></span> +<span><span class="co">## log_beta -2.085e-01 9.741e-01 1.000e+00 -1.372e-07</span></span> +<span><span class="co">## sigma -7.828e-09 -1.602e-07 -1.372e-07 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 93.770 58.120 4.267e-12 90.0500 97.490</span></span> +<span><span class="co">## alpha 1.374 6.414 1.030e-04 0.9594 1.969</span></span> +<span><span class="co">## beta 1.234 4.012 1.942e-03 0.6945 2.192</span></span> +<span><span class="co">## sigma 2.276 4.899 5.977e-04 1.2050 3.347</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 6.205 3 3</span></span> +<span><span class="co">## parent 6.205 3 3</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90 DT50back</span></span> +<span><span class="co">## parent 0.8092 5.356 1.612</span></span></code></pre> <p>The error level at which the <span class="math inline">\(\chi^2\)</span> test passes is much lower in this case. Therefore, the FOMC model provides a better description of the data, as less experimental error has to be assumed in order to explain the data.</p> </div> -<div id="dfop-fit-for-l2" class="section level2"> -<h2 class="hasAnchor"> -<a href="#dfop-fit-for-l2" class="anchor"></a>DFOP fit for L2</h2> +<div class="section level3"> +<h3 id="dfop-fit-for-l2">DFOP fit for L2<a class="anchor" aria-label="anchor" href="#dfop-fit-for-l2"></a> +</h3> <p>Fitting the four parameter DFOP model further reduces the <span class="math inline">\(\chi^2\)</span> error level.</p> <div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m.L2.DFOP</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>, - main <span class="op">=</span> <span class="st">"FOCUS L2 - DFOP"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">m.L2.DFOP</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_L2_mkin</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> main <span class="op">=</span> <span class="st">"FOCUS L2 - DFOP"</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-10-1.png" width="672"></p> <div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:41 2021 -## Date of summary: Mon Feb 15 17:13:41 2021 -## -## Equations: -## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * -## time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) -## * parent -## -## Model predictions using solution type analytical -## -## Fitted using 581 model solutions performed in 0.134 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 93.95 state -## k1 0.10 deparm -## k2 0.01 deparm -## g 0.50 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 93.950000 -Inf Inf -## log_k1 -2.302585 -Inf Inf -## log_k2 -4.605170 -Inf Inf -## g_qlogis 0.000000 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 52.36695 54.79148 -21.18347 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 93.950 9.998e-01 91.5900 96.3100 -## log_k1 3.112 1.842e+03 -4353.0000 4359.0000 -## log_k2 -1.088 6.285e-02 -1.2370 -0.9394 -## g_qlogis -0.399 9.946e-02 -0.6342 -0.1638 -## sigma 1.414 2.886e-01 0.7314 2.0960 -## -## Parameter correlation: -## parent_0 log_k1 log_k2 g_qlogis sigma -## parent_0 1.000e+00 6.783e-07 -3.390e-10 2.665e-01 -2.967e-10 -## log_k1 6.783e-07 1.000e+00 1.116e-04 -2.196e-04 -1.031e-05 -## log_k2 -3.390e-10 1.116e-04 1.000e+00 -7.903e-01 2.917e-09 -## g_qlogis 2.665e-01 -2.196e-04 -7.903e-01 1.000e+00 -4.408e-09 -## sigma -2.967e-10 -1.031e-05 2.917e-09 -4.408e-09 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 93.9500 9.397e+01 2.036e-12 91.5900 96.3100 -## k1 22.4800 5.553e-04 4.998e-01 0.0000 Inf -## k2 0.3369 1.591e+01 4.697e-07 0.2904 0.3909 -## g 0.4016 1.680e+01 3.238e-07 0.3466 0.4591 -## sigma 1.4140 4.899e+00 8.776e-04 0.7314 2.0960 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 2.53 4 2 -## parent 2.53 4 2 -## -## Estimated disappearance times: -## DT50 DT90 DT50back DT50_k1 DT50_k2 -## parent 0.5335 5.311 1.599 0.03084 2.058</code></pre> -<p>Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion. However, the failure to calculate the covariance matrix indicates that the parameter estimates correlate excessively. Therefore, the FOMC model may be preferred for this dataset.</p> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">m.L2.DFOP</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:37 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:37 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span></span> +<span><span class="co">## time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span></span> +<span><span class="co">## * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 581 model solutions performed in 0.132 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 93.95 state</span></span> +<span><span class="co">## k1 0.10 deparm</span></span> +<span><span class="co">## k2 0.01 deparm</span></span> +<span><span class="co">## g 0.50 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 93.950000 -Inf Inf</span></span> +<span><span class="co">## log_k1 -2.302585 -Inf Inf</span></span> +<span><span class="co">## log_k2 -4.605170 -Inf Inf</span></span> +<span><span class="co">## g_qlogis 0.000000 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 52.36695 54.79148 -21.18347</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 93.950 9.998e-01 91.5900 96.3100</span></span> +<span><span class="co">## log_k1 3.112 1.842e+03 -4353.0000 4359.0000</span></span> +<span><span class="co">## log_k2 -1.088 6.285e-02 -1.2370 -0.9394</span></span> +<span><span class="co">## g_qlogis -0.399 9.946e-02 -0.6342 -0.1638</span></span> +<span><span class="co">## sigma 1.414 2.886e-01 0.7314 2.0960</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_k1 log_k2 g_qlogis sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 6.783e-07 -3.390e-10 2.665e-01 -2.967e-10</span></span> +<span><span class="co">## log_k1 6.783e-07 1.000e+00 1.116e-04 -2.196e-04 -1.031e-05</span></span> +<span><span class="co">## log_k2 -3.390e-10 1.116e-04 1.000e+00 -7.903e-01 2.917e-09</span></span> +<span><span class="co">## g_qlogis 2.665e-01 -2.196e-04 -7.903e-01 1.000e+00 -4.408e-09</span></span> +<span><span class="co">## sigma -2.967e-10 -1.031e-05 2.917e-09 -4.408e-09 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 93.9500 9.397e+01 2.036e-12 91.5900 96.3100</span></span> +<span><span class="co">## k1 22.4800 5.553e-04 4.998e-01 0.0000 Inf</span></span> +<span><span class="co">## k2 0.3369 1.591e+01 4.697e-07 0.2904 0.3909</span></span> +<span><span class="co">## g 0.4016 1.680e+01 3.238e-07 0.3466 0.4591</span></span> +<span><span class="co">## sigma 1.4140 4.899e+00 8.776e-04 0.7314 2.0960</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 2.53 4 2</span></span> +<span><span class="co">## parent 2.53 4 2</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90 DT50back DT50_k1 DT50_k2</span></span> +<span><span class="co">## parent 0.5335 5.311 1.599 0.03084 2.058</span></span></code></pre> +<p>Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion.</p> </div> </div> -<div id="laboratory-data-l3" class="section level1"> -<h1 class="hasAnchor"> -<a href="#laboratory-data-l3" class="anchor"></a>Laboratory Data L3</h1> +<div class="section level2"> +<h2 id="laboratory-data-l3">Laboratory Data L3<a class="anchor" aria-label="anchor" href="#laboratory-data-l3"></a> +</h2> <p>The following code defines example dataset L3 from the FOCUS kinetics report, p. 290.</p> <div class="sourceCode" id="cb22"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">FOCUS_2006_L3</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span> - t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>, - parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">97.8</span>, <span class="fl">60</span>, <span class="fl">51</span>, <span class="fl">43</span>, <span class="fl">35</span>, <span class="fl">22</span>, <span class="fl">15</span>, <span class="fl">12</span><span class="op">)</span><span class="op">)</span> -<span class="va">FOCUS_2006_L3_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L3</span><span class="op">)</span></code></pre></div> -<div id="fit-multiple-models" class="section level2"> -<h2 class="hasAnchor"> -<a href="#fit-multiple-models" class="anchor"></a>Fit multiple models</h2> +<code class="sourceCode R"><span><span class="va">FOCUS_2006_L3</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> +<span> t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>,</span> +<span> parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">97.8</span>, <span class="fl">60</span>, <span class="fl">51</span>, <span class="fl">43</span>, <span class="fl">35</span>, <span class="fl">22</span>, <span class="fl">15</span>, <span class="fl">12</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">FOCUS_2006_L3_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L3</span><span class="op">)</span></span></code></pre></div> +<div class="section level3"> +<h3 id="fit-multiple-models">Fit multiple models<a class="anchor" aria-label="anchor" href="#fit-multiple-models"></a> +</h3> <p>As of mkin version 0.9-39 (June 2015), we can fit several models to one or more datasets in one call to the function <code>mmkin</code>. The datasets have to be passed in a list, in this case a named list holding only the L3 dataset prepared above.</p> <div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="co"># Only use one core here, not to offend the CRAN checks</span> -<span class="va">mm.L3</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>, - <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="st">"FOCUS L3"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L3_mkin</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="co"># Only use one core here, not to offend the CRAN checks</span></span> +<span><span class="va">mm.L3</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>,</span> +<span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS L3"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L3_mkin</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-12-1.png" width="700"></p> <p>The <span class="math inline">\(\chi^2\)</span> error level of 21% as well as the plot suggest that the SFO model does not fit very well. The FOMC model performs better, with an error level at which the <span class="math inline">\(\chi^2\)</span> test passes of 7%. Fitting the four parameter DFOP model further reduces the <span class="math inline">\(\chi^2\)</span> error level considerably.</p> </div> -<div id="accessing-mmkin-objects" class="section level2"> -<h2 class="hasAnchor"> -<a href="#accessing-mmkin-objects" class="anchor"></a>Accessing mmkin objects</h2> +<div class="section level3"> +<h3 id="accessing-mmkin-objects">Accessing mmkin objects<a class="anchor" aria-label="anchor" href="#accessing-mmkin-objects"></a> +</h3> <p>The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index.</p> <p>We can extract the summary and plot for <em>e.g.</em> the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.</p> <div class="sourceCode" id="cb24"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:41 2021 -## Date of summary: Mon Feb 15 17:13:42 2021 -## -## Equations: -## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * -## time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) -## * parent -## -## Model predictions using solution type analytical -## -## Fitted using 376 model solutions performed in 0.082 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 97.80 state -## k1 0.10 deparm -## k2 0.01 deparm -## g 0.50 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 97.800000 -Inf Inf -## log_k1 -2.302585 -Inf Inf -## log_k2 -4.605170 -Inf Inf -## g_qlogis 0.000000 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 32.97732 33.37453 -11.48866 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 97.7500 1.01900 94.5000 101.000000 -## log_k1 -0.6612 0.10050 -0.9812 -0.341300 -## log_k2 -4.2860 0.04322 -4.4230 -4.148000 -## g_qlogis -0.1739 0.05270 -0.3416 -0.006142 -## sigma 1.0170 0.25430 0.2079 1.827000 -## -## Parameter correlation: -## parent_0 log_k1 log_k2 g_qlogis sigma -## parent_0 1.000e+00 1.732e-01 2.282e-02 4.009e-01 -9.664e-08 -## log_k1 1.732e-01 1.000e+00 4.945e-01 -5.809e-01 7.147e-07 -## log_k2 2.282e-02 4.945e-01 1.000e+00 -6.812e-01 1.022e-06 -## g_qlogis 4.009e-01 -5.809e-01 -6.812e-01 1.000e+00 -7.926e-07 -## sigma -9.664e-08 7.147e-07 1.022e-06 -7.926e-07 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 97.75000 95.960 1.248e-06 94.50000 101.00000 -## k1 0.51620 9.947 1.081e-03 0.37490 0.71090 -## k2 0.01376 23.140 8.840e-05 0.01199 0.01579 -## g 0.45660 34.920 2.581e-05 0.41540 0.49850 -## sigma 1.01700 4.000 1.400e-02 0.20790 1.82700 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 2.225 4 4 -## parent 2.225 4 4 -## -## Estimated disappearance times: -## DT50 DT90 DT50back DT50_k1 DT50_k2 -## parent 7.464 123 37.03 1.343 50.37 -## -## Data: -## time variable observed predicted residual -## 0 parent 97.8 97.75 0.05396 -## 3 parent 60.0 60.45 -0.44933 -## 7 parent 51.0 49.44 1.56338 -## 14 parent 43.0 43.84 -0.83632 -## 30 parent 35.0 35.15 -0.14707 -## 60 parent 22.0 23.26 -1.25919 -## 91 parent 15.0 15.18 -0.18181 -## 120 parent 12.0 10.19 1.81395</code></pre> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:37 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:38 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span></span> +<span><span class="co">## time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span></span> +<span><span class="co">## * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 376 model solutions performed in 0.079 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 97.80 state</span></span> +<span><span class="co">## k1 0.10 deparm</span></span> +<span><span class="co">## k2 0.01 deparm</span></span> +<span><span class="co">## g 0.50 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 97.800000 -Inf Inf</span></span> +<span><span class="co">## log_k1 -2.302585 -Inf Inf</span></span> +<span><span class="co">## log_k2 -4.605170 -Inf Inf</span></span> +<span><span class="co">## g_qlogis 0.000000 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 32.97732 33.37453 -11.48866</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 97.7500 1.01900 94.5000 101.000000</span></span> +<span><span class="co">## log_k1 -0.6612 0.10050 -0.9812 -0.341300</span></span> +<span><span class="co">## log_k2 -4.2860 0.04322 -4.4230 -4.148000</span></span> +<span><span class="co">## g_qlogis -0.1739 0.05270 -0.3416 -0.006142</span></span> +<span><span class="co">## sigma 1.0170 0.25430 0.2079 1.827000</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_k1 log_k2 g_qlogis sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 1.732e-01 2.282e-02 4.009e-01 -9.664e-08</span></span> +<span><span class="co">## log_k1 1.732e-01 1.000e+00 4.945e-01 -5.809e-01 7.147e-07</span></span> +<span><span class="co">## log_k2 2.282e-02 4.945e-01 1.000e+00 -6.812e-01 1.022e-06</span></span> +<span><span class="co">## g_qlogis 4.009e-01 -5.809e-01 -6.812e-01 1.000e+00 -7.926e-07</span></span> +<span><span class="co">## sigma -9.664e-08 7.147e-07 1.022e-06 -7.926e-07 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 97.75000 95.960 1.248e-06 94.50000 101.00000</span></span> +<span><span class="co">## k1 0.51620 9.947 1.081e-03 0.37490 0.71090</span></span> +<span><span class="co">## k2 0.01376 23.140 8.840e-05 0.01199 0.01579</span></span> +<span><span class="co">## g 0.45660 34.920 2.581e-05 0.41540 0.49850</span></span> +<span><span class="co">## sigma 1.01700 4.000 1.400e-02 0.20790 1.82700</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 2.225 4 4</span></span> +<span><span class="co">## parent 2.225 4 4</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90 DT50back DT50_k1 DT50_k2</span></span> +<span><span class="co">## parent 7.464 123 37.03 1.343 50.37</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Data:</span></span> +<span><span class="co">## time variable observed predicted residual</span></span> +<span><span class="co">## 0 parent 97.8 97.75 0.05396</span></span> +<span><span class="co">## 3 parent 60.0 60.45 -0.44933</span></span> +<span><span class="co">## 7 parent 51.0 49.44 1.56338</span></span> +<span><span class="co">## 14 parent 43.0 43.84 -0.83632</span></span> +<span><span class="co">## 30 parent 35.0 35.15 -0.14707</span></span> +<span><span class="co">## 60 parent 22.0 23.26 -1.25919</span></span> +<span><span class="co">## 91 parent 15.0 15.18 -0.18181</span></span> +<span><span class="co">## 120 parent 12.0 10.19 1.81395</span></span></code></pre> <div class="sourceCode" id="cb26"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L3</span><span class="op">[[</span><span class="st">"DFOP"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, show_errmin <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-13-1.png" width="700"></p> <p>Here, a look to the model plot, the confidence intervals of the parameters and the correlation matrix suggest that the parameter estimates are reliable, and the DFOP model can be used as the best-fit model based on the <span class="math inline">\(\chi^2\)</span> error level criterion for laboratory data L3.</p> <p>This is also an example where the standard t-test for the parameter <code>g_ilr</code> is misleading, as it tests for a significant difference from zero. In this case, zero appears to be the correct value for this parameter, and the confidence interval for the backtransformed parameter <code>g</code> is quite narrow.</p> </div> </div> -<div id="laboratory-data-l4" class="section level1"> -<h1 class="hasAnchor"> -<a href="#laboratory-data-l4" class="anchor"></a>Laboratory Data L4</h1> +<div class="section level2"> +<h2 id="laboratory-data-l4">Laboratory Data L4<a class="anchor" aria-label="anchor" href="#laboratory-data-l4"></a> +</h2> <p>The following code defines example dataset L4 from the FOCUS kinetics report, p. 293:</p> <div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">FOCUS_2006_L4</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span> - t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>, - parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">96.6</span>, <span class="fl">96.3</span>, <span class="fl">94.3</span>, <span class="fl">88.8</span>, <span class="fl">74.9</span>, <span class="fl">59.9</span>, <span class="fl">53.5</span>, <span class="fl">49.0</span><span class="op">)</span><span class="op">)</span> -<span class="va">FOCUS_2006_L4_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L4</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">FOCUS_2006_L4</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> +<span> t <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">30</span>, <span class="fl">60</span>, <span class="fl">91</span>, <span class="fl">120</span><span class="op">)</span>,</span> +<span> parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">96.6</span>, <span class="fl">96.3</span>, <span class="fl">94.3</span>, <span class="fl">88.8</span>, <span class="fl">74.9</span>, <span class="fl">59.9</span>, <span class="fl">53.5</span>, <span class="fl">49.0</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">FOCUS_2006_L4_mkin</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mkin_wide_to_long.html">mkin_wide_to_long</a></span><span class="op">(</span><span class="va">FOCUS_2006_L4</span><span class="op">)</span></span></code></pre></div> <p>Fits of the SFO and FOMC models, plots and summaries are produced below:</p> <div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="co"># Only use one core here, not to offend the CRAN checks</span> -<span class="va">mm.L4</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>, - <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="st">"FOCUS L4"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L4_mkin</span><span class="op">)</span>, - quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html">plot</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="co"># Only use one core here, not to offend the CRAN checks</span></span> +<span><span class="va">mm.L4</span> <span class="op"><-</span> <span class="fu"><a href="../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>,</span> +<span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS L4"</span> <span class="op">=</span> <span class="va">FOCUS_2006_L4_mkin</span><span class="op">)</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">)</span></span></code></pre></div> <p><img src="FOCUS_L_files/figure-html/unnamed-chunk-15-1.png" width="700"></p> <p>The <span class="math inline">\(\chi^2\)</span> error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the <span class="math inline">\(\chi^2\)</span> test passes is slightly lower for the FOMC model. However, the difference appears negligible.</p> <div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"SFO"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:42 2021 -## Date of summary: Mon Feb 15 17:13:42 2021 -## -## Equations: -## d_parent/dt = - k_parent * parent -## -## Model predictions using solution type analytical -## -## Fitted using 142 model solutions performed in 0.03 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 96.6 state -## k_parent 0.1 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 96.600000 -Inf Inf -## log_k_parent -2.302585 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 47.12133 47.35966 -20.56067 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 96.440 1.69900 92.070 100.800 -## log_k_parent -5.030 0.07059 -5.211 -4.848 -## sigma 3.162 0.79050 1.130 5.194 -## -## Parameter correlation: -## parent_0 log_k_parent sigma -## parent_0 1.000e+00 5.938e-01 3.387e-07 -## log_k_parent 5.938e-01 1.000e+00 5.830e-07 -## sigma 3.387e-07 5.830e-07 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 96.440000 56.77 1.604e-08 92.070000 1.008e+02 -## k_parent 0.006541 14.17 1.578e-05 0.005455 7.842e-03 -## sigma 3.162000 4.00 5.162e-03 1.130000 5.194e+00 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 3.287 2 6 -## parent 3.287 2 6 -## -## Estimated disappearance times: -## DT50 DT90 -## parent 106 352</code></pre> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"SFO"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:38 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:38 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - k_parent * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 142 model solutions performed in 0.03 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 96.6 state</span></span> +<span><span class="co">## k_parent 0.1 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 96.600000 -Inf Inf</span></span> +<span><span class="co">## log_k_parent -2.302585 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 47.12133 47.35966 -20.56067</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 96.440 1.69900 92.070 100.800</span></span> +<span><span class="co">## log_k_parent -5.030 0.07059 -5.211 -4.848</span></span> +<span><span class="co">## sigma 3.162 0.79050 1.130 5.194</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_k_parent sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 5.938e-01 3.387e-07</span></span> +<span><span class="co">## log_k_parent 5.938e-01 1.000e+00 5.830e-07</span></span> +<span><span class="co">## sigma 3.387e-07 5.830e-07 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 96.440000 56.77 1.604e-08 92.070000 1.008e+02</span></span> +<span><span class="co">## k_parent 0.006541 14.17 1.578e-05 0.005455 7.842e-03</span></span> +<span><span class="co">## sigma 3.162000 4.00 5.162e-03 1.130000 5.194e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 3.287 2 6</span></span> +<span><span class="co">## parent 3.287 2 6</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90</span></span> +<span><span class="co">## parent 106 352</span></span></code></pre> <div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"FOMC"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> -<pre><code>## mkin version used for fitting: 1.0.3.9000 -## R version used for fitting: 4.0.3 -## Date of fit: Mon Feb 15 17:13:42 2021 -## Date of summary: Mon Feb 15 17:13:42 2021 -## -## Equations: -## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -## -## Model predictions using solution type analytical -## -## Fitted using 224 model solutions performed in 0.046 s -## -## Error model: Constant variance -## -## Error model algorithm: OLS -## -## Starting values for parameters to be optimised: -## value type -## parent_0 96.6 state -## alpha 1.0 deparm -## beta 10.0 deparm -## -## Starting values for the transformed parameters actually optimised: -## value lower upper -## parent_0 96.600000 -Inf Inf -## log_alpha 0.000000 -Inf Inf -## log_beta 2.302585 -Inf Inf -## -## Fixed parameter values: -## None -## -## Results: -## -## AIC BIC logLik -## 40.37255 40.69032 -16.18628 -## -## Optimised, transformed parameters with symmetric confidence intervals: -## Estimate Std. Error Lower Upper -## parent_0 99.1400 1.2670 95.6300 102.7000 -## log_alpha -0.3506 0.2616 -1.0770 0.3756 -## log_beta 4.1740 0.3938 3.0810 5.2670 -## sigma 1.8300 0.4575 0.5598 3.1000 -## -## Parameter correlation: -## parent_0 log_alpha log_beta sigma -## parent_0 1.000e+00 -4.696e-01 -5.543e-01 -2.468e-07 -## log_alpha -4.696e-01 1.000e+00 9.889e-01 2.478e-08 -## log_beta -5.543e-01 9.889e-01 1.000e+00 5.211e-08 -## sigma -2.468e-07 2.478e-08 5.211e-08 1.000e+00 -## -## Backtransformed parameters: -## Confidence intervals for internally transformed parameters are asymmetric. -## t-test (unrealistically) based on the assumption of normal distribution -## for estimators of untransformed parameters. -## Estimate t value Pr(>t) Lower Upper -## parent_0 99.1400 78.250 7.993e-08 95.6300 102.700 -## alpha 0.7042 3.823 9.365e-03 0.3407 1.456 -## beta 64.9800 2.540 3.201e-02 21.7800 193.900 -## sigma 1.8300 4.000 8.065e-03 0.5598 3.100 -## -## FOCUS Chi2 error levels in percent: -## err.min n.optim df -## All data 2.029 3 5 -## parent 2.029 3 5 -## -## Estimated disappearance times: -## DT50 DT90 DT50back -## parent 108.9 1644 494.9</code></pre> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">mm.L4</span><span class="op">[[</span><span class="st">"FOMC"</span>, <span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## mkin version used for fitting: 1.1.2 </span></span> +<span><span class="co">## R version used for fitting: 4.2.1 </span></span> +<span><span class="co">## Date of fit: Fri Sep 16 10:31:38 2022 </span></span> +<span><span class="co">## Date of summary: Fri Sep 16 10:31:38 2022 </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Equations:</span></span> +<span><span class="co">## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Model predictions using solution type analytical </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fitted using 224 model solutions performed in 0.045 s</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model: Constant variance </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Error model algorithm: OLS </span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for parameters to be optimised:</span></span> +<span><span class="co">## value type</span></span> +<span><span class="co">## parent_0 96.6 state</span></span> +<span><span class="co">## alpha 1.0 deparm</span></span> +<span><span class="co">## beta 10.0 deparm</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Starting values for the transformed parameters actually optimised:</span></span> +<span><span class="co">## value lower upper</span></span> +<span><span class="co">## parent_0 96.600000 -Inf Inf</span></span> +<span><span class="co">## log_alpha 0.000000 -Inf Inf</span></span> +<span><span class="co">## log_beta 2.302585 -Inf Inf</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Fixed parameter values:</span></span> +<span><span class="co">## None</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Results:</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## AIC BIC logLik</span></span> +<span><span class="co">## 40.37255 40.69032 -16.18628</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Optimised, transformed parameters with symmetric confidence intervals:</span></span> +<span><span class="co">## Estimate Std. Error Lower Upper</span></span> +<span><span class="co">## parent_0 99.1400 1.2670 95.6300 102.7000</span></span> +<span><span class="co">## log_alpha -0.3506 0.2616 -1.0770 0.3756</span></span> +<span><span class="co">## log_beta 4.1740 0.3938 3.0810 5.2670</span></span> +<span><span class="co">## sigma 1.8300 0.4575 0.5598 3.1000</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Parameter correlation:</span></span> +<span><span class="co">## parent_0 log_alpha log_beta sigma</span></span> +<span><span class="co">## parent_0 1.000e+00 -4.696e-01 -5.543e-01 -2.468e-07</span></span> +<span><span class="co">## log_alpha -4.696e-01 1.000e+00 9.889e-01 2.478e-08</span></span> +<span><span class="co">## log_beta -5.543e-01 9.889e-01 1.000e+00 5.211e-08</span></span> +<span><span class="co">## sigma -2.468e-07 2.478e-08 5.211e-08 1.000e+00</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Backtransformed parameters:</span></span> +<span><span class="co">## Confidence intervals for internally transformed parameters are asymmetric.</span></span> +<span><span class="co">## t-test (unrealistically) based on the assumption of normal distribution</span></span> +<span><span class="co">## for estimators of untransformed parameters.</span></span> +<span><span class="co">## Estimate t value Pr(>t) Lower Upper</span></span> +<span><span class="co">## parent_0 99.1400 78.250 7.993e-08 95.6300 102.700</span></span> +<span><span class="co">## alpha 0.7042 3.823 9.365e-03 0.3407 1.456</span></span> +<span><span class="co">## beta 64.9800 2.540 3.201e-02 21.7800 193.900</span></span> +<span><span class="co">## sigma 1.8300 4.000 8.065e-03 0.5598 3.100</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## FOCUS Chi2 error levels in percent:</span></span> +<span><span class="co">## err.min n.optim df</span></span> +<span><span class="co">## All data 2.029 3 5</span></span> +<span><span class="co">## parent 2.029 3 5</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## Estimated disappearance times:</span></span> +<span><span class="co">## DT50 DT90 DT50back</span></span> +<span><span class="co">## parent 108.9 1644 494.9</span></span></code></pre> </div> -<div id="references" class="section level1 unnumbered"> -<h1 class="hasAnchor"> -<a href="#references" class="anchor"></a>References</h1> +<div class="section level2"> +<h2 class="unnumbered" id="references">References<a class="anchor" aria-label="anchor" href="#references"></a> +</h2> <div id="refs" class="references hanging-indent"> <div id="ref-ranke2014"> <p>Ranke, Johannes. 2014. “Prüfung und Validierung von Modellierungssoftware als Alternative zu ModelMaker 4.0.” Umweltbundesamt Projektnummer 27452.</p> @@ -801,11 +806,13 @@ <footer><div class="copyright"> - 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<span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,12 +41,18 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -99,6 +105,8 @@ <dd> </dd><dt><a href="web_only/dimethenamid_2018.html">Example evaluations of the dimethenamid data from 2018</a></dt> <dd> + </dd><dt><a href="web_only/multistart.html">Short demo of the multistart method</a></dt> + <dd> </dd></dl></div> </div> </div> @@ -109,7 +117,7 @@ </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/articles/web_only/benchmarks.html b/docs/dev/articles/web_only/benchmarks.html index a6d52649..e5bc5a21 100644 --- a/docs/dev/articles/web_only/benchmarks.html +++ b/docs/dev/articles/web_only/benchmarks.html @@ -20,6 +20,8 @@ <![endif]--> </head> <body data-spy="scroll" data-target="#toc"> + + <div class="container template-article"> <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> @@ -32,7 +34,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -42,7 +44,7 @@ <a href="../../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -58,6 +60,9 @@ <a href="../../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -80,7 +85,7 @@ </ul> <ul class="nav navbar-nav navbar-right"> <li> - <a href="https://github.com/jranke/mkin/"> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> @@ -95,243 +100,442 @@ - </header><script src="benchmarks_files/header-attrs-2.6/header-attrs.js"></script><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> + </header><script src="benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> <div class="col-md-9 contents"> <div class="page-header toc-ignore"> <h1 data-toc-skip>Benchmark timings for mkin</h1> - <h4 class="author">Johannes Ranke</h4> + <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 class="date">Last change 13 May 2020 (rebuilt 2021-02-15)</h4> + <h4 data-toc-skip class="date">Last change 14 July 2022 (rebuilt 2022-09-16)</h4> - <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/master/vignettes/web_only/benchmarks.rmd"><code>vignettes/web_only/benchmarks.rmd</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/benchmarks.rmd" class="external-link"><code>vignettes/web_only/benchmarks.rmd</code></a></small> <div class="hidden name"><code>benchmarks.rmd</code></div> </div> -<p>Each system is characterized by its CPU type, the operating system type and the mkin version. Currently only values for one system are available. A compiler was available, so if no analytical solution was available, compiled ODE models are used.</p> -<div id="test-cases" class="section level2"> -<h2 class="hasAnchor"> -<a href="#test-cases" class="anchor"></a>Test cases</h2> -<p>Parent only:</p> +<p>Each system is characterized by the operating system type, the CPU type, the mkin version, and, as in June 2022 the current R version lead to worse performance, the R version. A compiler was available, so if no analytical solution was available, compiled ODE models are used.</p> +<p>Every fit is only performed once, so the accuracy of the benchmarks is limited.</p> +<p>The following wrapper function for <code>mmkin</code> is used because the way the error model is specified was changed in mkin version 0.9.49.1.</p> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">FOCUS_C</span> <span class="op"><-</span> <span class="va">FOCUS_2006_C</span> -<span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/subset.html">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span> -<span class="va">parent_datasets</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">FOCUS_C</span>, <span class="va">FOCUS_D</span><span class="op">)</span> - -<span class="va">t1</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span>, - error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></code></pre></div> -<p>One metabolite:</p> +<code class="sourceCode R"><span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/utils/packageDescription.html" class="external-link">packageVersion</a></span><span class="op">(</span><span class="st">"mkin"</span><span class="op">)</span> <span class="op">></span> <span class="st">"0.9.48.1"</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="va">mmkin_bench</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, <span class="va">error_model</span> <span class="op">=</span> <span class="st">"const"</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, error_model <span class="op">=</span> <span class="va">error_model</span>, cores <span class="op">=</span> <span class="fl">1</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span> <span class="op">}</span></span> +<span><span class="op">}</span> <span class="kw">else</span> <span class="op">{</span></span> +<span> <span class="va">mmkin_bench</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, <span class="va">error_model</span> <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="va">models</span>, <span class="va">datasets</span>, reweight.method <span class="op">=</span> <span class="va">error_model</span>, cores <span class="op">=</span> <span class="fl">1</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span> <span class="op">}</span></span> +<span><span class="op">}</span></span></code></pre></div> +<div class="section level2"> +<h2 id="test-cases">Test cases<a class="anchor" aria-label="anchor" href="#test-cases"></a> +</h2> +<p>Parent only:</p> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span> - parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>, - m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span> -<span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span> - parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>, - m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span> -<span class="va">DFOP_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span> - parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>, - m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span> -<span class="va">t3</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t4</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t5</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></code></pre></div> -<p>Two metabolites, synthetic data:</p> +<code class="sourceCode R"><span><span class="va">FOCUS_C</span> <span class="op"><-</span> <span class="va">FOCUS_2006_C</span></span> +<span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span> +<span><span class="va">parent_datasets</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_C</span>, <span class="va">FOCUS_D</span><span class="op">)</span></span> +<span></span> +<span></span> +<span><span class="va">t1</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span>, <span class="st">"HS"</span><span class="op">)</span>, <span class="va">parent_datasets</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> +<p>One metabolite:</p> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">m_synth_SFO_lin</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M1"</span><span class="op">)</span>, - M1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M2"</span><span class="op">)</span>, - M2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, - use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> - -<span class="va">m_synth_DFOP_par</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"M1"</span>, <span class="st">"M2"</span><span class="op">)</span><span class="op">)</span>, - M1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, - M2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, - use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> - -<span class="va">SFO_lin_a</span> <span class="op"><-</span> <span class="va">synthetic_data_for_UBA_2014</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span> - -<span class="va">DFOP_par_c</span> <span class="op"><-</span> <span class="va">synthetic_data_for_UBA_2014</span><span class="op">[[</span><span class="fl">12</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span> - -<span class="va">t6</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t7</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> - -<span class="va">t8</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t9</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> - -<span class="va">t10</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span> -<span class="va">t11</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span>, - error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span></span> +<span> parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> +<span> m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span></span> +<span> parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> +<span> m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">DFOP_SFO</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span></span> +<span> parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> +<span> m1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="va">t3</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t4</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t5</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOMC_SFO</span>, <span class="va">DFOP_SFO</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">FOCUS_D</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> +<p>Two metabolites, synthetic data:</p> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">mkin_benchmarks</span><span class="op">[</span><span class="va">system_string</span>, <span class="fu"><a href="https://rdrr.io/r/base/paste.html">paste0</a></span><span class="op">(</span><span class="st">"t"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">11</span><span class="op">)</span><span class="op">]</span> <span class="op"><-</span> - <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="va">t1</span>, <span class="va">t2</span>, <span class="va">t3</span>, <span class="va">t4</span>, <span class="va">t5</span>, <span class="va">t6</span>, <span class="va">t7</span>, <span class="va">t8</span>, <span class="va">t9</span>, <span class="va">t10</span>, <span class="va">t11</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/save.html">save</a></span><span class="op">(</span><span class="va">mkin_benchmarks</span>, file <span class="op">=</span> <span class="st">"~/git/mkin/vignettes/web_only/mkin_benchmarks.rda"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">m_synth_SFO_lin</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M1"</span><span class="op">)</span>,</span> +<span> M1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M2"</span><span class="op">)</span>,</span> +<span> M2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> +<span> use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span></span> +<span><span class="va">m_synth_DFOP_par</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"M1"</span>, <span class="st">"M2"</span><span class="op">)</span><span class="op">)</span>,</span> +<span> M1 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> +<span> M2 <span class="op">=</span> <span class="fu"><a href="../../reference/mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> +<span> use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span></span> +<span><span class="va">SFO_lin_a</span> <span class="op"><-</span> <span class="va">synthetic_data_for_UBA_2014</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span> +<span></span> +<span><span class="va">DFOP_par_c</span> <span class="op"><-</span> <span class="va">synthetic_data_for_UBA_2014</span><span class="op">[[</span><span class="fl">12</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span> +<span></span> +<span><span class="va">t6</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t7</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span></span> +<span><span class="va">t8</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t9</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span></span> +<span><span class="va">t10</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">SFO_lin_a</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span> +<span><span class="va">t11</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span><span class="fu">mmkin_bench</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DFOP_par_c</span><span class="op">)</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span><span class="op">)</span><span class="op">[[</span><span class="st">"elapsed"</span><span class="op">]</span><span class="op">]</span></span></code></pre></div> </div> -<div id="results" class="section level2"> -<h2 class="hasAnchor"> -<a href="#results" class="anchor"></a>Results</h2> -<p>Currently, we only have benchmark information on one system, therefore only the mkin version is shown with the results below. Timings are in seconds, shorter is better. All results were obtained by serial, i.e. not using multiple computing cores.</p> -<p>Benchmarks for all available error models are shown.</p> -<div id="parent-only" class="section level3"> -<h3 class="hasAnchor"> -<a href="#parent-only" class="anchor"></a>Parent only</h3> +<div class="section level2"> +<h2 id="results">Results<a class="anchor" aria-label="anchor" href="#results"></a> +</h2> +<p>Benchmarks for all available error models are shown. They are intended for improving mkin, not for comparing CPUs or operating systems. All trademarks belong to their respective owners.</p> +<div class="section level3"> +<h3 id="parent-only">Parent only<a class="anchor" aria-label="anchor" href="#parent-only"></a> +</h3> <p>Constant variance (t1) and two-component error model (t2) for four models fitted to two datasets, i.e. eight fits for each test.</p> <table class="table"> <thead><tr class="header"> -<th align="left">mkin version</th> -<th align="right">t1 [s]</th> -<th align="right">t2 [s]</th> +<th align="left">OS</th> +<th align="left">CPU</th> +<th align="left">R</th> +<th align="left">mkin</th> +<th align="right">t1</th> +<th align="right">t2</th> </tr></thead> <tbody> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.48.1</td> <td align="right">3.610</td> <td align="right">11.019</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.1</td> <td align="right">8.184</td> <td align="right">22.889</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.2</td> <td align="right">7.064</td> <td align="right">12.558</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.3</td> <td align="right">7.296</td> <td align="right">21.239</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.4</td> <td align="right">5.936</td> <td align="right">20.545</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.2</td> <td align="right">1.714</td> <td align="right">3.971</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.3</td> <td align="right">1.752</td> <td align="right">4.156</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.4</td> <td align="right">1.786</td> <td align="right">3.729</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">1.0.3</td> -<td align="right">1.722</td> -<td align="right">3.419</td> +<td align="right">1.881</td> +<td align="right">3.504</td> </tr> <tr class="even"> -<td align="left">1.0.3.9000</td> -<td align="right">2.770</td> -<td align="right">3.458</td> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> +<td align="left">1.0.4</td> +<td align="right">1.867</td> +<td align="right">3.450</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">1.791</td> +<td align="right">3.289</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">1.842</td> +<td align="right">3.453</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">1.959</td> +<td align="right">4.116</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">1.877</td> +<td align="right">3.906</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">1.644</td> +<td align="right">3.172</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">1.770</td> +<td align="right">3.377</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">1.957</td> +<td align="right">3.633</td> </tr> </tbody> </table> </div> -<div id="one-metabolite" class="section level3"> -<h3 class="hasAnchor"> -<a href="#one-metabolite" class="anchor"></a>One metabolite</h3> +<div class="section level3"> +<h3 id="one-metabolite">One metabolite<a class="anchor" aria-label="anchor" href="#one-metabolite"></a> +</h3> <p>Constant variance (t3), two-component error model (t4), and variance by variable (t5) for three models fitted to one dataset, i.e. three fits for each test.</p> <table class="table"> <thead><tr class="header"> -<th align="left">mkin version</th> -<th align="right">t3 [s]</th> -<th align="right">t4 [s]</th> -<th align="right">t5 [s]</th> +<th align="left">OS</th> +<th align="left">CPU</th> +<th align="left">R</th> +<th align="left">mkin</th> +<th align="right">t3</th> +<th align="right">t4</th> +<th align="right">t5</th> </tr></thead> <tbody> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.48.1</td> <td align="right">3.764</td> <td align="right">14.347</td> <td align="right">9.495</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.1</td> <td align="right">4.649</td> <td align="right">13.789</td> <td align="right">6.395</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.2</td> <td align="right">4.786</td> <td align="right">8.461</td> <td align="right">5.675</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.3</td> <td align="right">4.510</td> <td align="right">13.805</td> <td align="right">7.386</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.4</td> <td align="right">4.446</td> <td align="right">15.335</td> <td align="right">6.002</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.2</td> <td align="right">1.402</td> <td align="right">6.174</td> <td align="right">2.764</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.3</td> <td align="right">1.430</td> <td align="right">6.615</td> <td align="right">2.878</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.4</td> <td align="right">1.397</td> <td align="right">7.251</td> <td align="right">2.810</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">1.0.3</td> -<td align="right">1.402</td> -<td align="right">6.343</td> -<td align="right">2.802</td> +<td align="right">1.430</td> +<td align="right">6.344</td> +<td align="right">2.798</td> </tr> <tr class="even"> -<td align="left">1.0.3.9000</td> -<td align="right">1.405</td> -<td align="right">6.417</td> -<td align="right">2.824</td> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> +<td align="left">1.0.4</td> +<td align="right">1.415</td> +<td align="right">6.364</td> +<td align="right">2.820</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">1.310</td> +<td align="right">6.279</td> +<td align="right">2.681</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">3.802</td> +<td align="right">21.247</td> +<td align="right">8.461</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">3.334</td> +<td align="right">19.521</td> +<td align="right">7.565</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">1.578</td> +<td align="right">8.058</td> +<td align="right">3.339</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">1.230</td> +<td align="right">5.839</td> +<td align="right">2.444</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">1.308</td> +<td align="right">5.758</td> +<td align="right">2.558</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">1.503</td> +<td align="right">6.147</td> +<td align="right">2.803</td> </tr> </tbody> </table> </div> -<div id="two-metabolites" class="section level3"> -<h3 class="hasAnchor"> -<a href="#two-metabolites" class="anchor"></a>Two metabolites</h3> +<div class="section level3"> +<h3 id="two-metabolites">Two metabolites<a class="anchor" aria-label="anchor" href="#two-metabolites"></a> +</h3> <p>Constant variance (t6 and t7), two-component error model (t8 and t9), and variance by variable (t10 and t11) for one model fitted to one dataset, i.e. one fit for each test.</p> <table class="table"> <thead><tr class="header"> -<th align="left">mkin version</th> -<th align="right">t6 [s]</th> -<th align="right">t7 [s]</th> -<th align="right">t8 [s]</th> -<th align="right">t9 [s]</th> -<th align="right">t10 [s]</th> -<th align="right">t11 [s]</th> +<th align="left">OS</th> +<th align="left">CPU</th> +<th align="left">R</th> +<th align="left">mkin</th> +<th align="right">t6</th> +<th align="right">t7</th> +<th align="right">t8</th> +<th align="right">t9</th> +<th align="right">t10</th> +<th align="right">t11</th> </tr></thead> <tbody> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.48.1</td> <td align="right">2.623</td> <td align="right">4.587</td> @@ -341,6 +545,9 @@ <td align="right">31.267</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.1</td> <td align="right">2.542</td> <td align="right">4.128</td> @@ -350,6 +557,9 @@ <td align="right">5.636</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.2</td> <td align="right">2.723</td> <td align="right">4.478</td> @@ -359,6 +569,9 @@ <td align="right">5.574</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.3</td> <td align="right">2.643</td> <td align="right">4.374</td> @@ -368,6 +581,9 @@ <td align="right">7.365</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.49.4</td> <td align="right">2.635</td> <td align="right">4.259</td> @@ -377,6 +593,9 @@ <td align="right">5.626</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.2</td> <td align="right">0.777</td> <td align="right">1.236</td> @@ -386,6 +605,9 @@ <td align="right">2.987</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.3</td> <td align="right">0.858</td> <td align="right">1.264</td> @@ -395,6 +617,9 @@ <td align="right">3.073</td> </tr> <tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">0.9.50.4</td> <td align="right">0.783</td> <td align="right">1.282</td> @@ -404,22 +629,112 @@ <td align="right">3.105</td> </tr> <tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> <td align="left">1.0.3</td> -<td align="right">0.771</td> -<td align="right">1.251</td> -<td align="right">1.464</td> -<td align="right">3.074</td> -<td align="right">1.940</td> -<td align="right">2.831</td> +<td align="right">0.763</td> +<td align="right">1.244</td> +<td align="right">1.457</td> +<td align="right">3.054</td> +<td align="right">1.923</td> +<td align="right">2.839</td> </tr> <tr class="even"> -<td align="left">1.0.3.9000</td> -<td align="right">0.772</td> -<td align="right">1.263</td> -<td align="right">1.483</td> -<td align="right">3.101</td> -<td align="right">1.958</td> -<td align="right">2.843</td> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">NA</td> +<td align="left">1.0.4</td> +<td align="right">0.785</td> +<td align="right">1.252</td> +<td align="right">1.466</td> +<td align="right">3.091</td> +<td align="right">1.936</td> +<td align="right">2.826</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">0.744</td> +<td align="right">1.227</td> +<td align="right">1.288</td> +<td align="right">3.553</td> +<td align="right">1.895</td> +<td align="right">2.738</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">3.018</td> +<td align="right">4.165</td> +<td align="right">5.036</td> +<td align="right">10.844</td> +<td align="right">6.623</td> +<td align="right">9.722</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.0</td> +<td align="right">2.522</td> +<td align="right">3.792</td> +<td align="right">4.143</td> +<td align="right">11.268</td> +<td align="right">5.935</td> +<td align="right">8.728</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.1.3</td> +<td align="left">1.1.0</td> +<td align="right">0.907</td> +<td align="right">1.535</td> +<td align="right">1.589</td> +<td align="right">4.544</td> +<td align="right">2.302</td> +<td align="right">3.463</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">i7-4710MQ</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">0.678</td> +<td align="right">1.095</td> +<td align="right">1.149</td> +<td align="right">3.247</td> +<td align="right">1.658</td> +<td align="right">2.472</td> +</tr> +<tr class="even"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.1</td> +<td align="right">0.696</td> +<td align="right">1.124</td> +<td align="right">1.321</td> +<td align="right">2.786</td> +<td align="right">1.744</td> +<td align="right">2.566</td> +</tr> +<tr class="odd"> +<td align="left">Linux</td> +<td align="left">Ryzen 7 1700</td> +<td align="left">4.2.1</td> +<td align="left">1.1.2</td> +<td align="right">0.861</td> +<td align="right">1.295</td> +<td align="right">1.507</td> +<td align="right">3.102</td> +<td align="right">1.961</td> +<td align="right">2.852</td> </tr> </tbody> </table> @@ -438,11 +753,13 @@ <footer><div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <p></p> +<p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer> @@ -451,5 +768,7 @@ + + </body> </html> diff --git a/docs/dev/articles/web_only/dimethenamid_2018.html b/docs/dev/articles/web_only/dimethenamid_2018.html index 6b5c8c4e..60f1ab5a 100644 --- a/docs/dev/articles/web_only/dimethenamid_2018.html +++ b/docs/dev/articles/web_only/dimethenamid_2018.html @@ -34,7 +34,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -44,7 +44,7 @@ <a href="../../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -60,6 +60,9 @@ <a href="../../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -103,7 +106,7 @@ <h1 data-toc-skip>Example evaluations of the dimethenamid data from 2018</h1> <h4 data-toc-skip class="author">Johannes Ranke</h4> - <h4 data-toc-skip class="date">Last change 10 February 2022, built on 28 Feb 2022</h4> + <h4 data-toc-skip class="date">Last change 1 July 2022, built on 16 Sep 2022</h4> <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/dimethenamid_2018.rmd" class="external-link"><code>vignettes/web_only/dimethenamid_2018.rmd</code></a></small> <div class="hidden name"><code>dimethenamid_2018.rmd</code></div> @@ -116,8 +119,8 @@ <div class="section level2"> <h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a> </h2> -<p>During the preparation of the journal article on nonlinear mixed-effects models in degradation kinetics <span class="citation">(Ranke et al. 2021)</span> and the analysis of the dimethenamid degradation data analysed therein, a need for a more detailed analysis using not only nlme and saemix, but also nlmixr for fitting the mixed-effects models was identified, as many model variants do not converge when fitted with nlme, and not all relevant error models can be fitted with saemix.</p> -<p>This vignette is an attempt to satisfy this need.</p> +<p>A first analysis of the data analysed here was presented in a recent journal article on nonlinear mixed-effects models in degradation kinetics <span class="citation">(Ranke et al. 2021)</span>. That analysis was based on the <code>nlme</code> package and a development version of the <code>saemix</code> package that was unpublished at the time. Meanwhile, version 3.0 of the <code>saemix</code> package is available from the CRAN repository. Also, it turned out that there was an error in the handling of the Borstel data in the mkin package at the time, leading to the duplication of a few data points from that soil. The dataset in the mkin package has been corrected, and the interface to <code>saemix</code> in the mkin package has been updated to use the released version.</p> +<p>This vignette is intended to present an up to date analysis of the data, using the corrected dataset and released versions of <code>mkin</code> and <code>saemix</code>.</p> </div> <div class="section level2"> <h2 id="data">Data<a class="anchor" aria-label="anchor" href="#data"></a> @@ -126,17 +129,17 @@ <p>The data are <a href="https://pkgdown.jrwb.de/mkin/reference/dimethenamid_2018.html">available in the mkin package</a>. The following code (hidden by default, please use the button to the right to show it) treats the data available for the racemic mixture dimethenamid (DMTA) and its enantiomer dimethenamid-P (DMTAP) in the same way, as no difference between their degradation behaviour was identified in the EU risk assessment. The observation times of each dataset are multiplied with the corresponding normalisation factor also available in the dataset, in order to make it possible to describe all datasets with a single set of parameters.</p> <p>Also, datasets observed in the same soil are merged, resulting in dimethenamid (DMTA) data from six soils.</p> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/mkin/">mkin</a></span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span> - <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span> - <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span> - <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span> - <span class="va">ds_i</span> -<span class="op">}</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span> -<span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span> -<span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span> -<span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></code></pre></div> +<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/mkin/">mkin</a></span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span> +<span> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span> +<span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span> +<span> <span class="va">ds_i</span></span> +<span><span class="op">}</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span> +<span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></code></pre></div> </div> <div class="section level2"> <h2 id="parent-degradation">Parent degradation<a class="anchor" aria-label="anchor" href="#parent-degradation"></a> @@ -147,30 +150,30 @@ </h3> <p>As a first step, to get a visual impression of the fit of the different models, we do separate evaluations for each soil using the mmkin function from the mkin package:</p> <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_mkin_const</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">dmta_ds</span>, - error_model <span class="op">=</span> <span class="st">"const"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> -<span class="va">f_parent_mkin_tc</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">dmta_ds</span>, - error_model <span class="op">=</span> <span class="st">"tc"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_parent_mkin_const</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">dmta_ds</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"const"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="va">f_parent_mkin_tc</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">dmta_ds</span>,</span> +<span> error_model <span class="op">=</span> <span class="st">"tc"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <p>The plot of the individual SFO fits shown below suggests that at least in some datasets the degradation slows down towards later time points, and that the scatter of the residuals error is smaller for smaller values (panel to the right):</p> <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_sfo_const-1.png" width="700"></p> <p>Using biexponential decline (DFOP) results in a slightly more random scatter of the residuals:</p> <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const-1.png" width="700"></p> <p>The population curve (bold line) in the above plot results from taking the mean of the individual transformed parameters, i.e. of log k1 and log k2, as well as of the logit of the g parameter of the DFOP model). Here, this procedure does not result in parameters that represent the degradation well, because in some datasets the fitted value for k2 is extremely close to zero, leading to a log k2 value that dominates the average. This is alleviated if only rate constants that pass the t-test for significant difference from zero (on the untransformed scale) are considered in the averaging:</p> <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const_test-1.png" width="700"></p> <p>While this is visually much more satisfactory, such an average procedure could introduce a bias, as not all results from the individual fits enter the population curve with the same weight. This is where nonlinear mixed-effects models can help out by treating all datasets with equally by fitting a parameter distribution model together with the degradation model and the error model (see below).</p> <p>The remaining trend of the residuals to be higher for higher predicted residues is reduced by using the two-component error model:</p> <div class="sourceCode" id="cb6"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="../../reference/mixed.html">mixed</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_tc_test-1.png" width="700"></p> <p>However, note that in the case of using this error model, the fits to the Flaach and BBA 2.3 datasets appear to be ill-defined, indicated by the fact that they did not converge:</p> <div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></code></pre></div> <pre><code><mmkin> object Status of individual fits: @@ -178,9 +181,9 @@ Status of individual fits: model Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot DFOP OK OK C OK C OK -OK: No warnings C: Optimisation did not converge: -iteration limit reached without convergence (10)</code></pre> +iteration limit reached without convergence (10) +OK: No warnings</code></pre> </div> <div class="section level3"> <h3 id="nonlinear-mixed-effects-models">Nonlinear mixed-effects models<a class="anchor" aria-label="anchor" href="#nonlinear-mixed-effects-models"></a> @@ -191,92 +194,146 @@ iteration limit reached without convergence (10)</code></pre> </h4> <p>The nlme package was the first R extension providing facilities to fit nonlinear mixed-effects models. We would like to do model selection from all four combinations of degradation models and error models based on the AIC. However, fitting the DFOP model with constant variance and using default control parameters results in an error, signalling that the maximum number of 50 iterations was reached, potentially indicating overparameterisation. Nevertheless, the algorithm converges when the two-component error model is used in combination with the DFOP model. This can be explained by the fact that the smaller residues observed at later sampling times get more weight when using the two-component error model which will counteract the tendency of the algorithm to try parameter combinations unsuitable for fitting these data.</p> <div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://svn.r-project.org/R-packages/trunk/nlme/" class="external-link">nlme</a></span><span class="op">)</span> -<span class="va">f_parent_nlme_sfo_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span> -<span class="co"># f_parent_nlme_dfop_const <- nlme(f_parent_mkin_const["DFOP", ])</span> -<span class="va">f_parent_nlme_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span> -<span class="va">f_parent_nlme_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://svn.r-project.org/R-packages/trunk/nlme/" class="external-link">nlme</a></span><span class="op">)</span></span> +<span><span class="va">f_parent_nlme_sfo_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> +<span><span class="co"># f_parent_nlme_dfop_const <- nlme(f_parent_mkin_const["DFOP", ])</span></span> +<span><span class="va">f_parent_nlme_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> +<span><span class="va">f_parent_nlme_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></code></pre></div> <p>Note that a certain degree of overparameterisation is also indicated by a warning obtained when fitting DFOP with the two-component error model (‘false convergence’ in the ‘LME step’ in iteration 3). However, as this warning does not occur in later iterations, and specifically not in the last of the 6 iterations, we can ignore this warning.</p> <p>The model comparison function of the nlme package can directly be applied to these fits showing a much lower AIC for the DFOP model fitted with the two-component error model. Also, the likelihood ratio test indicates that this difference is significant as the p-value is below 0.0001.</p> <div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span> - <span class="va">f_parent_nlme_sfo_const</span>, <span class="va">f_parent_nlme_sfo_tc</span>, <span class="va">f_parent_nlme_dfop_tc</span> -<span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span></span> +<span> <span class="va">f_parent_nlme_sfo_const</span>, <span class="va">f_parent_nlme_sfo_tc</span>, <span class="va">f_parent_nlme_dfop_tc</span></span> +<span><span class="op">)</span></span></code></pre></div> <pre><code> Model df AIC BIC logLik Test L.Ratio p-value f_parent_nlme_sfo_const 1 5 796.60 811.82 -393.30 f_parent_nlme_sfo_tc 2 6 798.60 816.86 -393.30 1 vs 2 0.00 0.998 f_parent_nlme_dfop_tc 3 10 671.91 702.34 -325.96 2 vs 3 134.69 <.0001</code></pre> <p>In addition to these fits, attempts were also made to include correlations between random effects by using the log Cholesky parameterisation of the matrix specifying them. The code used for these attempts can be made visible below.</p> <div class="sourceCode" id="cb12"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlme_sfo_const_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, - random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k_DMTA</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_const</span>, <span class="va">f_parent_nlme_sfo_const_logchol</span><span class="op">)</span> -<span class="va">f_parent_nlme_sfo_tc_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, - random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k_DMTA</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_tc</span>, <span class="va">f_parent_nlme_sfo_tc_logchol</span><span class="op">)</span> -<span class="va">f_parent_nlme_dfop_tc_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, - random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k1</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">g_qlogis</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span>, <span class="va">f_parent_nlme_dfop_tc_logchol</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_parent_nlme_sfo_const_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>,</span> +<span> random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k_DMTA</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_const</span>, <span class="va">f_parent_nlme_sfo_const_logchol</span><span class="op">)</span></span> +<span><span class="va">f_parent_nlme_sfo_tc_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>,</span> +<span> random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k_DMTA</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_tc</span>, <span class="va">f_parent_nlme_sfo_tc_logchol</span><span class="op">)</span></span> +<span><span class="va">f_parent_nlme_dfop_tc_logchol</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>,</span> +<span> random <span class="op">=</span> <span class="fu">nlme</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdLogChol.html" class="external-link">pdLogChol</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">DMTA_0</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k1</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">log_k2</span> <span class="op">~</span> <span class="fl">1</span>, <span class="va">g_qlogis</span> <span class="op">~</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span>, <span class="va">f_parent_nlme_dfop_tc_logchol</span><span class="op">)</span></span></code></pre></div> <p>While the SFO variants converge fast, the additional parameters introduced by this lead to convergence warnings for the DFOP model. The model comparison clearly show that adding correlations between random effects does not improve the fits.</p> <p>The selected model (DFOP with two-component error) fitted to the data assuming no correlations between random effects is shown below.</p> <div class="sourceCode" id="cb13"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/plot_parent_nlme-1.png" width="700"></p> </div> <div class="section level4"> <h4 id="saemix">saemix<a class="anchor" aria-label="anchor" href="#saemix"></a> </h4> <p>The saemix package provided the first Open Source implementation of the Stochastic Approximation to the Expectation Maximisation (SAEM) algorithm. SAEM fits of degradation models can be conveniently performed using an interface to the saemix package available in current development versions of the mkin package.</p> -<p>The corresponding SAEM fits of the four combinations of degradation and error models are fitted below. As there is no convergence criterion implemented in the saemix package, the convergence plots need to be manually checked for every fit. As we will compare the SAEM implementation of saemix to the results obtained using the nlmixr package later, we define control settings that work well for all the parent data fits shown in this vignette.</p> +<p>The corresponding SAEM fits of the four combinations of degradation and error models are fitted below. As there is no convergence criterion implemented in the saemix package, the convergence plots need to be manually checked for every fit. We define control settings that work well for all the parent data fits shown in this vignette.</p> <div class="sourceCode" id="cb14"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span> -<span class="va">saemix_control</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">800</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, - print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> -<span class="va">saemix_control_moreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1600</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, - print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span> -<span class="va">saemix_control_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10000</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>, - print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span></span> +<span><span class="va">saemix_control</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">800</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>,</span> +<span> print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span> +<span><span class="va">saemix_control_moreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1600</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>,</span> +<span> print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span> +<span><span class="va">saemix_control_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/saemixControl.html" class="external-link">saemixControl</a></span><span class="op">(</span>nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10000</span>, <span class="fl">300</span><span class="op">)</span>, nb.chains <span class="op">=</span> <span class="fl">15</span>,</span> +<span> print <span class="op">=</span> <span class="cn">FALSE</span>, save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span>, displayProgress <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div> <p>The convergence plot for the SFO model using constant variance is shown below.</p> <div class="sourceCode" id="cb15"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_sfo_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_sfo_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_sfo_const-1.png" width="700"></p> -<p>Obviously the default number of iterations is sufficient to reach convergence. This can also be said for the SFO fit using the two-component error model.</p> +<p>Obviously the selected number of iterations is sufficient to reach convergence. This can also be said for the SFO fit using the two-component error model.</p> <div class="sourceCode" id="cb16"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_sfo_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_sfo_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_sfo_tc-1.png" width="700"></p> <p>When fitting the DFOP model with constant variance (see below), parameter convergence is not as unambiguous.</p> <div class="sourceCode" id="cb17"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_dfop_const</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_const-1.png" width="700"></p> -<p>This is improved when the DFOP model is fitted with the two-component error model. Convergence of the variance of k2 is enhanced, it remains more or less stable already after 200 iterations of the first phase.</p> <div class="sourceCode" id="cb18"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="va">f_parent_saemix_dfop_tc_moreiter</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, - control <span class="op">=</span> <span class="va">saemix_control_moreiter</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_const</span><span class="op">)</span></span></code></pre></div> +<pre><code>Kinetic nonlinear mixed-effects model fit by SAEM +Structural model: +d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Likelihood computed by importance sampling + AIC BIC logLik + 706 704 -344 + +Fitted parameters: + estimate lower upper +DMTA_0 97.99583 96.50079 99.4909 +k1 0.06377 0.03432 0.0932 +k2 0.00848 0.00444 0.0125 +g 0.95701 0.91313 1.0009 +a.1 1.82141 1.65974 1.9831 +SD.DMTA_0 1.64787 0.45779 2.8379 +SD.k1 0.57439 0.24731 0.9015 +SD.k2 0.03296 -2.50143 2.5673 +SD.g 1.10266 0.32371 1.8816</code></pre> +<p>While the other parameters converge to credible values, the variance of k2 (<code>omega2.k2</code>) converges to a very small value. The printout of the <code>saem.mmkin</code> model shows that the estimated standard deviation of k2 across the population of soils (<code>SD.k2</code>) is ill-defined, indicating overparameterisation of this model.</p> +<p>When the DFOP model is fitted with the two-component error model, we also observe that the estimated variance of k2 becomes very small, while being ill-defined, as illustrated by the excessive confidence interval of <code>SD.k2</code>.</p> +<div class="sourceCode" id="cb20"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_dfop_tc</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> control <span class="op">=</span> <span class="va">saemix_control</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> +<span><span class="va">f_parent_saemix_dfop_tc_moreiter</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> control <span class="op">=</span> <span class="va">saemix_control_moreiter</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></code></pre></div> <p><img src="dimethenamid_2018_files/figure-html/f_parent_saemix_dfop_tc-1.png" width="700"></p> -<p>Doubling the number of iterations in the first phase of the algorithm leads to a slightly lower likelihood, and therefore to slightly higher AIC and BIC values. With even more iterations, the algorithm stops with an error message. This is related to the variance of k2 approximating zero. This has been submitted as a <a href="https://github.com/saemixdevelopment/saemixextension/issues/29" class="external-link">bug to the saemix package</a>, as the algorithm does not converge in this case.</p> +<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">)</span></span></code></pre></div> +<pre><code>Kinetic nonlinear mixed-effects model fit by SAEM +Structural model: +d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Likelihood computed by importance sampling + AIC BIC logLik + 666 664 -323 + +Fitted parameters: + estimate lower upper +DMTA_0 98.27617 96.3088 100.2436 +k1 0.06437 0.0337 0.0950 +k2 0.00880 0.0063 0.0113 +g 0.95249 0.9100 0.9949 +a.1 1.06161 0.8625 1.2607 +b.1 0.02967 0.0226 0.0367 +SD.DMTA_0 2.06075 0.4187 3.7028 +SD.k1 0.59357 0.2561 0.9310 +SD.k2 0.00292 -10.2960 10.3019 +SD.g 1.05725 0.3808 1.7337</code></pre> +<p>Doubling the number of iterations in the first phase of the algorithm leads to a slightly lower likelihood, and therefore to slightly higher AIC and BIC values. With even more iterations, the algorithm stops with an error message. This is related to the variance of k2 approximating zero and has been submitted as a <a href="https://github.com/saemixdevelopment/saemixextension/issues/29" class="external-link">bug to the saemix package</a>, as the algorithm does not converge in this case.</p> <p>An alternative way to fit DFOP in combination with the two-component error model is to use the model formulation with transformed parameters as used per default in mkin. When using this option, convergence is slower, but eventually the algorithm stops as well with the same error message.</p> <p>The four combinations (SFO/const, SFO/tc, DFOP/const and DFOP/tc) and the version with increased iterations can be compared using the model comparison function of the saemix package:</p> -<div class="sourceCode" id="cb19"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">AIC_parent_saemix</span> <span class="op"><-</span> <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span> - <span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_tc_moreiter</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></code></pre></div> +<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">AIC_parent_saemix</span> <span class="op"><-</span> <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span></span> +<span> <span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_dfop_tc_moreiter</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span></code></pre></div> <pre><code>Likelihoods calculated by importance sampling</code></pre> -<div class="sourceCode" id="cb21"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">rownames</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> - <span class="st">"SFO const"</span>, <span class="st">"SFO tc"</span>, <span class="st">"DFOP const"</span>, <span class="st">"DFOP tc"</span>, <span class="st">"DFOP tc more iterations"</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span></code></pre></div> +<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">rownames</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span> +<span> <span class="st">"SFO const"</span>, <span class="st">"SFO tc"</span>, <span class="st">"DFOP const"</span>, <span class="st">"DFOP tc"</span>, <span class="st">"DFOP tc more iterations"</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix</span><span class="op">)</span></span></code></pre></div> <pre><code> AIC BIC SFO const 796.38 795.34 SFO tc 798.38 797.13 @@ -284,149 +341,57 @@ DFOP const 705.75 703.88 DFOP tc 665.65 663.57 DFOP tc more iterations 665.88 663.80</code></pre> <p>In order to check the influence of the likelihood calculation algorithms implemented in saemix, the likelihood from Gaussian quadrature is added to the best fit, and the AIC values obtained from the three methods are compared.</p> -<div class="sourceCode" id="cb23"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span> <span class="op"><-</span> - <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/llgq.saemix.html" class="external-link">llgq.saemix</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span> -<span class="va">AIC_parent_saemix_methods</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> - is <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"is"</span><span class="op">)</span>, - gq <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"gq"</span><span class="op">)</span>, - lin <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"lin"</span><span class="op">)</span> -<span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix_methods</span><span class="op">)</span></code></pre></div> +<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span> <span class="op"><-</span></span> +<span> <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/llgq.saemix.html" class="external-link">llgq.saemix</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> +<span><span class="va">AIC_parent_saemix_methods</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span> +<span> is <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"is"</span><span class="op">)</span>,</span> +<span> gq <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"gq"</span><span class="op">)</span>,</span> +<span> lin <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"lin"</span><span class="op">)</span></span> +<span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix_methods</span><span class="op">)</span></span></code></pre></div> <pre><code> is gq lin 665.65 665.68 665.11 </code></pre> -<p>The AIC values based on importance sampling and Gaussian quadrature are very similar. Using linearisation is known to be less accurate, but still gives a similar value. In order to illustrate that the comparison of the three method depends on the degree of convergence obtained in the fit, the same comparison is shown below for the fit using the defaults for the number of iterations and the number of MCMC chains.</p> -<div class="sourceCode" id="cb25"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_saemix_dfop_tc_defaults</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span> -<span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span> <span class="op"><-</span> - <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/llgq.saemix.html" class="external-link">llgq.saemix</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span><span class="op">)</span> -<span class="va">AIC_parent_saemix_methods_defaults</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span> - is <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"is"</span><span class="op">)</span>, - gq <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"gq"</span><span class="op">)</span>, - lin <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"lin"</span><span class="op">)</span> -<span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix_methods_defaults</span><span class="op">)</span></code></pre></div> +<p>The AIC values based on importance sampling and Gaussian quadrature are very similar. Using linearisation is known to be less accurate, but still gives a similar value.</p> +<p>In order to illustrate that the comparison of the three method depends on the degree of convergence obtained in the fit, the same comparison is shown below for the fit using the defaults for the number of iterations and the number of MCMC chains.</p> +<p>When using OpenBlas for linear algebra, there is a large difference in the values obtained with Gaussian quadrature, so the larger number of iterations makes a lot of difference. When using the LAPACK version coming with Debian Bullseye, the AIC based on Gaussian quadrature is almost the same as the one obtained with the other methods, also when using defaults for the fit.</p> +<div class="sourceCode" id="cb29"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_parent_saemix_dfop_tc_defaults</span> <span class="op"><-</span> <span class="fu">mkin</span><span class="fu">::</span><span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span> +<span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span> <span class="op"><-</span></span> +<span> <span class="fu">saemix</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/llgq.saemix.html" class="external-link">llgq.saemix</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> +<span><span class="va">AIC_parent_saemix_methods_defaults</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span> +<span> is <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"is"</span><span class="op">)</span>,</span> +<span> gq <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"gq"</span><span class="op">)</span>,</span> +<span> lin <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_saemix_dfop_tc_defaults</span><span class="op">$</span><span class="va">so</span>, method <span class="op">=</span> <span class="st">"lin"</span><span class="op">)</span></span> +<span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">AIC_parent_saemix_methods_defaults</span><span class="op">)</span></span></code></pre></div> <pre><code> is gq lin 668.27 718.36 666.49 </code></pre> </div> -<div class="section level4"> -<h4 id="nlmixr">nlmixr<a class="anchor" aria-label="anchor" href="#nlmixr"></a> -</h4> -<p>In the last years, a lot of effort has been put into the nlmixr package which is designed for pharmacokinetics, where nonlinear mixed-effects models are routinely used, but which can also be used for related data like chemical degradation data. A current development branch of the mkin package provides an interface between mkin and nlmixr. Here, we check if we get equivalent results when using a refined version of the First Order Conditional Estimation (FOCE) algorithm used in nlme, namely the First Order Conditional Estimation with Interaction (FOCEI), and the SAEM algorithm as implemented in nlmixr.</p> -<p>First, the focei algorithm is used for the four model combinations.</p> -<div class="sourceCode" id="cb27"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/nlmixrdevelopment/nlmixr" class="external-link">nlmixr</a></span><span class="op">)</span> -<span class="va">f_parent_nlmixr_focei_sfo_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"focei"</span><span class="op">)</span> -<span class="va">f_parent_nlmixr_focei_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"focei"</span><span class="op">)</span> -<span class="va">f_parent_nlmixr_focei_dfop_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"focei"</span><span class="op">)</span> -<span class="va">f_parent_nlmixr_focei_dfop_tc</span><span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"focei"</span><span class="op">)</span></code></pre></div> -<p>For the SFO model with constant variance, the AIC values are the same, for the DFOP model, there are significant differences between the AIC values. These may be caused by different solutions that are found, but also by the fact that the AIC values for the nlmixr fits are calculated based on Gaussian quadrature, not on linearisation.</p> -<div class="sourceCode" id="cb28"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">aic_nlmixr_focei</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span> - <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_focei_sfo_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_focei_sfo_tc</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_focei_dfop_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_focei_dfop_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span>, - <span class="va">AIC</span><span class="op">)</span> -<span class="va">aic_nlme</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span> - <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_const</span>, <span class="cn">NA</span>, <span class="va">f_parent_nlme_sfo_tc</span>, <span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span>, - <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">x</span><span class="op">[</span><span class="fl">1</span><span class="op">]</span><span class="op">)</span><span class="op">)</span> <span class="cn">NA</span> <span class="kw">else</span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span><span class="op">)</span> -<span class="va">aic_nlme_nlmixr_focei</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span> - <span class="st">"Degradation model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"SFO"</span>, <span class="st">"DFOP"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, - <span class="st">"Error model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"constant variance"</span>, <span class="st">"two-component"</span><span class="op">)</span>, <span class="fl">2</span><span class="op">)</span>, - <span class="st">"AIC (nlme)"</span> <span class="op">=</span> <span class="va">aic_nlme</span>, - <span class="st">"AIC (nlmixr with FOCEI)"</span> <span class="op">=</span> <span class="va">aic_nlmixr_focei</span>, - check.names <span class="op">=</span> <span class="cn">FALSE</span> -<span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">aic_nlme_nlmixr_focei</span><span class="op">)</span></code></pre></div> -<pre><code> Degradation model Error model AIC (nlme) AIC (nlmixr with FOCEI) -1 SFO constant variance 796.60 796.60 -2 SFO two-component NA 798.64 -3 DFOP constant variance 798.60 745.87 -4 DFOP two-component 671.91 740.42</code></pre> -<p>Secondly, we use the SAEM estimation routine and check the convergence plots. The control parameters, which were also used for the saemix fits, are defined beforehand.</p> -<div class="sourceCode" id="cb30"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">nlmixr_saem_control_800</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html" class="external-link">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, - nBurn <span class="op">=</span> <span class="fl">800</span>, nEm <span class="op">=</span> <span class="fl">300</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span> -<span class="va">nlmixr_saem_control_moreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html" class="external-link">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, - nBurn <span class="op">=</span> <span class="fl">1600</span>, nEm <span class="op">=</span> <span class="fl">300</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span> -<span class="va">nlmixr_saem_control_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html" class="external-link">saemControl</a></span><span class="op">(</span>logLik <span class="op">=</span> <span class="cn">TRUE</span>, - nBurn <span class="op">=</span> <span class="fl">10000</span>, nEm <span class="op">=</span> <span class="fl">1000</span>, nmc <span class="op">=</span> <span class="fl">15</span><span class="op">)</span></code></pre></div> -<p>Then we fit SFO with constant variance</p> -<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_sfo_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_const</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_sfo_const-1.png" width="700"></p> -<p>and SFO with two-component error.</p> -<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_sfo_tc-1.png" width="700"></p> -<p>For DFOP with constant variance, the convergence plots show considerable instability of the fit, which indicates overparameterisation which was already observed above for this model combination. Also note that the variance of k2 approximates zero, which was already observed in the saemix fits of the DFOP model.</p> -<div class="sourceCode" id="cb33"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_const</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_const</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_const</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_const-1.png" width="700"></p> -<p>For DFOP with two-component error, a less erratic convergence is seen, but the variance of k2 again approximates zero.</p> -<div class="sourceCode" id="cb34"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_800</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc-1.png" width="700"></p> -<p>To check if an increase in the number of iterations improves the fit, we repeat the fit with 1000 iterations for the burn in phase and 300 iterations for the second phase.</p> -<div class="sourceCode" id="cb35"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc_moreiter</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_moreiter</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc_moreiter</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc_1k-1.png" width="700"></p> -<p>Here the fit looks very similar, but we will see below that it shows a higher AIC than the fit with 800 iterations in the burn in phase. Next we choose 10 000 iterations for the burn in phase and 1000 iterations for the second phase for comparison with saemix.</p> -<div class="sourceCode" id="cb36"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_parent_mkin_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span>, est <span class="op">=</span> <span class="st">"saem"</span>, - control <span class="op">=</span> <span class="va">nlmixr_saem_control_10k</span><span class="op">)</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/traceplot.html" class="external-link">traceplot</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<p><img src="dimethenamid_2018_files/figure-html/f_parent_nlmixr_saem_dfop_tc_10k-1.png" width="700"></p> -<p>The AIC values are internally calculated using Gaussian quadrature.</p> -<div class="sourceCode" id="cb37"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_sfo_tc</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_saem_dfop_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_saem_dfop_tc_moreiter</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_saem_dfop_tc_10k</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></code></pre></div> -<pre><code> df AIC -f_parent_nlmixr_saem_sfo_const$nm 5 798.71 -f_parent_nlmixr_saem_sfo_tc$nm 6 808.64 -f_parent_nlmixr_saem_dfop_const$nm 9 1995.96 -f_parent_nlmixr_saem_dfop_tc$nm 10 664.96 -f_parent_nlmixr_saem_dfop_tc_moreiter$nm 10 4464.93 -f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> -<p>We can see that again, the DFOP/tc model shows the best goodness of fit. However, increasing the number of burn-in iterations from 800 to 1600 results in a higher AIC. If we further increase the number of iterations to 10 000 (burn-in) and 1000 (second phase), the AIC cannot be calculated for the nlmixr/saem fit, confirming that this fit does not converge properly with the SAEM algorithm.</p> </div> -<div class="section level4"> -<h4 id="comparison">Comparison<a class="anchor" aria-label="anchor" href="#comparison"></a> -</h4> -<p>The following table gives the AIC values obtained with the three packages using the same control parameters (800 iterations burn-in, 300 iterations second phase, 15 chains).</p> -<div class="sourceCode" id="cb39"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="va">AIC_all</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span> - check.names <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="st">"Degradation model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"SFO"</span>, <span class="st">"DFOP"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, - <span class="st">"Error model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"tc"</span>, <span class="st">"const"</span>, <span class="st">"tc"</span><span class="op">)</span>, - nlme <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_const</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_tc</span><span class="op">)</span>, <span class="cn">NA</span>, <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span><span class="op">)</span>, - nlmixr_focei <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_focei_sfo_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_focei_sfo_tc</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_focei_dfop_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_focei_dfop_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span>, <span class="va">AIC</span><span class="op">)</span>, - saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>, - <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span>, <span class="va">AIC</span><span class="op">)</span>, - nlmixr_saem <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_nlmixr_saem_sfo_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_sfo_tc</span><span class="op">$</span><span class="va">nm</span>, - <span class="va">f_parent_nlmixr_saem_dfop_const</span><span class="op">$</span><span class="va">nm</span>, <span class="va">f_parent_nlmixr_saem_dfop_tc</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span>, <span class="va">AIC</span><span class="op">)</span> -<span class="op">)</span> -<span class="fu">kable</span><span class="op">(</span><span class="va">AIC_all</span><span class="op">)</span></code></pre></div> +<div class="section level3"> +<h3 id="comparison">Comparison<a class="anchor" aria-label="anchor" href="#comparison"></a> +</h3> +<p>The following table gives the AIC values obtained with both backend packages using the same control parameters (800 iterations burn-in, 300 iterations second phase, 15 chains).</p> +<div class="sourceCode" id="cb31"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">AIC_all</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></span><span class="op">(</span></span> +<span> check.names <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="st">"Degradation model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"SFO"</span>, <span class="st">"DFOP"</span>, <span class="st">"DFOP"</span><span class="op">)</span>,</span> +<span> <span class="st">"Error model"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"tc"</span>, <span class="st">"const"</span>, <span class="st">"tc"</span><span class="op">)</span>,</span> +<span> nlme <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_const</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_sfo_tc</span><span class="op">)</span>, <span class="cn">NA</span>, <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_parent_nlme_dfop_tc</span><span class="op">)</span><span class="op">)</span>,</span> +<span> saemix_lin <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span>, <span class="va">AIC</span>, method <span class="op">=</span> <span class="st">"lin"</span><span class="op">)</span>,</span> +<span> saemix_is <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">f_parent_saemix_sfo_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_sfo_tc</span><span class="op">$</span><span class="va">so</span>,</span> +<span> <span class="va">f_parent_saemix_dfop_const</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_parent_saemix_dfop_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span>, <span class="va">AIC</span>, method <span class="op">=</span> <span class="st">"is"</span><span class="op">)</span></span> +<span><span class="op">)</span></span> +<span><span class="fu">kable</span><span class="op">(</span><span class="va">AIC_all</span><span class="op">)</span></span></code></pre></div> <table class="table"> <thead><tr class="header"> <th align="left">Degradation model</th> <th align="left">Error model</th> <th align="right">nlme</th> -<th align="right">nlmixr_focei</th> -<th align="right">saemix</th> -<th align="right">nlmixr_saem</th> +<th align="right">saemix_lin</th> +<th align="right">saemix_is</th> </tr></thead> <tbody> <tr class="odd"> @@ -435,36 +400,81 @@ f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> <td align="right">796.60</td> <td align="right">796.60</td> <td align="right">796.38</td> -<td align="right">798.71</td> </tr> <tr class="even"> <td align="left">SFO</td> <td align="left">tc</td> <td align="right">798.60</td> -<td align="right">798.64</td> +<td align="right">798.60</td> <td align="right">798.38</td> -<td align="right">808.64</td> </tr> <tr class="odd"> <td align="left">DFOP</td> <td align="left">const</td> <td align="right">NA</td> -<td align="right">745.87</td> +<td align="right">671.98</td> <td align="right">705.75</td> -<td align="right">1995.96</td> </tr> <tr class="even"> <td align="left">DFOP</td> <td align="left">tc</td> <td align="right">671.91</td> -<td align="right">740.42</td> +<td align="right">665.11</td> <td align="right">665.65</td> -<td align="right">664.96</td> </tr> </tbody> </table> </div> </div> +<div class="section level2"> +<h2 id="conclusion">Conclusion<a class="anchor" aria-label="anchor" href="#conclusion"></a> +</h2> +<p>A more detailed analysis of the dimethenamid dataset confirmed that the DFOP model provides the most appropriate description of the decline of the parent compound in these data. On the other hand, closer inspection of the results revealed that the variability of the k2 parameter across the population of soils is ill-defined. This coincides with the observation that this parameter cannot robustly be quantified for some of the soils.</p> +<p>Regarding the regulatory use of these data, it is claimed that an improved characterisation of the mean parameter values across the population is obtained using the nonlinear mixed-effects models presented here. However, attempts to quantify the variability of the slower rate constant of the biphasic decline of dimethenamid indicate that the data are not sufficient to characterise this variability to a satisfactory precision.</p> +</div> +<div class="section level2"> +<h2 id="session-info">Session Info<a class="anchor" aria-label="anchor" href="#session-info"></a> +</h2> +<div class="sourceCode" id="cb32"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/sessionInfo.html" class="external-link">sessionInfo</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div> +<pre><code>R version 4.2.1 (2022-06-23) +Platform: x86_64-pc-linux-gnu (64-bit) +Running under: Debian GNU/Linux 11 (bullseye) + +Matrix products: default +BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 +LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.13.so + +locale: + [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C + [3] LC_TIME=C LC_COLLATE=de_DE.UTF-8 + [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 + [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C + [9] LC_ADDRESS=C LC_TELEPHONE=C +[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C + +attached base packages: +[1] stats graphics grDevices utils datasets methods base + +other attached packages: +[1] nlme_3.1-158 mkin_1.1.2 knitr_1.39 + +loaded via a namespace (and not attached): + [1] deSolve_1.33 zoo_1.8-10 tidyselect_1.1.2 xfun_0.31 + [5] bslib_0.4.0 purrr_0.3.4 lattice_0.20-45 colorspace_2.0-3 + [9] vctrs_0.4.1 generics_0.1.3 htmltools_0.5.3 yaml_2.3.5 +[13] utf8_1.2.2 rlang_1.0.4 pkgdown_2.0.6 saemix_3.1 +[17] jquerylib_0.1.4 pillar_1.8.0 glue_1.6.2 DBI_1.1.3 +[21] lifecycle_1.0.1 stringr_1.4.0 munsell_0.5.0 gtable_0.3.0 +[25] ragg_1.2.2 memoise_2.0.1 evaluate_0.15 npde_3.2 +[29] fastmap_1.1.0 lmtest_0.9-40 parallel_4.2.1 fansi_1.0.3 +[33] highr_0.9 KernSmooth_2.23-20 scales_1.2.0 cachem_1.0.6 +[37] desc_1.4.1 jsonlite_1.8.0 systemfonts_1.0.4 fs_1.5.2 +[41] textshaping_0.3.6 gridExtra_2.3 ggplot2_3.3.6 digest_0.6.29 +[45] stringi_1.7.8 dplyr_1.0.9 grid_4.2.1 rprojroot_2.0.3 +[49] cli_3.3.0 tools_4.2.1 magrittr_2.0.3 sass_0.4.2 +[53] tibble_3.1.8 pkgconfig_2.0.3 assertthat_0.2.1 rmarkdown_2.14.3 +[57] mclust_5.4.10 R6_2.5.1 compiler_4.2.1 </code></pre> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a> @@ -501,7 +511,7 @@ f_parent_nlmixr_saem_dfop_tc_10k$nm 10 Inf</code></pre> <div class="pkgdown"> <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer> diff --git a/docs/dev/articles/web_only/dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const-1.png b/docs/dev/articles/web_only/dimethenamid_2018_files/figure-html/f_parent_mkin_dfop_const-1.png Binary 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</ul> +</div> +<!--/.nav-collapse --> + </div> +<!--/.container --> +</div> +<!--/.navbar --> + + + + </header><script src="multistart_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header toc-ignore"> + <h1 data-toc-skip>Short demo of the multistart method</h1> + <h4 data-toc-skip class="author">Johannes Ranke</h4> + + <h4 data-toc-skip class="date">Last change 26 September 2022 (rebuilt 2022-10-28)</h4> + + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/vignettes/web_only/multistart.rmd" class="external-link"><code>vignettes/web_only/multistart.rmd</code></a></small> + <div class="hidden name"><code>multistart.rmd</code></div> + + </div> + + + +<p>The dimethenamid data from 2018 from seven soils is used as example data in this vignette.</p> +<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/mkin/">mkin</a></span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> +<span> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span> +<span> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span> +<span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span> +<span> <span class="va">ds_i</span></span> +<span><span class="op">}</span><span class="op">)</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span> +<span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></code></pre></div> +<p>First, we check the DFOP model with the two-component error model and random effects for all degradation parameters.</p> +<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">dmta_ds</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">7</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> +<span><span class="va">f_saem_full</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_full</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## [1] "sd(log_k2)"</span></span></code></pre> +<p>We see that not all variability parameters are identifiable. The <code>illparms</code> function tells us that the confidence interval for the standard deviation of ‘log_k2’ includes zero. We check this assessment using multiple runs with different starting values.</p> +<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_full_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_full</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">16</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_full_multi</span><span class="op">)</span></span></code></pre></div> +<p><img src="multistart_files/figure-html/unnamed-chunk-3-1.png" width="700"></p> +<p>This confirms that the variance of k2 is the most problematic parameter, so we reduce the parameter distribution model by removing the intersoil variability for k2.</p> +<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_reduced</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_full</span>, no_random_effect <span class="op">=</span> <span class="st">"log_k2"</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_reduced</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## character(0)</span></span></code></pre> +<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="va">f_saem_reduced_multi</span> <span class="op"><-</span> <span class="fu"><a href="../../reference/multistart.html">multistart</a></span><span class="op">(</span><span class="va">f_saem_reduced</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">16</span><span class="op">)</span></span> +<span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span><span class="op">)</span></span></code></pre></div> +<p><img src="multistart_files/figure-html/unnamed-chunk-4-1.png" width="700"></p> +<p>The results confirm that all remaining parameters can be determined with sufficient certainty.</p> +<p>We can also analyse the log-likelihoods obtained in the multiple runs:</p> +<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/llhist.html">llhist</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span><span class="op">)</span></span></code></pre></div> +<p><img src="multistart_files/figure-html/unnamed-chunk-5-1.png" width="700"></p> +<p>The parameter histograms can be further improved by excluding the result with the low likelihood.</p> +<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="../../reference/parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span>, llmin <span class="op">=</span> <span class="op">-</span><span class="fl">326</span>, ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.5</span>, <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> +<p><img src="multistart_files/figure-html/unnamed-chunk-6-1.png" width="700"></p> +<p>We can use the <code>anova</code> method to compare the models, including a likelihood ratio test if the models are nested.</p> +<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r"> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_full</span>, <span class="fu"><a href="../../reference/multistart.html">best</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span><span class="op">)</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div> +<pre><code><span><span class="co">## Data: 155 observations of 1 variable(s) grouped in 6 datasets</span></span> +<span><span class="co">## </span></span> +<span><span class="co">## npar AIC BIC Lik Chisq Df Pr(>Chisq)</span></span> +<span><span class="co">## best(f_saem_reduced_multi) 9 663.64 661.77 -322.82 </span></span> +<span><span class="co">## f_saem_full 10 668.27 666.19 -324.13 0 1 1</span></span></code></pre> +<p>While AIC and BIC are lower for the reduced model, the likelihood ratio test does not indicate a significant difference between the fits.</p> + </div> + + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + + </div> + +</div> + + + + <footer><div class="copyright"> + <p></p> +<p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer> +</div> + + + + + + + </body> +</html> diff --git a/docs/dev/articles/web_only/multistart_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/web_only/multistart_files/accessible-code-block-0.0.1/empty-anchor.js new file mode 100644 index 00000000..ca349fd6 --- /dev/null +++ b/docs/dev/articles/web_only/multistart_files/accessible-code-block-0.0.1/empty-anchor.js @@ -0,0 +1,15 @@ +// Hide empty <a> tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> +// v0.0.1 +// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. + +document.addEventListener('DOMContentLoaded', function() { + const codeList = document.getElementsByClassName("sourceCode"); + for (var i = 0; i < codeList.length; i++) { + var linkList = codeList[i].getElementsByTagName('a'); + for (var j = 0; j < linkList.length; j++) { + if (linkList[j].innerHTML === "") { + linkList[j].setAttribute('aria-hidden', 'true'); + } + } + } +}); diff --git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-2-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-2-1.png Binary files differnew file mode 100644 index 00000000..e3baa59b --- /dev/null +++ b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-2-1.png diff --git 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--git a/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png Binary files differnew file mode 100644 index 00000000..3963e993 --- /dev/null +++ b/docs/dev/articles/web_only/multistart_files/figure-html/unnamed-chunk-6-1.png diff --git a/docs/dev/authors.html b/docs/dev/authors.html index 2ed9ea29..35ae54bd 100644 --- a/docs/dev/authors.html +++ b/docs/dev/authors.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,12 +41,18 @@ <a href="articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -106,13 +112,13 @@ <p>Ranke J (2022). <em>mkin: Kinetic Evaluation of Chemical Degradation Data</em>. -R package version 1.1.0, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown.jrwb.de/mkin/</a>. +R package version 1.1.2, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown.jrwb.de/mkin/</a>. </p> <pre>@Manual{, title = {mkin: Kinetic Evaluation of Chemical Degradation Data}, author = {Johannes Ranke}, year = {2022}, - note = {R package version 1.1.0}, + note = {R package version 1.1.2}, url = {https://pkgdown.jrwb.de/mkin/}, }</pre> @@ -127,7 +133,7 @@ R package version 1.1.0, <a href="https://pkgdown.jrwb.de/mkin/">https://pkgdown </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/index.html b/docs/dev/index.html index 9490235c..5257b590 100644 --- a/docs/dev/index.html +++ b/docs/dev/index.html @@ -45,7 +45,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -55,7 +55,7 @@ <a href="reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -71,12 +71,18 @@ <a href="articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -120,7 +126,7 @@ </h2> <p>You can install the latest released version from <a href="https://cran.r-project.org/package=mkin" class="external-link">CRAN</a> from within R:</p> <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r"> -<code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"mkin"</span><span class="op">)</span></code></pre></div> +<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"mkin"</span><span class="op">)</span></span></code></pre></div> </div> <div class="section level2"> <h2 id="background">Background<a class="anchor" aria-label="anchor" href="#background"></a> @@ -149,7 +155,7 @@ <li>The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.</li> <li>Summary and plotting functions. The <code>summary</code> of an <code>mkinfit</code> object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.</li> <li>The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.</li> -<li>The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) should now be specified as <code>error_model = "obs"</code>.</li> +<li>The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) can be specified as <code>error_model = "obs"</code>.</li> </ul> </div> <div class="section level3"> @@ -161,7 +167,7 @@ <li>By default, kinetic rate constants and kinetic formation fractions are transformed internally using <a href="https://pkgdown.jrwb.de/mkin/reference/transform_odeparms.html"><code>transform_odeparms</code></a> so their estimators can more reasonably be expected to follow a normal distribution.</li> <li>When parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which cannot occur in a single experiment with a single defined radiolabel position.</li> <li>When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite. Mathematically, the SFORB model is equivalent to the DFOP model used by other tools for biphasic metabolite curves. However, the SFORB model has the advantage that there is a mechanistic interpretation of the model parameters.</li> -<li>Nonlinear mixed-effects models can be created from fits of the same degradation model to different datasets for the same compound by using the <a href="https://pkgdown.jrwb.de/mkin/reference/nlme.mmkin.html">nlme.mmkin</a> method. Note that the convergence of the nlme fits depends on the quality of the data. Convergence is better for simple models and data for many groups (e.g. soils).</li> +<li>Nonlinear mixed-effects models can be created from fits of the same degradation model to different datasets for the same compound by using the <a href="https://pkgdown.jrwb.de/mkin/reference/nlme.mmkin.html">nlme.mmkin</a> and <a href="https://pkgdown.jrwb.de/mkin/reference/saem.html">saem.mmkin</a> and methods. Note that the convergence of the nlme fits depends on the quality of the data. Convergence is better for simple models and data for many groups (e.g. soils). The saem method uses the <code>saemix</code> package as a backend. Analytical solutions suitable for use with this package have been implemented for parent only models and the most important models including one metabolite (SFO-SFO and DFOP-SFO). Fitting other models with <code>saem.mmkin</code>, while it makes use of the compiled ODE models that mkin provides, has longer run times (at least six minutes on my system).</li> </ul> </div> <div class="section level3"> @@ -206,26 +212,18 @@ <li>Project Number 120667 (Development of objective criteria for the evaluation of the visual fit in the kinetic evaluation of degradation data, 2019-2020)</li> <li>Project Number 146839 (Checking the feasibility of using mixed-effects models for the derivation of kinetic modelling parameters from degradation studies, 2020-2021)</li> </ul> +<p>Thanks are due also to Emmanuelle Comets, maintainer of the saemix package, for the nice collaboration on using the SAEM algorithm and its implementation in saemix for the evaluation of chemical degradation data.</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a> </h2> <table class="table"> -<tr> -<td> -Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. <i>Environments</i> <b>8</b> (8) 71 <a href="https://doi.org/10.3390/environments8080071" class="external-link">doi:10.3390/environments8080071</a> -</td> -</tr> -<tr> -<td> -Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data <i>Environments</i> <b>6</b> (12) 124 <a href="https://doi.org/10.3390/environments6120124" class="external-link">doi:10.3390/environments6120124</a> -</td> -</tr> -<tr> -<td> -Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data <i>Environmental Sciences Europe</i> <b>30</b> 17 <a href="https://doi.org/10.1186/s12302-018-0145-1" class="external-link">doi:10.1186/s12302-018-0145-1</a> -</td> -</tr> +<tr><td>Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. <i>Environments</i> <b>8</b> (8) 71 <a href="https://doi.org/10.3390/environments8080071" class="external-link">doi:10.3390/environments8080071</a> +</td></tr> +<tr><td>Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data <i>Environments</i> <b>6</b> (12) 124 <a href="https://doi.org/10.3390/environments6120124" class="external-link">doi:10.3390/environments6120124</a> +</td></tr> +<tr><td>Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data <i>Environmental Sciences Europe</i> <b>30</b> 17 <a href="https://doi.org/10.1186/s12302-018-0145-1" class="external-link">doi:10.1186/s12302-018-0145-1</a> +</td></tr> </table> </div> <div class="section level2"> @@ -273,6 +271,7 @@ Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic <h2 data-toc-skip>Dev status</h2> <ul class="list-unstyled"> <li><a href="https://cran.r-project.org/package=mkin" class="external-link"><img src="https://www.r-pkg.org/badges/version/mkin"></a></li> +<li><a href="https://jranke.r-universe.dev/ui#package:mkin" class="external-link"><img src="https://jranke.r-universe.dev/badges/mkin" alt="mkin status badge"></a></li> <li><a href="https://app.travis-ci.com/github/jranke/mkin" class="external-link"><img src="https://travis-ci.com/jranke/mkin.svg?branch=main" alt="Build Status"></a></li> <li><a href="https://codecov.io/github/jranke/mkin" class="external-link"><img src="https://codecov.io/github/jranke/mkin/branch/main/graphs/badge.svg" alt="codecov"></a></li> </ul> @@ -289,7 +288,7 @@ Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic <div class="pkgdown"> <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer> diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html index 39e7a52e..b509aca3 100644 --- a/docs/dev/news/index.html +++ b/docs/dev/news/index.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,12 +41,18 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -79,21 +85,41 @@ </div> <div class="section level2"> -<h2 class="page-header" data-toc-text="1.1.0" id="mkin-110-unreleased">mkin 1.1.0 (unreleased)<a class="anchor" aria-label="anchor" href="#mkin-110-unreleased"></a></h2> +<h2 class="page-header" data-toc-text="1.1.2" id="mkin-112">mkin 1.1.2<a class="anchor" aria-label="anchor" href="#mkin-112"></a></h2> +<ul><li><p>‘R/multistart.R’: New method for testing multiple start parameters for hierarchical model fits, with diagnostic plotting functions ‘llhist’ and ‘parplot’.</p></li> +<li><p>‘R/mhmkin.R’: New method for performing multiple hierarchical mkin fits in one function call, optionally in parallel.</p></li> +<li><p>‘R/saem.R’: Implement and test saemix transformations for FOMC and HS. Also, error out if saemix transformations are requested but not supported.</p></li> +<li><p>‘R/saem.R’: ‘logLik’ and ‘update’ methods for ‘saem.mmkin’ objects.</p></li> +<li><p>‘R/status.R’: New generic to show status information for fit array objects with methods for ‘mmkin’ and ‘mhmkin’ objects.</p></li> +<li><p>‘R/illparms.R’: New generic to show ill-defined parameters with methods for ‘mkinfit’, ‘mmkin’, ‘saem.mmkin’ and ‘mhmkin’ objects.</p></li> +<li><p>‘R/summary.mmkin.R’: Summary method for mmkin objects.</p></li> +</ul></div> + <div class="section level2"> +<h2 class="page-header" data-toc-text="1.1.1" id="mkin-111-2022-07-12">mkin 1.1.1 (2022-07-12)<a class="anchor" aria-label="anchor" href="#mkin-111-2022-07-12"></a></h2> +<ul><li><p>’R/{mkinmod,mkinpredict}.R: Store DLL information in mkinmod objects and use that information in mkinpredict to avoid a performance regression brought by a bugfix in R 4.2.x. Thanks to Tomas Kalibera for his analysis of the problem on the r-package-devel list and his suggestion on how to fix it.</p></li> +<li><p>‘vignettes/FOCUS_L.rmd’: Remove an outdated note referring to a failure to calculate the covariance matrix for DFOP with the L2 dataset. Since 0.9.45.5 the covariance matrix is available</p></li> +<li><p>‘vignettes/web_only/benchmarks.rmd’: Add the first benchmark data using my laptop system, therefore add the CPU when showing the benchmark results.</p></li> +<li><p>‘dimethenamid_2018’: Update example code to use saemix</p></li> +<li><p>‘CAKE_export’: Check for validity of the map argument, updates</p></li> +<li><p>‘saem()’: Slightly improve speed in the case that no analytical solution for saemix is implemented, activate a test of the respective code</p></li> +<li><p>‘mean_degparms’: New argument ‘default_log_parms’ that makes it possible to supply a surrogate value (default) for log parameters that fail the t-test</p></li> +<li><p>‘plot.mixed.mmkin’: Pass the frame argument also to residual plots, take the ‘default_log_parms’ argument for ‘mean_degparms’ used for constructing approximate population curves, plot population curve last to avoid that it is covered by data</p></li> +<li><p>‘plot.mkinfit’: Respect argument ‘maxabs’ for residual plots, and make it possible to give ylim as a list, for row layouts</p></li> +</ul></div> + <div class="section level2"> +<h2 class="page-header" data-toc-text="1.1.0" id="mkin-110-2022-03-14">mkin 1.1.0 (2022-03-14)<a class="anchor" aria-label="anchor" href="#mkin-110-2022-03-14"></a></h2> <div class="section level3"> <h3 id="mixed-effects-models-1-1-0">Mixed-effects models<a class="anchor" aria-label="anchor" href="#mixed-effects-models-1-1-0"></a></h3> -<ul><li><p>Introduce an interface to nlmixr, supporting estimation methods ‘saem’ and ‘focei’: S3 method ‘nlmixr.mmkin’ using the helper functions ‘nlmixr_model’ and ‘nlmixr_data’ to set up nlmixr models for mmkin row objects, with summary and plot methods.</p></li> -<li><p>Reintroduce the interface to saemix (now on CRAN), in particular the generic function ‘saem’ with a generator ‘saem.mmkin’, currently using ‘saemix_model’ and ‘saemix_data’, summary and plot methods</p></li> +<ul><li><p>Reintroduce the interface to saemix version 3.0 (now on CRAN), in particular the generic function ‘saem’ with a generator ‘saem.mmkin’, currently using ‘saemix_model’ and ‘saemix_data’, summary and plot methods</p></li> <li><p>‘mean_degparms’: New argument ‘test_log_parms’ that makes the function only consider log-transformed parameters where the untransformed parameters pass the t-test for a certain confidence level. This can be used to obtain more plausible starting parameters for the different mixed-effects model backends</p></li> <li><p>‘plot.mixed.mmkin’: Gains arguments ‘test_log_parms’ and ‘conf.level’</p></li> <li><p>‘vignettes/web_only/dimethenamid_2018.rmd’: Example evaluations of the dimethenamid data.</p></li> -<li><p>‘intervals’: Provide methods of this nlme function for ‘nlmixr.mmkin’ and ‘saem.mmkin’ objects.</p></li> +<li><p>‘intervals’: Provide a method of this nlme function for ‘saem.mmkin’ objects.</p></li> </ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.5" id="mkin-105-2021-09-15">mkin 1.0.5 (2021-09-15)<a class="anchor" aria-label="anchor" href="#mkin-105-2021-09-15"></a></h2> -<ul><li>‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”</li> -</ul></div> +<ul><li>‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.4" id="mkin-104-2021-04-20">mkin 1.0.4 (2021-04-20)<a class="anchor" aria-label="anchor" href="#mkin-104-2021-04-20"></a></h2> <ul><li><p>All plotting functions setting graphical parameters: Use on.exit() for resetting graphical parameters</p></li> @@ -102,12 +128,10 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.3" id="mkin-103-2021-02-15">mkin 1.0.3 (2021-02-15)<a class="anchor" aria-label="anchor" href="#mkin-103-2021-02-15"></a></h2> -<ul><li>Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages</li> -</ul></div> +<ul><li>Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.2" id="mkin-102-unreleased">mkin 1.0.2 (Unreleased)<a class="anchor" aria-label="anchor" href="#mkin-102-unreleased"></a></h2> -<ul><li>‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’</li> -</ul></div> +<ul><li>‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="1.0.1" id="mkin-101-2021-02-10">mkin 1.0.1 (2021-02-10)<a class="anchor" aria-label="anchor" href="#mkin-101-2021-02-10"></a></h2> <ul><li><p>‘confint.mmkin’, ‘nlme.mmkin’, ‘transform_odeparms’: Fix example code in dontrun sections that failed with current defaults</p></li> @@ -162,8 +186,7 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.49.11" id="mkin-094911-2020-04-20">mkin 0.9.49.11 (2020-04-20)<a class="anchor" aria-label="anchor" href="#mkin-094911-2020-04-20"></a></h2> -<ul><li>Increase a test tolerance to make it pass on all CRAN check machines</li> -</ul></div> +<ul><li>Increase a test tolerance to make it pass on all CRAN check machines</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.49.10" id="mkin-094910-2020-04-18">mkin 0.9.49.10 (2020-04-18)<a class="anchor" aria-label="anchor" href="#mkin-094910-2020-04-18"></a></h2> <ul><li><p>‘nlme.mmkin’: An nlme method for mmkin row objects and an associated S3 class with print, plot, anova and endpoint methods</p></li> @@ -278,8 +301,7 @@ </ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.46" id="mkin-0946-2017-07-24">mkin 0.9.46 (2017-07-24)<a class="anchor" aria-label="anchor" href="#mkin-0946-2017-07-24"></a></h2> -<ul><li>Remove <code>test_FOMC_ill-defined.R</code> as it is too platform dependent</li> -</ul></div> +<ul><li>Remove <code>test_FOMC_ill-defined.R</code> as it is too platform dependent</li></ul></div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.45.2" id="mkin-09452-2017-07-24">mkin 0.9.45.2 (2017-07-24)<a class="anchor" aria-label="anchor" href="#mkin-09452-2017-07-24"></a></h2> <ul><li><p>Rename <code>twa</code> to <code>max_twa_parent</code> to avoid conflict with <code>twa</code> from my <code>pfm</code> package</p></li> @@ -291,8 +313,7 @@ <h2 class="page-header" data-toc-text="0.9.45.1" id="mkin-09451-2016-12-20">mkin 0.9.45.1 (2016-12-20)<a class="anchor" aria-label="anchor" href="#mkin-09451-2016-12-20"></a></h2> <div class="section level3"> <h3 id="new-features-0-9-45-1">New features<a class="anchor" aria-label="anchor" href="#new-features-0-9-45-1"></a></h3> -<ul><li>A <code>twa</code> function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).</li> -</ul></div> +<ul><li>A <code>twa</code> function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.45" id="mkin-0945-2016-12-08">mkin 0.9.45 (2016-12-08)<a class="anchor" aria-label="anchor" href="#mkin-0945-2016-12-08"></a></h2> @@ -307,8 +328,7 @@ <h2 class="page-header" data-toc-text="0.9.44" id="mkin-0944-2016-06-29">mkin 0.9.44 (2016-06-29)<a class="anchor" aria-label="anchor" href="#mkin-0944-2016-06-29"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-44">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-44"></a></h3> -<ul><li>The test <code>test_FOMC_ill-defined</code> failed on several architectures, so the test is now skipped</li> -</ul></div> +<ul><li>The test <code>test_FOMC_ill-defined</code> failed on several architectures, so the test is now skipped</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9.43" id="mkin-0943-2016-06-28">mkin 0.9.43 (2016-06-28)<a class="anchor" aria-label="anchor" href="#mkin-0943-2016-06-28"></a></h2> @@ -342,8 +362,7 @@ <h2 class="page-header" data-toc-text="0.9.42" id="mkin-0942-2016-03-25">mkin 0.9.42 (2016-03-25)<a class="anchor" aria-label="anchor" href="#mkin-0942-2016-03-25"></a></h2> <div class="section level3"> <h3 id="major-changes-0-9-42">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-42"></a></h3> -<ul><li>Add the argument <code>from_max_mean</code> to <code>mkinfit</code>, for fitting only the decline from the maximum observed value for models with a single observed variable</li> -</ul></div> +<ul><li>Add the argument <code>from_max_mean</code> to <code>mkinfit</code>, for fitting only the decline from the maximum observed value for models with a single observed variable</li></ul></div> <div class="section level3"> <h3 id="minor-changes-0-9-42">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-9-42"></a></h3> <ul><li><p>Add plots to <code>compiled_models</code> vignette</p></li> @@ -363,21 +382,18 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-41">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-41"></a></h3> <ul><li> -<code><a href="../reference/summary.mkinfit.html">print.summary.mkinfit()</a></code>: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36</li> -</ul></div> +<code><a href="../reference/summary.mkinfit.html">print.summary.mkinfit()</a></code>: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-40" id="mkin-09-40-2015-07-21">mkin 0.9-40 (2015-07-21)<a class="anchor" aria-label="anchor" href="#mkin-09-40-2015-07-21"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-40">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-40"></a></h3> <ul><li> -<code><a href="../reference/endpoints.html">endpoints()</a></code>: For DFOP and SFORB models, where <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.</li> -</ul></div> +<code><a href="../reference/endpoints.html">endpoints()</a></code>: For DFOP and SFORB models, where <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as <code><a href="https://rdrr.io/r/stats/optimize.html" class="external-link">optimize()</a></code> sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.</li></ul></div> <div class="section level3"> <h3 id="internal-changes-0-9-40">Internal changes<a class="anchor" aria-label="anchor" href="#internal-changes-0-9-40"></a></h3> <ul><li> -<code>DESCRIPTION</code>, <code>NAMESPACE</code>, <code>R/*.R</code>: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.</li> -</ul></div> +<code>DESCRIPTION</code>, <code>NAMESPACE</code>, <code>R/*.R</code>: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-39" id="mkin-09-39-2015-06-26">mkin 0.9-39 (2015-06-26)<a class="anchor" aria-label="anchor" href="#mkin-09-39-2015-06-26"></a></h2> @@ -389,8 +405,7 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-39">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-39"></a></h3> <ul><li> -<code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.</li> -</ul></div> +<code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-38" id="mkin-09-38-2015-06-24">mkin 0.9-38 (2015-06-24)<a class="anchor" aria-label="anchor" href="#mkin-09-38-2015-06-24"></a></h2> @@ -402,8 +417,7 @@ <div class="section level3"> <h3 id="bug-fixes-0-9-38">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-38"></a></h3> <ul><li> -<code><a href="../reference/mkinmod.html">mkinmod()</a></code>: When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.</li> -</ul></div> +<code><a href="../reference/mkinmod.html">mkinmod()</a></code>: When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-36" id="mkin-09-36-2015-06-21">mkin 0.9-36 (2015-06-21)<a class="anchor" aria-label="anchor" href="#mkin-09-36-2015-06-21"></a></h2> @@ -416,15 +430,13 @@ </ul></div> <div class="section level3"> <h3 id="minor-changes-0-9-36">Minor changes<a class="anchor" aria-label="anchor" href="#minor-changes-0-9-36"></a></h3> -<ul><li>Added a simple showcase vignette with an evaluation of FOCUS example dataset D</li> -</ul></div> +<ul><li>Added a simple showcase vignette with an evaluation of FOCUS example dataset D</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-35" id="mkin-09-35-2015-05-15">mkin 0.9-35 (2015-05-15)<a class="anchor" aria-label="anchor" href="#mkin-09-35-2015-05-15"></a></h2> <div class="section level3"> <h3 id="major-changes-0-9-35">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-35"></a></h3> -<ul><li>Switch from RUnit to testthat for testing</li> -</ul></div> +<ul><li>Switch from RUnit to testthat for testing</li></ul></div> <div class="section level3"> <h3 id="bug-fixes-0-9-35">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-35"></a></h3> <ul><li><p><code><a href="../reference/mkinparplot.html">mkinparplot()</a></code>: Avoid warnings that occurred when not all confidence intervals were available in the summary of the fit</p></li> @@ -506,15 +518,13 @@ <h2 class="page-header" data-toc-text="0.9-31" id="mkin-09-31-2014-07-14">mkin 0.9-31 (2014-07-14)<a class="anchor" aria-label="anchor" href="#mkin-09-31-2014-07-14"></a></h2> <div class="section level3"> <h3 id="bug-fixes-0-9-31">Bug fixes<a class="anchor" aria-label="anchor" href="#bug-fixes-0-9-31"></a></h3> -<ul><li>The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in <code><a href="../reference/mkinerrmin.html">mkinerrmin()</a></code> used by the summary function.</li> -</ul></div> +<ul><li>The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in <code><a href="../reference/mkinerrmin.html">mkinerrmin()</a></code> used by the summary function.</li></ul></div> </div> <div class="section level2"> <h2 class="page-header" data-toc-text="0.9-30" id="mkin-09-30-2014-07-11">mkin 0.9-30 (2014-07-11)<a class="anchor" aria-label="anchor" href="#mkin-09-30-2014-07-11"></a></h2> <div class="section level3"> <h3 id="new-features-0-9-30">New features<a class="anchor" aria-label="anchor" href="#new-features-0-9-30"></a></h3> -<ul><li>It is now possible to use formation fractions in combination with turning off the sink in <code><a href="../reference/mkinmod.html">mkinmod()</a></code>.</li> -</ul></div> +<ul><li>It is now possible to use formation fractions in combination with turning off the sink in <code><a href="../reference/mkinmod.html">mkinmod()</a></code>.</li></ul></div> <div class="section level3"> <h3 id="major-changes-0-9-30">Major changes<a class="anchor" aria-label="anchor" href="#major-changes-0-9-30"></a></h3> <ul><li><p>The original and the transformed parameters now have different names (e.g. <code>k_parent</code> and <code>log_k_parent</code>. They also differ in how many they are when we have formation fractions but no pathway to sink.</p></li> @@ -597,7 +607,7 @@ </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index b5257483..12a9b003 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -1,5 +1,5 @@ pandoc: 2.9.2.1 -pkgdown: 2.0.2 +pkgdown: 2.0.6 pkgdown_sha: ~ articles: FOCUS_D: FOCUS_D.html @@ -11,7 +11,8 @@ articles: benchmarks: web_only/benchmarks.html compiled_models: web_only/compiled_models.html dimethenamid_2018: web_only/dimethenamid_2018.html -last_built: 2022-02-28T14:05Z + multistart: web_only/multistart.html +last_built: 2022-10-28T21:37Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/dev/reference/CAKE_export.html b/docs/dev/reference/CAKE_export.html index e187772f..47efd056 100644 --- a/docs/dev/reference/CAKE_export.html +++ b/docs/dev/reference/CAKE_export.html @@ -1,68 +1,13 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - 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+<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - - </head> - - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -73,23 +18,21 @@ specified as well." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -99,6 +42,9 @@ specified as well." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -113,34 +59,27 @@ specified as well." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Export a list of datasets format to a CAKE study file</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/CAKE_export.R'><code>R/CAKE_export.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/CAKE_export.R" class="external-link"><code>R/CAKE_export.R</code></a></small> <div class="hidden name"><code>CAKE_export.Rd</code></div> </div> @@ -149,116 +88,115 @@ specified as well." /> specified as well.</p> </div> - <pre class="usage"><span class='fu'>CAKE_export</span><span class='op'>(</span> - <span class='va'>ds</span>, - map <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='st'>"Parent"</span><span class='op'>)</span>, - links <span class='op'>=</span> <span class='cn'>NA</span>, - filename <span class='op'>=</span> <span class='st'>"CAKE_export.csf"</span>, - path <span class='op'>=</span> <span class='st'>"."</span>, - overwrite <span class='op'>=</span> <span class='cn'>FALSE</span>, - study <span class='op'>=</span> <span class='st'>"Codlemone aerobic soil degradation"</span>, - description <span class='op'>=</span> <span class='st'>""</span>, - time_unit <span class='op'>=</span> <span class='st'>"days"</span>, - res_unit <span class='op'>=</span> <span class='st'>"% AR"</span>, - comment <span class='op'>=</span> <span class='st'>"Created using mkin::CAKE_export"</span>, - date <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Sys.time.html'>Sys.Date</a></span><span class='op'>(</span><span class='op'>)</span>, - optimiser <span class='op'>=</span> <span class='st'>"IRLS"</span> -<span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>ds</th> - <td><p>A named list of datasets in long format as compatible with -<code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> - </tr> - <tr> - <th>map</th> - <td><p>A character vector with CAKE compartment names (Parent, A1, ...), -named with the names used in the list of datasets.</p></td> - </tr> - <tr> - <th>links</th> - <td><p>An optional character vector of target compartments, named with + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">CAKE_export</span><span class="op">(</span></span> +<span> <span class="va">ds</span>,</span> +<span> map <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="st">"Parent"</span><span class="op">)</span>,</span> +<span> links <span class="op">=</span> <span class="cn">NA</span>,</span> +<span> filename <span class="op">=</span> <span class="st">"CAKE_export.csf"</span>,</span> +<span> path <span class="op">=</span> <span class="st">"."</span>,</span> +<span> overwrite <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> study <span class="op">=</span> <span class="st">"Degradinol aerobic soil degradation"</span>,</span> +<span> description <span class="op">=</span> <span class="st">""</span>,</span> +<span> time_unit <span class="op">=</span> <span class="st">"days"</span>,</span> +<span> res_unit <span class="op">=</span> <span class="st">"% AR"</span>,</span> +<span> comment <span class="op">=</span> <span class="st">""</span>,</span> +<span> date <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.Date</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> optimiser <span class="op">=</span> <span class="st">"IRLS"</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>ds</dt> +<dd><p>A named list of datasets in long format as compatible with +<code><a href="mkinfit.html">mkinfit</a></code>.</p></dd> + + +<dt>map</dt> +<dd><p>A character vector with CAKE compartment names (Parent, A1, ...), +named with the names used in the list of datasets.</p></dd> + + +<dt>links</dt> +<dd><p>An optional character vector of target compartments, named with the names of the source compartments. In order to make this easier, the -names are used as in the datasets supplied.</p></td> - </tr> - <tr> - <th>filename</th> - <td><p>Where to write the result. Should end in .csf in order to be -compatible with CAKE.</p></td> - </tr> - <tr> - <th>path</th> - <td><p>An optional path to the output file.</p></td> - </tr> - <tr> - <th>overwrite</th> - <td><p>If TRUE, existing files are overwritten.</p></td> - </tr> - <tr> - <th>study</th> - <td><p>The name of the study.</p></td> - </tr> - <tr> - <th>description</th> - <td><p>An optional description.</p></td> - </tr> - <tr> - <th>time_unit</th> - <td><p>The time unit for the residue data.</p></td> - </tr> - <tr> - <th>res_unit</th> - <td><p>The unit used for the residues.</p></td> - </tr> - <tr> - <th>comment</th> - <td><p>An optional comment.</p></td> - </tr> - <tr> - <th>date</th> - <td><p>The date of file creation.</p></td> - </tr> - <tr> - <th>optimiser</th> - <td><p>Can be OLS or IRLS.</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>The function is called for its side effect.</p> - <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> +names are used as in the datasets supplied.</p></dd> + + +<dt>filename</dt> +<dd><p>Where to write the result. Should end in .csf in order to be +compatible with CAKE.</p></dd> + + +<dt>path</dt> +<dd><p>An optional path to the output file.</p></dd> + + +<dt>overwrite</dt> +<dd><p>If TRUE, existing files are overwritten.</p></dd> + + +<dt>study</dt> +<dd><p>The name of the study.</p></dd> + + +<dt>description</dt> +<dd><p>An optional description.</p></dd> + +<dt>time_unit</dt> +<dd><p>The time unit for the residue data.</p></dd> + + +<dt>res_unit</dt> +<dd><p>The unit used for the residues.</p></dd> + + +<dt>comment</dt> +<dd><p>An optional comment.</p></dd> + + +<dt>date</dt> +<dd><p>The date of file creation.</p></dd> + + +<dt>optimiser</dt> +<dd><p>Can be OLS or IRLS.</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>The function is called for its side effect.</p> + </div> + <div id="author"> + <h2>Author</h2> <p>Johannes Ranke</p> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/D24_2014.html b/docs/dev/reference/D24_2014.html index 9ecb6330..5cf7604c 100644 --- a/docs/dev/reference/D24_2014.html +++ b/docs/dev/reference/D24_2014.html @@ -1,72 +1,17 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - <head> - <meta charset="utf-8"> -<meta http-equiv="X-UA-Compatible" content="IE=edge"> -<meta name="viewport" content="width=device-width, initial-scale=1.0"> - -<title>Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 — D24_2014 • mkin</title> - - -<!-- jquery --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script> -<!-- Bootstrap --> - -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" /> - -<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script> - -<!-- bootstrap-toc --> -<link rel="stylesheet" href="../bootstrap-toc.css"> -<script src="../bootstrap-toc.js"></script> - -<!-- Font Awesome icons --> -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" /> -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" /> - -<!-- clipboard.js --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script> - -<!-- headroom.js --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script> - -<!-- pkgdown --> -<link href="../pkgdown.css" rel="stylesheet"> -<script src="../pkgdown.js"></script> - - - - -<meta property="og:title" content="Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 — D24_2014" /> -<meta property="og:description" content="The five datasets were extracted from the active substance evaluation dossier +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; 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Kinetic evaluations shown for these datasets are intended to illustrate and advance kinetic modelling. The fact that these data and some results are shown here does not imply a license to use them in the context of pesticide registrations, as the use of the data may be -constrained by data protection regulations." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +constrained by data protection regulations."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> -<![endif]--> - +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - - </head> - - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -77,23 +22,21 @@ constrained by data protection regulations." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -103,6 +46,9 @@ constrained by data protection regulations." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -117,34 +63,27 @@ constrained by data protection regulations." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Aerobic soil degradation data on 2,4-D from the EU assessment in 2014</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/D24_2014.R'><code>R/D24_2014.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/D24_2014.R" class="external-link"><code>R/D24_2014.R</code></a></small> <div class="hidden name"><code>D24_2014.Rd</code></div> </div> @@ -157,20 +96,23 @@ context of pesticide registrations, as the use of the data may be constrained by data protection regulations.</p> </div> - <pre class="usage"><span class='va'>D24_2014</span></pre> - - - <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> - - <p>An <a href='mkindsg.html'>mkindsg</a> object grouping five datasets</p> - <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2> + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">D24_2014</span></span></code></pre></div> + </div> + <div id="format"> + <h2>Format</h2> + <p>An <a href="mkindsg.html">mkindsg</a> object grouping five datasets</p> + </div> + <div id="source"> + <h2>Source</h2> <p>Hellenic Ministry of Rural Development and Agriculture (2014) Final addendum to the Renewal Assessment Report - public version - 2,4-D Volume 3 Annex B.8 Fate and behaviour in the environment -<a href='http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-3812'>http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-3812</a></p> - <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> - +<a href="https://open.efsa.europa.eu/study-inventory/EFSA-Q-2013-00811" class="external-link">https://open.efsa.europa.eu/study-inventory/EFSA-Q-2013-00811</a></p> + </div> + <div id="details"> + <h2>Details</h2> <p>Data for the first dataset are from p. 685. Data for the other four datasets were used in the preprocessed versions given in the kinetics section (p. 761ff.), with the exception of residues smaller than 1 for DCP @@ -178,114 +120,119 @@ in the soil from Site I2, where the values given on p. 694 were used.</p> <p>The R code used to create this data object is installed with this package in the 'dataset_generation' directory. In the code, page numbers are given for specific pieces of information in the comments.</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>D24_2014</span><span class='op'>)</span> -</div><div class='output co'>#> <mkindsg> holding 5 mkinds objects -#> Title $title: Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 -#> Occurrence of observed compounds $observed_n: -#> D24 DCP DCA -#> 5 4 4 -#> Time normalisation factors $f_time_norm: -#> [1] 1.6062378 0.7118732 0.7156063 0.7156063 0.8977124 -#> Meta information $meta: -#> study usda_soil_type study_moisture_ref_type -#> Mississippi Cohen 1991 Silt loam <NA> -#> Fayette Liu and Adelfinskaya 2011 Silt loam pF1 -#> RefSol 03-G Liu and Adelfinskaya 2011 Loam pF1 -#> Site E1 Liu and Adelfinskaya 2011 Loam pF1 -#> Site I2 Liu and Adelfinskaya 2011 Loamy sand pF1 -#> rel_moisture temperature -#> Mississippi NA 25 -#> Fayette 0.5 20 -#> RefSol 03-G 0.5 20 -#> Site E1 0.5 20 -#> Site I2 0.5 20</div><div class='input'><span class='co'># \dontrun{</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>D24_2014</span><span class='op'>$</span><span class='va'>ds</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <mkinds> with $title: Mississippi -#> Observed compounds $observed: D24 -#> Sampling times $sampling_times: -#> 0, 2, 4, 7, 15, 24, 35, 56, 71, 114, 183, 273, 365 -#> With a maximum of 1 replicates -#> time D24 -#> 1 0 96.8 -#> 2 2 81.0 -#> 3 4 81.7 -#> 4 7 88.2 -#> 5 15 66.3 -#> 6 24 72.9 -#> 7 35 62.6 -#> 8 56 54.6 -#> 9 71 35.2 -#> 10 114 18.0 -#> 11 183 11.3 -#> 12 273 9.9 -#> 13 365 6.3</div><div class='input'><span class='va'>m_D24</span> <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>D24 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"DCP"</span><span class='op'>)</span>, - DCP <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"DCA"</span><span class='op'>)</span>, - DCA <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>m_D24</span><span class='op'>)</span> -</div><div class='output co'>#> <mkinmod> model generated with -#> Use of formation fractions $use_of_ff: max -#> Specification $spec: -#> $D24 -#> $type: SFO; $to: DCP; $sink: TRUE -#> $DCP -#> $type: SFO; $to: DCA; $sink: TRUE -#> $DCA -#> $type: SFO; $sink: TRUE -#> Coefficient matrix $coefmat available -#> Compiled model $cf available -#> Differential equations: -#> d_D24/dt = - k_D24 * D24 -#> d_DCP/dt = + f_D24_to_DCP * k_D24 * D24 - k_DCP * DCP -#> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA</div><div class='input'><span class='va'>m_D24_2</span> <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>D24 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, to <span class='op'>=</span> <span class='st'>"DCP"</span><span class='op'>)</span>, - DCP <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"DCA"</span><span class='op'>)</span>, - DCA <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>m_D24_2</span><span class='op'>)</span> -</div><div class='output co'>#> <mkinmod> model generated with -#> Use of formation fractions $use_of_ff: max -#> Specification $spec: -#> $D24 -#> $type: DFOP; $to: DCP; $sink: TRUE -#> $DCP -#> $type: SFO; $to: DCA; $sink: TRUE -#> $DCA -#> $type: SFO; $sink: TRUE -#> Compiled model $cf available -#> Differential equations: -#> d_D24/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * -#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) -#> * D24 -#> d_DCP/dt = + f_D24_to_DCP * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * -#> exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 -#> * time))) * D24 - k_DCP * DCP -#> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA</div><div class='input'><span class='co'># }</span> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">D24_2014</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 5 mkinds objects</span> +<span class="r-out co"><span class="r-pr">#></span> Title $title: Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 </span> +<span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> +<span class="r-out co"><span class="r-pr">#></span> D24 DCP DCA </span> +<span class="r-out co"><span class="r-pr">#></span> 5 4 4 </span> +<span class="r-out co"><span class="r-pr">#></span> Time normalisation factors $f_time_norm:</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 1.6062378 0.7118732 0.7156063 0.7156063 0.8977124</span> +<span class="r-out co"><span class="r-pr">#></span> Meta information $meta:</span> +<span class="r-out co"><span class="r-pr">#></span> study usda_soil_type study_moisture_ref_type</span> +<span class="r-out co"><span class="r-pr">#></span> Mississippi Cohen 1991 Silt loam <NA></span> +<span class="r-out co"><span class="r-pr">#></span> Fayette Liu and Adelfinskaya 2011 Silt loam pF1</span> +<span class="r-out co"><span class="r-pr">#></span> RefSol 03-G Liu and Adelfinskaya 2011 Loam pF1</span> +<span class="r-out co"><span class="r-pr">#></span> Site E1 Liu and Adelfinskaya 2011 Loam pF1</span> +<span class="r-out co"><span class="r-pr">#></span> Site I2 Liu and Adelfinskaya 2011 Loamy sand pF1</span> +<span class="r-out co"><span class="r-pr">#></span> rel_moisture temperature</span> +<span class="r-out co"><span class="r-pr">#></span> Mississippi NA 25</span> +<span class="r-out co"><span class="r-pr">#></span> Fayette 0.5 20</span> +<span class="r-out co"><span class="r-pr">#></span> RefSol 03-G 0.5 20</span> +<span class="r-out co"><span class="r-pr">#></span> Site E1 0.5 20</span> +<span class="r-out co"><span class="r-pr">#></span> Site I2 0.5 20</span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">D24_2014</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Mississippi </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: D24 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 2, 4, 7, 15, 24, 35, 56, 71, 114, 183, 273, 365 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 1 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> time D24</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 96.8</span> +<span class="r-out co"><span class="r-pr">#></span> 2 2 81.0</span> +<span class="r-out co"><span class="r-pr">#></span> 3 4 81.7</span> +<span class="r-out co"><span class="r-pr">#></span> 4 7 88.2</span> +<span class="r-out co"><span class="r-pr">#></span> 5 15 66.3</span> +<span class="r-out co"><span class="r-pr">#></span> 6 24 72.9</span> +<span class="r-out co"><span class="r-pr">#></span> 7 35 62.6</span> +<span class="r-out co"><span class="r-pr">#></span> 8 56 54.6</span> +<span class="r-out co"><span class="r-pr">#></span> 9 71 35.2</span> +<span class="r-out co"><span class="r-pr">#></span> 10 114 18.0</span> +<span class="r-out co"><span class="r-pr">#></span> 11 183 11.3</span> +<span class="r-out co"><span class="r-pr">#></span> 12 273 9.9</span> +<span class="r-out co"><span class="r-pr">#></span> 13 365 6.3</span> +<span class="r-in"><span><span class="va">m_D24</span> <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>D24 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, to <span class="op">=</span> <span class="st">"DCP"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> DCP <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, to <span class="op">=</span> <span class="st">"DCA"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> DCA <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">m_D24</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkinmod> model generated with</span> +<span class="r-out co"><span class="r-pr">#></span> Use of formation fractions $use_of_ff: max </span> +<span class="r-out co"><span class="r-pr">#></span> Specification $spec:</span> +<span class="r-out co"><span class="r-pr">#></span> $D24</span> +<span class="r-out co"><span class="r-pr">#></span> $type: SFO; $to: DCP; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> $DCP</span> +<span class="r-out co"><span class="r-pr">#></span> $type: SFO; $to: DCA; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> $DCA</span> +<span class="r-out co"><span class="r-pr">#></span> $type: SFO; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> Coefficient matrix $coefmat available</span> +<span class="r-out co"><span class="r-pr">#></span> Compiled model $cf available</span> +<span class="r-out co"><span class="r-pr">#></span> Differential equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_D24/dt = - k_D24 * D24</span> +<span class="r-out co"><span class="r-pr">#></span> d_DCP/dt = + f_D24_to_DCP * k_D24 * D24 - k_DCP * DCP</span> +<span class="r-out co"><span class="r-pr">#></span> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA</span> +<span class="r-in"><span><span class="va">m_D24_2</span> <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>D24 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, to <span class="op">=</span> <span class="st">"DCP"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> DCP <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, to <span class="op">=</span> <span class="st">"DCA"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> DCA <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">m_D24_2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkinmod> model generated with</span> +<span class="r-out co"><span class="r-pr">#></span> Use of formation fractions $use_of_ff: max </span> +<span class="r-out co"><span class="r-pr">#></span> Specification $spec:</span> +<span class="r-out co"><span class="r-pr">#></span> $D24</span> +<span class="r-out co"><span class="r-pr">#></span> $type: DFOP; $to: DCP; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> $DCP</span> +<span class="r-out co"><span class="r-pr">#></span> $type: SFO; $to: DCA; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> $DCA</span> +<span class="r-out co"><span class="r-pr">#></span> $type: SFO; $sink: TRUE</span> +<span class="r-out co"><span class="r-pr">#></span> Compiled model $cf available</span> +<span class="r-out co"><span class="r-pr">#></span> Differential equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_D24/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * D24</span> +<span class="r-out co"><span class="r-pr">#></span> d_DCP/dt = + f_D24_to_DCP * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2</span> +<span class="r-out co"><span class="r-pr">#></span> * time))) * D24 - k_DCP * DCP</span> +<span class="r-out co"><span class="r-pr">#></span> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a 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The method to calculate the BIC is that from +the saemix package. As in other prominent anova methods, models are sorted"><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Anova method for saem.mmkin objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/anova.saem.mmkin.R" class="external-link"><code>R/anova.saem.mmkin.R</code></a></small> + <div class="hidden name"><code>anova.saem.mmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Generate an anova object. The method to calculate the BIC is that from +the saemix package. As in other prominent anova methods, models are sorted</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> <span class="va">...</span>,</span> +<span> method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"is"</span>, <span class="st">"lin"</span>, <span class="st">"gq"</span><span class="op">)</span>,</span> +<span> test <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> model.names <span class="op">=</span> <span class="cn">NULL</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>An <a href="saem.html">saem.mmkin</a> object</p></dd> + + +<dt>...</dt> +<dd><p>further such objects</p></dd> + + +<dt>method</dt> +<dd><p>Method for likelihood calculation: "is" (importance sampling), +"lin" (linear approximation), or "gq" (Gaussian quadrature). Passed +to <a href="https://rdrr.io/pkg/saemix/man/logLik.html" class="external-link">saemix::logLik.SaemixObject</a></p></dd> + + +<dt>test</dt> +<dd><p>Should a likelihood ratio test be performed? If TRUE, +the alternative models are tested against the first model. Should +only be done for nested models.</p></dd> + + +<dt>model.names</dt> +<dd><p>Optional character vector of model names</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>an "anova" data frame; the traditional (S3) result of anova()</p> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/aw.html b/docs/dev/reference/aw.html index 3b06f2a6..57dfa06c 100644 --- a/docs/dev/reference/aw.html +++ b/docs/dev/reference/aw.html @@ -1,69 +1,14 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - 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</ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Calculate Akaike weights for model averaging</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/aw.R'><code>R/aw.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/aw.R" class="external-link"><code>R/aw.R</code></a></small> <div class="hidden name"><code>aw.Rd</code></div> </div> @@ -151,76 +90,85 @@ expected Kullback-Leibler information as specified by Burnham and Anderson (2004).</p> </div> - <pre class="usage"><span class='fu'>aw</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span> - -<span class='co'># S3 method for mkinfit</span> -<span class='fu'>aw</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span> - -<span class='co'># S3 method for mmkin</span> -<span class='fu'>aw</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span></pre> + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">aw</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu">aw</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">aw</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mixed.mmkin</span></span> +<span><span class="fu">aw</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for multistart</span></span> +<span><span class="fu">aw</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>object</th> - <td><p>An <a href='mmkin.html'>mmkin</a> column object, containing two or more -<a href='mkinfit.html'>mkinfit</a> models that have been fitted to the same data, + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>An <a href="mmkin.html">mmkin</a> column object, containing two or more +<a href="mkinfit.html">mkinfit</a> models that have been fitted to the same data, or an mkinfit object. In the latter case, further mkinfit objects fitted to the same data should be specified -as dots arguments.</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Not used in the method for <a href='mmkin.html'>mmkin</a> column objects, -further <a href='mkinfit.html'>mkinfit</a> objects in the method for mkinfit objects.</p></td> - </tr> - </table> +as dots arguments.</p></dd> + - <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2> +<dt>...</dt> +<dd><p>Not used in the method for <a href="mmkin.html">mmkin</a> column objects, +further <a href="mkinfit.html">mkinfit</a> objects in the method for mkinfit objects.</p></dd> +</dl></div> + <div id="references"> + <h2>References</h2> <p>Burnham KP and Anderson DR (2004) Multimodel Inference: Understanding AIC and BIC in Model Selection. <em>Sociological Methods & Research</em> <strong>33</strong>(2) 261-304</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'><span class='co'># \dontrun{</span> -<span class='va'>f_sfo</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='va'>f_dfop</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='va'>aw_sfo_dfop</span> <span class='op'><-</span> <span class='fu'>aw</span><span class='op'>(</span><span class='va'>f_sfo</span>, <span class='va'>f_dfop</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span><span class='op'>(</span><span class='va'>aw_sfo_dfop</span><span class='op'>)</span> -</div><div class='output co'>#> [1] 1</div><div class='input'><span class='va'>aw_sfo_dfop</span> <span class='co'># SFO gets more weight as it has less parameters and a similar fit</span> -</div><div class='output co'>#> [1] 0.5970258 0.4029742</div><div class='input'><span class='va'>f</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"FOCUS D"</span> <span class='op'>=</span> <span class='va'>FOCUS_2006_D</span><span class='op'>)</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='fu'>aw</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span> -</div><div class='output co'>#> [1] 0.4808722 0.1945539 0.3245740</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/sum.html'>sum</a></span><span class='op'>(</span><span class='fu'>aw</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> [1] 1</div><div class='input'><span class='fu'>aw</span><span class='op'>(</span><span class='va'>f</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> [1] 0.5970258 0.4029742</div><div class='input'><span class='co'># }</span> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">f_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_dfop</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">aw_sfo_dfop</span> <span class="op"><-</span> <span class="fu">aw</span><span class="op">(</span><span class="va">f_sfo</span>, <span class="va">f_dfop</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="va">aw_sfo_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 1</span> +<span class="r-in"><span><span class="va">aw_sfo_dfop</span> <span class="co"># SFO gets more weight as it has less parameters and a similar fit</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.5970258 0.4029742</span> +<span class="r-in"><span><span class="va">f</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS D"</span> <span class="op">=</span> <span class="va">FOCUS_2006_D</span><span class="op">)</span>, cores <span class="op">=</span> <span class="fl">1</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">aw</span><span class="op">(</span><span class="va">f</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.4808722 0.1945539 0.3245740</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">aw</span><span class="op">(</span><span class="va">f</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 1</span> +<span class="r-in"><span><span class="fu">aw</span><span class="op">(</span><span class="va">f</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.5970258 0.4029742</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/convergence.html b/docs/dev/reference/convergence.html new file mode 100644 index 00000000..e9fac3bb --- /dev/null +++ b/docs/dev/reference/convergence.html @@ -0,0 +1,163 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Method to get convergence information — convergence • mkin</title><!-- jquery --><script 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content="Method to get convergence information"><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a 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+<span><span class="fu">convergence</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for convergence.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The object to investigate</p></dd> + + +<dt>...</dt> +<dd><p>For potential future extensions</p></dd> + + +<dt>x</dt> +<dd><p>The object to be printed</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>For <a href="mkinfit.html">mkinfit</a> objects, a character vector containing +For <a href="mmkin.html">mmkin</a> objects, an object of class 'convergence.mmkin' with a +suitable printing method.</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS B"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">convergence</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS B</span> +<span class="r-out co"><span class="r-pr">#></span> SFO OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 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navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -72,23 +17,21 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -98,6 +41,9 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -112,34 +58,27 @@ <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Create degradation functions for known analytical solutions</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/create_deg_func.R'><code>R/create_deg_func.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/create_deg_func.R" class="external-link"><code>R/create_deg_func.R</code></a></small> <div class="hidden name"><code>create_deg_func.Rd</code></div> </div> @@ -147,83 +86,88 @@ <p>Create degradation functions for known analytical solutions</p> </div> - <pre class="usage"><span class='fu'>create_deg_func</span><span class='op'>(</span><span class='va'>spec</span>, use_of_ff <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"min"</span>, <span class='st'>"max"</span><span class='op'>)</span><span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>spec</th> - <td><p>List of model specifications as contained in mkinmod objects</p></td> - </tr> - <tr> - <th>use_of_ff</th> - <td><p>Minimum or maximum use of formation fractions</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>Degradation function to be attached to mkinmod objects</p> - - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> - parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>FOCUS_D</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='co'># to avoid warnings</span> -<span class='va'>fit_1</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"analytical"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='va'>fit_2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='co'># \dontrun{</span> -<span class='kw'>if</span> <span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='va'><a href='http://rbenchmark.googlecode.com'>rbenchmark</a></span><span class='op'>)</span><span class='op'>)</span> - <span class='fu'><a href='https://rdrr.io/pkg/rbenchmark/man/benchmark.html'>benchmark</a></span><span class='op'>(</span> - analytical <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"analytical"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - deSolve <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - replications <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Loading required package: rbenchmark</span></div><div class='output co'>#> test replications elapsed relative user.self sys.self user.child -#> 1 analytical 2 0.396 1.00 0.396 0 0 -#> 2 deSolve 2 0.709 1.79 0.707 0 0 -#> sys.child -#> 1 0 -#> 2 0</div><div class='input'> <span class='va'>DFOP_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> - parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='fu'><a href='https://rdrr.io/pkg/rbenchmark/man/benchmark.html'>benchmark</a></span><span class='op'>(</span> - analytical <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>DFOP_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"analytical"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - deSolve <span class='op'>=</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>DFOP_SFO</span>, <span class='va'>FOCUS_D</span>, solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - replications <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span> -</div><div class='output co'>#> test replications elapsed relative user.self sys.self user.child -#> 1 analytical 2 0.844 1.000 0.844 0 0 -#> 2 deSolve 2 1.624 1.924 1.624 0 0 -#> sys.child -#> 1 0 -#> 2 0</div><div class='input'><span class='co'># }</span> -</div></pre> + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">create_deg_func</span><span class="op">(</span><span class="va">spec</span>, use_of_ff <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"min"</span>, <span class="st">"max"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>spec</dt> +<dd><p>List of model specifications as contained in mkinmod objects</p></dd> + + +<dt>use_of_ff</dt> +<dd><p>Minimum or maximum use of formation fractions</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>Degradation function to be attached to mkinmod objects</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span> <span class="co"># to avoid warnings</span></span></span> +<span class="r-in"><span><span class="va">fit_1</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"analytical"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fit_2</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/rbenchmark/man/benchmark.html" class="external-link">benchmark</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> analytical <span class="op">=</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"analytical"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> deSolve <span class="op">=</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> replications <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Loading required package: rbenchmark</span> +<span class="r-out co"><span class="r-pr">#></span> test replications elapsed relative user.self sys.self user.child</span> +<span class="r-out co"><span class="r-pr">#></span> 1 analytical 2 0.401 1.000 0.401 0 0</span> +<span class="r-out co"><span class="r-pr">#></span> 2 deSolve 2 0.654 1.631 0.654 0 0</span> +<span class="r-out co"><span class="r-pr">#></span> sys.child</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0</span> +<span class="r-in"><span> <span class="va">DFOP_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/rbenchmark/man/benchmark.html" class="external-link">benchmark</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> analytical <span class="op">=</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">DFOP_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"analytical"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> deSolve <span class="op">=</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">DFOP_SFO</span>, <span class="va">FOCUS_D</span>, solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> replications <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> test replications elapsed relative user.self sys.self user.child</span> +<span class="r-out co"><span class="r-pr">#></span> 1 analytical 2 0.843 1.000 0.843 0 0</span> +<span class="r-out co"><span class="r-pr">#></span> 2 deSolve 2 1.445 1.714 1.445 0 0</span> +<span class="r-out co"><span class="r-pr">#></span> sys.child</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/dimethenamid_2018-1.png b/docs/dev/reference/dimethenamid_2018-1.png Binary files differindex b8c5355f..4300b0c0 100644 --- a/docs/dev/reference/dimethenamid_2018-1.png +++ b/docs/dev/reference/dimethenamid_2018-1.png diff --git a/docs/dev/reference/dimethenamid_2018-2.png b/docs/dev/reference/dimethenamid_2018-2.png Binary files differindex 3b8a123b..36db063c 100644 --- a/docs/dev/reference/dimethenamid_2018-2.png +++ b/docs/dev/reference/dimethenamid_2018-2.png diff --git a/docs/dev/reference/dimethenamid_2018-3.png b/docs/dev/reference/dimethenamid_2018-3.png Binary files differnew file mode 100644 index 00000000..7c876208 --- /dev/null +++ b/docs/dev/reference/dimethenamid_2018-3.png diff --git a/docs/dev/reference/dimethenamid_2018.html b/docs/dev/reference/dimethenamid_2018.html index 5fb94988..2454a609 100644 --- a/docs/dev/reference/dimethenamid_2018.html +++ b/docs/dev/reference/dimethenamid_2018.html @@ -22,7 +22,7 @@ constrained by data protection regulations."><meta name="robots" content="noinde </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -31,7 +31,7 @@ constrained by data protection regulations."><meta name="robots" content="noinde <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -46,6 +46,9 @@ constrained by data protection regulations."><meta name="robots" content="noinde <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -94,7 +97,7 @@ constrained by data protection regulations.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">dimethenamid_2018</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">dimethenamid_2018</span></span></code></pre></div> </div> <div id="format"> @@ -117,7 +120,7 @@ specific pieces of information in the comments.</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 7 mkinds objects</span> <span class="r-out co"><span class="r-pr">#></span> Title $title: Aerobic soil degradation data on dimethenamid-P from the EU assessment in 2018 </span> <span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> @@ -142,296 +145,168 @@ specific pieces of information in the comments.</p> <span class="r-out co"><span class="r-pr">#></span> Flaach NA 20</span> <span class="r-out co"><span class="r-pr">#></span> BBA 2.2 NA 20</span> <span class="r-out co"><span class="r-pr">#></span> BBA 2.3 NA 20</span> -<span class="r-in"><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span> -<span class="r-in"> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span> -<span class="r-in"> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span> -<span class="r-in"> <span class="va">ds_i</span></span> -<span class="r-in"><span class="op">}</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span> -<span class="r-in"><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span> -<span class="r-in"><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">dfop_sfo3_plus</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span> -<span class="r-in"> DMTA <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"M23"</span>, <span class="st">"M27"</span>, <span class="st">"M31"</span><span class="op">)</span><span class="op">)</span>,</span> -<span class="r-in"> M23 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> -<span class="r-in"> M27 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span> -<span class="r-in"> M31 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M27"</span>, sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> -<span class="r-in"> quiet <span class="op">=</span> <span class="cn">TRUE</span></span> -<span class="r-in"><span class="op">)</span></span> -<span class="r-in"><span class="va">f_dmta_mkin_tc</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"DFOP-SFO3+"</span> <span class="op">=</span> <span class="va">dfop_sfo3_plus</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">dmta_ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="nlmixr.mmkin.html">nlmixr_model</a></span><span class="op">(</span><span class="va">f_dmta_mkin_tc</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)</span> -<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>number of items to replace is not a multiple of replacement length</span> -<span class="r-out co"><span class="r-pr">#></span> function () </span> -<span class="r-out co"><span class="r-pr">#></span> {</span> -<span class="r-out co"><span class="r-pr">#></span> ini({</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0 = 99</span> -<span class="r-out co"><span class="r-pr">#></span> eta.DMTA_0 ~ 2.3</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M23 = -3.9</span> -<span class="r-out co"><span class="r-pr">#></span> eta.log_k_M23 ~ 0.55</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M27 = -4.3</span> -<span class="r-out co"><span class="r-pr">#></span> eta.log_k_M27 ~ 0.86</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_M31 = -4.2</span> -<span class="r-out co"><span class="r-pr">#></span> eta.log_k_M31 ~ 0.75</span> -<span class="r-out co"><span class="r-pr">#></span> log_k1 = -2.2</span> -<span class="r-out co"><span class="r-pr">#></span> eta.log_k1 ~ 0.9</span> -<span class="r-out co"><span class="r-pr">#></span> log_k2 = -3.8</span> -<span class="r-out co"><span class="r-pr">#></span> eta.log_k2 ~ 1.6</span> -<span class="r-out co"><span class="r-pr">#></span> g_qlogis = 0.44</span> -<span class="r-out co"><span class="r-pr">#></span> eta.g_qlogis ~ 3.1</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_tffm0_1_qlogis = -2.1</span> -<span class="r-out co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_1_qlogis ~ 0.3</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_tffm0_2_qlogis = -2.2</span> -<span class="r-out co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_2_qlogis ~ 0.3</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_tffm0_3_qlogis = -2.1</span> -<span class="r-out co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_3_qlogis ~ 0.3</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low_DMTA = 0.7</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high_DMTA = 0.026</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low_M23 = 0.7</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high_M23 = 0.026</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low_M27 = 0.7</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high_M27 = 0.026</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low_M31 = 0.7</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high_M31 = 0.026</span> -<span class="r-out co"><span class="r-pr">#></span> })</span> -<span class="r-out co"><span class="r-pr">#></span> model({</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA_0_model = DMTA_0 + eta.DMTA_0</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA(0) = DMTA_0_model</span> -<span class="r-out co"><span class="r-pr">#></span> k_M23 = exp(log_k_M23 + eta.log_k_M23)</span> -<span class="r-out co"><span class="r-pr">#></span> k_M27 = exp(log_k_M27 + eta.log_k_M27)</span> -<span class="r-out co"><span class="r-pr">#></span> k_M31 = exp(log_k_M31 + eta.log_k_M31)</span> -<span class="r-out co"><span class="r-pr">#></span> k1 = exp(log_k1 + eta.log_k1)</span> -<span class="r-out co"><span class="r-pr">#></span> k2 = exp(log_k2 + eta.log_k2)</span> -<span class="r-out co"><span class="r-pr">#></span> g = expit(g_qlogis + eta.g_qlogis)</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 = expit(f_DMTA_tffm0_1_qlogis + eta.f_DMTA_tffm0_1_qlogis)</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 = expit(f_DMTA_tffm0_2_qlogis + eta.f_DMTA_tffm0_2_qlogis)</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 = expit(f_DMTA_tffm0_3_qlogis + eta.f_DMTA_tffm0_3_qlogis)</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 = f_DMTA_tffm0_1</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M27 = f_DMTA_tffm0_2 * (1 - f_DMTA_tffm0_1)</span> -<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M31 = f_DMTA_tffm0_3 * (1 - f_DMTA_tffm0_2) * </span> -<span class="r-out co"><span class="r-pr">#></span> (1 - f_DMTA_tffm0_1)</span> -<span class="r-out co"><span class="r-pr">#></span> d/dt(DMTA) = -((k1 * g * exp(-k1 * time) + k2 * (1 - </span> -<span class="r-out co"><span class="r-pr">#></span> g) * exp(-k2 * time))/(g * exp(-k1 * time) + (1 - </span> -<span class="r-out co"><span class="r-pr">#></span> g) * exp(-k2 * time))) * DMTA</span> -<span class="r-out co"><span class="r-pr">#></span> d/dt(M23) = +f_DMTA_to_M23 * ((k1 * g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> (1 - g) * exp(-k2 * time))) * DMTA - k_M23 * M23</span> -<span class="r-out co"><span class="r-pr">#></span> d/dt(M27) = +f_DMTA_to_M27 * ((k1 * g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> (1 - g) * exp(-k2 * time))) * DMTA - k_M27 * M27 + </span> -<span class="r-out co"><span class="r-pr">#></span> k_M31 * M31</span> -<span class="r-out co"><span class="r-pr">#></span> d/dt(M31) = +f_DMTA_to_M31 * ((k1 * g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> k2 * (1 - g) * exp(-k2 * time))/(g * exp(-k1 * time) + </span> -<span class="r-out co"><span class="r-pr">#></span> (1 - g) * exp(-k2 * time))) * DMTA - k_M31 * M31</span> -<span class="r-out co"><span class="r-pr">#></span> DMTA ~ add(sigma_low_DMTA) + prop(rsd_high_DMTA)</span> -<span class="r-out co"><span class="r-pr">#></span> M23 ~ add(sigma_low_M23) + prop(rsd_high_M23)</span> -<span class="r-out co"><span class="r-pr">#></span> M27 ~ add(sigma_low_M27) + prop(rsd_high_M27)</span> -<span class="r-out co"><span class="r-pr">#></span> M31 ~ add(sigma_low_M31) + prop(rsd_high_M31)</span> -<span class="r-out co"><span class="r-pr">#></span> })</span> -<span class="r-out co"><span class="r-pr">#></span> }</span> -<span class="r-out co"><span class="r-pr">#></span> <environment: 0x55555fca3790></span> -<span class="r-in"><span class="co"># The focei fit takes about four minutes on my system</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="va">f_dmta_nlmixr_focei</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_dmta_mkin_tc</span>, est <span class="op">=</span> <span class="st">"focei"</span>,</span> -<span class="r-in"> control <span class="op">=</span> <span class="fu">nlmixr</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/foceiControl.html" class="external-link">foceiControl</a></span><span class="op">(</span>print <span class="op">=</span> <span class="fl">500</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="op">)</span></span> -<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>number of items to replace is not a multiple of replacement length</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BBBB;">ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BBBB;">ℹ</span> Need to run with the source intact to parse comments</span> -<span class="r-msg co"><span class="r-pr">#></span> → creating full model...</span> -<span class="r-msg co"><span class="r-pr">#></span> → pruning branches (`if`/`else`)...</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → loading into <span style="color: #0000BB;">symengine</span> environment...</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → creating full model...</span> -<span class="r-msg co"><span class="r-pr">#></span> → pruning branches (`if`/`else`)...</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → loading into <span style="color: #0000BB;">symengine</span> environment...</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → calculate jacobian</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:01 </span> +<span class="r-in"><span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="co"># We don't use DFOP for the parent compound, as this gives numerical</span></span></span> +<span class="r-in"><span><span class="co"># instabilities in the fits</span></span></span> +<span class="r-in"><span><span class="va">sfo_sfo3p</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> DMTA <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"M23"</span>, <span class="st">"M27"</span>, <span class="st">"M31"</span><span class="op">)</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M23 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M27 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M31 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"M27"</span>, sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span></span></span> +<span class="r-in"><span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_sfo_sfo3p_tc</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"SFO-SFO3+"</span> <span class="op">=</span> <span class="va">sfo_sfo3p</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">dmta_ds</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mmkin> object</span> +<span class="r-out co"><span class="r-pr">#></span> Status of individual fits:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot</span> +<span class="r-out co"><span class="r-pr">#></span> SFO-SFO3+ OK OK OK OK OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-in"><span><span class="co"># The default (test_log_parms = FALSE) gives an undue</span></span></span> +<span class="r-in"><span><span class="co"># influence of ill-defined rate constants that have</span></span></span> +<span class="r-in"><span><span class="co"># extremely small values:</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="dimethenamid_2018-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># If we disregards ill-defined rate constants, the results</span></span></span> +<span class="r-in"><span><span class="co"># look more plausible, but the truth is likely to be in</span></span></span> +<span class="r-in"><span><span class="co"># between these variants</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="dimethenamid_2018-2.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># We can also specify a default value for the failing</span></span></span> +<span class="r-in"><span><span class="co"># log parameters, to mimic FOCUS guidance</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="fu"><a href="mixed.html">mixed</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>,</span></span> +<span class="r-in"><span> default_log_parms <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">2</span><span class="op">)</span><span class="op">/</span><span class="fl">1000</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="dimethenamid_2018-3.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># As these attempts are not satisfying, we use nonlinear mixed-effects models</span></span></span> +<span class="r-in"><span><span class="co"># f_dmta_nlme_tc <- nlme(dmta_sfo_sfo3p_tc)</span></span></span> +<span class="r-in"><span><span class="co"># nlme reaches maxIter = 50 without convergence</span></span></span> +<span class="r-in"><span><span class="va">f_dmta_saem_tc</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">dmta_sfo_sfo3p_tc</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># I am commenting out the convergence plot as rendering them</span></span></span> +<span class="r-in"><span><span class="co"># with pkgdown fails (at least without further tweaks to the</span></span></span> +<span class="r-in"><span><span class="co"># graphics device used)</span></span></span> +<span class="r-in"><span><span class="co">#saemix::plot(f_dmta_saem_tc$so, plot.type = "convergence")</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_dmta_saem_tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.1 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:29:07 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:29:07 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_DMTA/dt = - k_DMTA * DMTA</span> +<span class="r-out co"><span class="r-pr">#></span> d_M23/dt = + f_DMTA_to_M23 * k_DMTA * DMTA - k_M23 * M23</span> +<span class="r-out co"><span class="r-pr">#></span> d_M27/dt = + f_DMTA_to_M27 * k_DMTA * DMTA - k_M27 * M27 + k_M31 * M31</span> +<span class="r-out co"><span class="r-pr">#></span> d_M31/dt = + f_DMTA_to_M31 * k_DMTA * DMTA - k_M31 * M31</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 563 observations of 4 variable(s) grouped in 6 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type deSolve </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 797.539 s</span> +<span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 9 chains</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model: Two-component variance function </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Mean of starting values for individual parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_0 log_k_DMTA log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1 </span> +<span class="r-out co"><span class="r-pr">#></span> 95.5662 -2.9048 -3.8130 -4.1600 -4.1486 0.1341 </span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 f_DMTA_ilr_3 </span> +<span class="r-out co"><span class="r-pr">#></span> 0.1385 -1.6700 </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → calculate sensitivities</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:03 </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → calculate ∂(f)/∂(η)</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:01 </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → calculate ∂(R²)/∂(η)</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:08 </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 2276 2272 -1120</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → finding duplicate expressions in inner model...</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:07 </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_0 88.5943 84.3961 92.7925</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA -3.0466 -3.5609 -2.5322</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -4.0684 -4.9340 -3.2029</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -3.8628 -4.2627 -3.4628</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -3.9803 -4.4804 -3.4801</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 0.1304 -0.2186 0.4795</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 0.1490 -0.2559 0.5540</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -1.3970 -1.6976 -1.0964</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → optimizing duplicate expressions in inner model...</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:06 </span> +<span class="r-out co"><span class="r-pr">#></span> Correlation: </span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_0 l__DMTA lg__M23 lg__M27 lg__M31 f_DMTA__1 f_DMTA__2</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_DMTA 0.0309 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M23 -0.0231 -0.0031 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M27 -0.0381 -0.0048 0.0039 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M31 -0.0251 -0.0031 0.0021 0.0830 </span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_1 -0.0046 -0.0006 0.0417 -0.0437 0.0328 </span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_2 -0.0008 -0.0002 0.0214 -0.0270 -0.0909 -0.0361 </span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_ilr_3 -0.1832 -0.0135 0.0434 0.0804 0.0395 -0.0070 0.0059 </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → finding duplicate expressions in EBE model...</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:00 </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> SD.DMTA_0 3.3651 -0.9649 7.6951</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_DMTA 0.6415 0.2774 1.0055</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M23 1.0176 0.3809 1.6543</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M27 0.4538 0.1522 0.7554</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_M31 0.5684 0.1905 0.9464</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_1 0.4111 0.1524 0.6699</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_2 0.4788 0.1808 0.7768</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_DMTA_ilr_3 0.3501 0.1316 0.5685</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → optimizing duplicate expressions in EBE model...</span> -<span class="r-out co"><span class="r-pr">#></span> [====|====|====|====|====|====|====|====|====|====] 0:00:00 </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.9349 0.8409 1.029</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.1344 0.1178 0.151</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → compiling inner model...</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → finding duplicate expressions in FD model...</span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_0 88.59431 84.396147 92.79246</span> +<span class="r-out co"><span class="r-pr">#></span> k_DMTA 0.04752 0.028413 0.07948</span> +<span class="r-out co"><span class="r-pr">#></span> k_M23 0.01710 0.007198 0.04064</span> +<span class="r-out co"><span class="r-pr">#></span> k_M27 0.02101 0.014084 0.03134</span> +<span class="r-out co"><span class="r-pr">#></span> k_M31 0.01868 0.011329 0.03080</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M23 0.14498 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M27 0.12056 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> f_DMTA_to_M31 0.11015 NA NA</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → optimizing duplicate expressions in FD model...</span> +<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> +<span class="r-out co"><span class="r-pr">#></span> ff</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_M23 0.1450</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_M27 0.1206</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_M31 0.1101</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA_sink 0.6243</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> → compiling EBE model...</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> → compiling events FD model...</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> done</span> -<span class="r-msg co"><span class="r-pr">#></span> Model:</span> -<span class="r-msg co"><span class="r-pr">#></span> cmt(DMTA);</span> -<span class="r-msg co"><span class="r-pr">#></span> cmt(M23);</span> -<span class="r-msg co"><span class="r-pr">#></span> cmt(M27);</span> -<span class="r-msg co"><span class="r-pr">#></span> cmt(M31);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_14~ETA[1]+THETA[1];</span> -<span class="r-msg co"><span class="r-pr">#></span> DMTA(0)=rx_expr_14;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_15~ETA[5]+THETA[5];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_16~ETA[7]+THETA[7];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_17~ETA[6]+THETA[6];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_24~exp(rx_expr_15);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_25~exp(rx_expr_17);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_29~t*rx_expr_24;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_30~t*rx_expr_25;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_31~exp(-(rx_expr_16));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_35~1+rx_expr_31;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_40~1/(rx_expr_35);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_42~(rx_expr_40);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_43~1-rx_expr_42;</span> -<span class="r-msg co"><span class="r-pr">#></span> d/dt(DMTA)=-DMTA*(exp(rx_expr_15-rx_expr_29)/(rx_expr_35)+exp(rx_expr_17-rx_expr_30)*(rx_expr_43))/(exp(-t*rx_expr_24)/(rx_expr_35)+exp(-t*rx_expr_25)*(rx_expr_43));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_18~ETA[2]+THETA[2];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_26~exp(rx_expr_18);</span> -<span class="r-msg co"><span class="r-pr">#></span> d/dt(M23)=-rx_expr_26*M23+DMTA*(exp(rx_expr_15-rx_expr_29)/(rx_expr_35)+exp(rx_expr_17-rx_expr_30)*(rx_expr_43))*f_DMTA_tffm0_1/(exp(-t*rx_expr_24)/(rx_expr_35)+exp(-t*rx_expr_25)*(rx_expr_43));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_19~ETA[3]+THETA[3];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_20~ETA[4]+THETA[4];</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_21~1-f_DMTA_tffm0_1;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_27~exp(rx_expr_19);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_28~exp(rx_expr_20);</span> -<span class="r-msg co"><span class="r-pr">#></span> d/dt(M27)=-rx_expr_27*M27+rx_expr_28*M31+DMTA*(rx_expr_21)*(exp(rx_expr_15-rx_expr_29)/(rx_expr_35)+exp(rx_expr_17-rx_expr_30)*(rx_expr_43))*f_DMTA_tffm0_2/(exp(-t*rx_expr_24)/(rx_expr_35)+exp(-t*rx_expr_25)*(rx_expr_43));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_22~1-f_DMTA_tffm0_2;</span> -<span class="r-msg co"><span class="r-pr">#></span> d/dt(M31)=-rx_expr_28*M31+DMTA*(rx_expr_22)*(rx_expr_21)*(exp(rx_expr_15-rx_expr_29)/(rx_expr_35)+exp(rx_expr_17-rx_expr_30)*(rx_expr_43))*f_DMTA_tffm0_3/(exp(-t*rx_expr_24)/(rx_expr_35)+exp(-t*rx_expr_25)*(rx_expr_43));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_0~CMT==4;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_1~CMT==2;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_2~CMT==1;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_3~CMT==3;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_4~1-(rx_expr_0);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_5~1-(rx_expr_1);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_6~1-(rx_expr_3);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_yj_~(rx_expr_4)*((2*(rx_expr_5)*(rx_expr_2)+2*(rx_expr_1))*(rx_expr_6)+2*(rx_expr_3))+2*(rx_expr_0);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_7~(rx_expr_1);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_8~(rx_expr_3);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_9~(rx_expr_0);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_13~(rx_expr_5);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_32~rx_expr_13*(rx_expr_2);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_lambda_~(rx_expr_4)*((rx_expr_32+rx_expr_7)*(rx_expr_6)+rx_expr_8)+rx_expr_9;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_hi_~(rx_expr_4)*((rx_expr_32+rx_expr_7)*(rx_expr_6)+rx_expr_8)+rx_expr_9;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_low_~0;</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_10~M31*(rx_expr_0);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_11~M27*(rx_expr_3);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_12~M23*(rx_expr_1);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_23~DMTA*(rx_expr_5);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_36~rx_expr_23*(rx_expr_2);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_pred_=(rx_expr_4)*((rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_3)+((rx_expr_1)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))+(rx_expr_5)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_2))*(rx_expr_6))+(rx_expr_0)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)));</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_33~Rx_pow_di(THETA[12],2);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_expr_34~Rx_pow_di(THETA[11],2);</span> -<span class="r-msg co"><span class="r-pr">#></span> rx_r_=(rx_expr_4)*((rx_expr_33*Rx_pow_di(((rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_3)+((rx_expr_1)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))+(rx_expr_5)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_2))*(rx_expr_6)),2)+rx_expr_34)*(rx_expr_3)+((rx_expr_1)*(rx_expr_33*Rx_pow_di(((rx_expr_1)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))+(rx_expr_5)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_2)),2)+rx_expr_34)+(rx_expr_33*Rx_pow_di(((rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_2)),2)+rx_expr_34)*(rx_expr_5)*(rx_expr_2))*(rx_expr_6))+(rx_expr_0)*(rx_expr_33*Rx_pow_di(((rx_expr_4)*((rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_3)+((rx_expr_1)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))+(rx_expr_5)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))*(rx_expr_2))*(rx_expr_6))+(rx_expr_0)*(rx_expr_10+(rx_expr_4)*(rx_expr_11+(rx_expr_12+rx_expr_36)*(rx_expr_6)))),2)+rx_expr_34);</span> -<span class="r-msg co"><span class="r-pr">#></span> DMTA_0=THETA[1];</span> -<span class="r-msg co"><span class="r-pr">#></span> log_k_M23=THETA[2];</span> -<span class="r-msg co"><span class="r-pr">#></span> log_k_M27=THETA[3];</span> -<span class="r-msg co"><span class="r-pr">#></span> log_k_M31=THETA[4];</span> -<span class="r-msg co"><span class="r-pr">#></span> log_k1=THETA[5];</span> -<span class="r-msg co"><span class="r-pr">#></span> log_k2=THETA[6];</span> -<span class="r-msg co"><span class="r-pr">#></span> g_qlogis=THETA[7];</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_tffm0_1_qlogis=THETA[8];</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_tffm0_2_qlogis=THETA[9];</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_tffm0_3_qlogis=THETA[10];</span> -<span class="r-msg co"><span class="r-pr">#></span> sigma_low=THETA[11];</span> -<span class="r-msg co"><span class="r-pr">#></span> rsd_high=THETA[12];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.DMTA_0=ETA[1];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.log_k_M23=ETA[2];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.log_k_M27=ETA[3];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.log_k_M31=ETA[4];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.log_k1=ETA[5];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.log_k2=ETA[6];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.g_qlogis=ETA[7];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_1_qlogis=ETA[8];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_2_qlogis=ETA[9];</span> -<span class="r-msg co"><span class="r-pr">#></span> eta.f_DMTA_tffm0_3_qlogis=ETA[10];</span> -<span class="r-msg co"><span class="r-pr">#></span> DMTA_0_model=rx_expr_14;</span> -<span class="r-msg co"><span class="r-pr">#></span> k_M23=rx_expr_26;</span> -<span class="r-msg co"><span class="r-pr">#></span> k_M27=rx_expr_27;</span> -<span class="r-msg co"><span class="r-pr">#></span> k_M31=rx_expr_28;</span> -<span class="r-msg co"><span class="r-pr">#></span> k1=rx_expr_24;</span> -<span class="r-msg co"><span class="r-pr">#></span> k2=rx_expr_25;</span> -<span class="r-msg co"><span class="r-pr">#></span> g=1/(rx_expr_35);</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M23=1/(1+exp(-(ETA[8]+THETA[8])));</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M23=1/(1+exp(-(ETA[9]+THETA[9])));</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M23=1/(1+exp(-(ETA[10]+THETA[10])));</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M23=f_DMTA_tffm0_1;</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M27=(rx_expr_21)*f_DMTA_tffm0_2;</span> -<span class="r-msg co"><span class="r-pr">#></span> f_DMTA_to_M31=(rx_expr_22)*(rx_expr_21)*f_DMTA_tffm0_3;</span> -<span class="r-msg co"><span class="r-pr">#></span> tad=tad();</span> -<span class="r-msg co"><span class="r-pr">#></span> dosenum=dosenum();</span> -<span class="r-msg co"><span class="r-pr">#></span> Needed Covariates:</span> -<span class="r-msg co"><span class="r-pr">#></span> [1] "f_DMTA_tffm0_1" "f_DMTA_tffm0_2" "f_DMTA_tffm0_3" "CMT" </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">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):</span> Not all the covariates are in the dataset.</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 119.8 9.331 129.2</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 120 9.331 129.3</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_dmta_nlmixr_focei</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in summary(f_dmta_nlmixr_focei):</span> object 'f_dmta_nlmixr_focei' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_dmta_nlmixr_focei</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in plot(f_dmta_nlmixr_focei):</span> object 'f_dmta_nlmixr_focei' not found</span> -<span class="r-in"><span class="co"># Using saemix takes about 18 minutes</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="va">f_dmta_saemix</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_dmta_mkin_tc</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="op">)</span></span> -<span class="r-out co"><span class="r-pr">#></span> DINTDY- T (=R1) illegal </span> -<span class="r-out co"><span class="r-pr">#></span> In above message, R1 = 115.507</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> T not in interval TCUR - HU (= R1) to TCUR (=R2) </span> -<span class="r-out co"><span class="r-pr">#></span> In above message, R1 = 112.133, R2 = 113.577</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> DLSODA- At T (=R1), too much accuracy requested </span> -<span class="r-out co"><span class="r-pr">#></span> for precision of machine.. See TOLSF (=R2) </span> -<span class="r-out co"><span class="r-pr">#></span> In above message, R1 = 55.3899, R2 = nan</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in out[available, var]:</span> (subscript) logical subscript too long</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 11.84 0.008 11.85</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 12.16 0.008 12.17</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># nlmixr with est = "saem" is pretty fast with default iteration numbers, most</span></span> -<span class="r-in"><span class="co"># of the time (about 2.5 minutes) is spent for calculating the log likelihood at the end</span></span> -<span class="r-in"><span class="co"># The likelihood calculated for the nlmixr fit is much lower than that found by saemix</span></span> -<span class="r-in"><span class="co"># Also, the trace plot and the plot of the individual predictions is not</span></span> -<span class="r-in"><span class="co"># convincing for the parent. It seems we are fitting an overparameterised</span></span> -<span class="r-in"><span class="co"># model, so the result we get strongly depends on starting parameters and control settings.</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/system.time.html" class="external-link">system.time</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="va">f_dmta_nlmixr_saem</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></span><span class="op">(</span><span class="va">f_dmta_mkin_tc</span>, est <span class="op">=</span> <span class="st">"saem"</span>,</span> -<span class="r-in"> control <span class="op">=</span> <span class="fu">nlmixr</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/nlmixr/man/saemControl.html" class="external-link">saemControl</a></span><span class="op">(</span>print <span class="op">=</span> <span class="fl">500</span>, logLik <span class="op">=</span> <span class="cn">TRUE</span>, nmc <span class="op">=</span> <span class="fl">9</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BBBB;">ℹ</span> parameter labels from comments are typically ignored in non-interactive mode</span> -<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BBBB;">ℹ</span> Need to run with the source intact to parse comments</span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in eval(substitute(expr), data, enclos = parent.frame()):</span> Cannot run SAEM since some of the parameters are not mu-referenced (eta.f_DMTA_tffm0_1_qlogis, eta.f_DMTA_tffm0_2_qlogis, eta.f_DMTA_tffm0_3_qlogis)</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 0.892 0.004 0.896</span> -<span class="r-msg co"><span class="r-pr">#></span> Timing stopped at: 1.096 0.005 1.1</span> -<span class="r-in"><span class="fu">traceplot</span><span class="op">(</span><span class="va">f_dmta_nlmixr_saem</span><span class="op">$</span><span class="va">nm</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in traceplot(f_dmta_nlmixr_saem$nm):</span> could not find function "traceplot"</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_dmta_nlmixr_saem</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in summary(f_dmta_nlmixr_saem):</span> object 'f_dmta_nlmixr_saem' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_dmta_nlmixr_saem</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in plot(f_dmta_nlmixr_saem):</span> object 'f_dmta_nlmixr_saem' not found</span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> +<span class="r-out co"><span class="r-pr">#></span> DMTA 14.59 48.45</span> +<span class="r-out co"><span class="r-pr">#></span> M23 40.52 134.62</span> +<span class="r-out co"><span class="r-pr">#></span> M27 32.99 109.60</span> +<span class="r-out co"><span class="r-pr">#></span> M31 37.11 123.26</span> +<span class="r-in"><span><span class="co"># As the confidence interval for the random effects of DMTA_0</span></span></span> +<span class="r-in"><span><span class="co"># includes zero, we could try an alternative model without</span></span></span> +<span class="r-in"><span><span class="co"># such random effects</span></span></span> +<span class="r-in"><span><span class="co"># f_dmta_saem_tc_2 <- saem(dmta_sfo_sfo3p_tc,</span></span></span> +<span class="r-in"><span><span class="co"># covariance.model = diag(c(0, rep(1, 7))))</span></span></span> +<span class="r-in"><span><span class="co"># saemix::plot(f_dmta_saem_tc_2$so, plot.type = "convergence")</span></span></span> +<span class="r-in"><span><span class="co"># This does not perform better judged by AIC and BIC</span></span></span> +<span class="r-in"><span><span class="co"># saemix::compare.saemix(f_dmta_saem_tc$so, f_dmta_saem_tc_2$so)</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -446,7 +321,7 @@ specific pieces of information in the comments.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/endpoints.html b/docs/dev/reference/endpoints.html index a472b054..ed72ec47 100644 --- a/docs/dev/reference/endpoints.html +++ b/docs/dev/reference/endpoints.html @@ -23,7 +23,7 @@ advantage that the SFORB model can also be used for metabolites."><meta name="ro </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -32,7 +32,7 @@ advantage that the SFORB model can also be used for metabolites."><meta name="ro <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -47,6 +47,9 @@ advantage that the SFORB model can also be used for metabolites."><meta name="ro <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -95,21 +98,24 @@ advantage that the SFORB model can also be used for metabolites.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">endpoints</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">endpoints</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>fit</dt> -<dd><p>An object of class <a href="mkinfit.html">mkinfit</a>, <a href="nlme.mmkin.html">nlme.mmkin</a>, <a href="saem.html">saem.mmkin</a> or -<a href="nlmixr.mmkin.html">nlmixr.mmkin</a>. Or another object that has list components +<dd><p>An object of class <a href="mkinfit.html">mkinfit</a>, <a href="nlme.mmkin.html">nlme.mmkin</a> or <a href="saem.html">saem.mmkin</a>, +or another object that has list components mkinmod containing an <a href="mkinmod.html">mkinmod</a> degradation model, and two numeric vectors, bparms.optim and bparms.fixed, that contain parameter values for that model.</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>A list with a matrix of dissipation times named distimes, + + +<p>A list with a matrix of dissipation times named distimes, and, if applicable, a vector of formation fractions named ff and, if the SFORB model was in use, a vector of eigenvalues of these SFORB models, equivalent to DFOP rate constants</p> @@ -131,22 +137,22 @@ HS and DFOP, as well as from Eigenvalues b1 and b2 of any SFORB models</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span> -<span class="r-in"> <span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $distimes</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back</span> <span class="r-out co"><span class="r-pr">#></span> parent 1.785233 15.1479 4.559973</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"> <span class="co"># \dontrun{</span></span> -<span class="r-in"> <span class="va">fit_2</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit_2</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span> <span class="va">fit_2</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit_2</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $distimes</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_k1 DT50_k2</span> <span class="r-out co"><span class="r-pr">#></span> parent 1.886925 21.25106 6.397207 1.508293 38.83438</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"> <span class="va">fit_3</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFORB"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit_3</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="va">fit_3</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFORB"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu">endpoints</span><span class="op">(</span><span class="va">fit_3</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $ff</span> <span class="r-out co"><span class="r-pr">#></span> parent_free </span> <span class="r-out co"><span class="r-pr">#></span> 1 </span> @@ -159,8 +165,8 @@ HS and DFOP, as well as from Eigenvalues b1 and b2 of any SFORB models</p> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_parent_b1 DT50_parent_b2</span> <span class="r-out co"><span class="r-pr">#></span> parent 1.886925 21.25106 6.397208 1.508293 38.83438</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"> <span class="co"># }</span></span> -<span class="r-in"></span> +<span class="r-in"><span> <span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> </code></pre></div> </div> </div> @@ -175,7 +181,7 @@ HS and DFOP, as well as from Eigenvalues b1 and b2 of any SFORB models</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/illparms.html 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For this test, the parameterisation +without parameter transformations is used.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for illparms.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, errmod <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mhmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, errmod <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for illparms.mhmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The object to investigate</p></dd> + + +<dt>...</dt> +<dd><p>For potential future extensions</p></dd> + + +<dt>conf.level</dt> +<dd><p>The confidence level for checking p values</p></dd> + + +<dt>x</dt> +<dd><p>The object to be printed</p></dd> + + +<dt>random</dt> +<dd><p>For hierarchical fits, should random effects be tested?</p></dd> + + +<dt>errmod</dt> +<dd><p>For hierarchical fits, should error model parameters be +tested?</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>For <a href="mkinfit.html">mkinfit</a> or <a href="saem.html">saem</a> objects, a character vector of parameter +names. For <a href="mmkin.html">mmkin</a> or <a href="mhmkin.html">mhmkin</a> objects, a matrix like object of class +'illparms.mmkin' or 'illparms.mhmkin'. The latter objects have a suitable +printing method.</p> + </div> + <div id="details"> + <h2>Details</h2> + <p>The method for hierarchical model fits, also known as nonlinear +mixed-effects model fits as obtained with <a href="saem.html">saem</a> and <a href="mhmkin.html">mhmkin</a> +checks if any of the confidence intervals for the random +effects expressed as standard deviations include zero, and if +the confidence intervals for the error model parameters include +zero.</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_A</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">illparms</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "parent_0" "alpha" "beta" "sigma" </span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS C"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">illparms</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC parent_0, alpha, beta, sigma </span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html index afd3692d..0fac6842 100644 --- a/docs/dev/reference/index.html +++ b/docs/dev/reference/index.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,12 +41,18 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -95,9 +101,35 @@ <td><p>Fit one or more kinetic models with one or more state variables to one or more datasets</p></td> </tr><tr><td> - <p><code><a href="nafta.html">nafta()</a></code> <code><a href="nafta.html">print(<i><nafta></i>)</a></code> </p> + <p><code><a href="mhmkin.html">mhmkin()</a></code> <code><a href="mhmkin.html">`[`(<i><mhmkin></i>)</a></code> <code><a href="mhmkin.html">print(<i><mhmkin></i>)</a></code> </p> </td> - <td><p>Evaluate parent kinetics using the NAFTA guidance</p></td> + <td><p>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</p></td> + </tr></tbody><tbody><tr><th colspan="2"> + <h2 id="generics">Generics <a href="#generics" class="anchor" aria-hidden="true"></a></h2> + <p class="section-desc"></p><p>Generic functions introduced by the package</p> + </th> + </tr></tbody><tbody><tr><td> + <p><code><a href="parms.html">parms()</a></code> </p> + </td> + <td><p>Extract model parameters</p></td> + </tr><tr><td> + <p><code><a href="status.html">status()</a></code> <code><a href="status.html">print(<i><status.mmkin></i>)</a></code> <code><a href="status.html">print(<i><status.mhmkin></i>)</a></code> </p> + </td> + <td><p>Method to get status information for fit array objects</p></td> + </tr><tr><td> + <p><code><a href="illparms.html">illparms()</a></code> <code><a href="illparms.html">print(<i><illparms.mmkin></i>)</a></code> <code><a href="illparms.html">print(<i><illparms.mhmkin></i>)</a></code> </p> + </td> + <td><p>Method to get the names of ill-defined parameters</p></td> + </tr><tr><td> + <p><code><a href="endpoints.html">endpoints()</a></code> </p> + </td> + <td><p>Function to calculate endpoints for further use from kinetic models fitted +with mkinfit</p></td> + </tr><tr><td> + <p><code><a href="aw.html">aw()</a></code> </p> + </td> + <td><p>Calculate Akaike weights for model averaging</p></td> </tr></tbody><tbody><tr><th colspan="2"> <h2 id="show-results">Show results <a href="#show-results" class="anchor" aria-hidden="true"></a></h2> <p class="section-desc"></p><p>Functions working with mkinfit objects</p> @@ -111,10 +143,6 @@ more datasets</p></td> </td> <td><p>Summary method for class "mkinfit"</p></td> </tr><tr><td> - <p><code><a href="parms.html">parms()</a></code> </p> - </td> - <td><p>Extract model parameters from mkinfit models</p></td> - </tr><tr><td> <p><code><a href="confint.mkinfit.html">confint(<i><mkinfit></i>)</a></code> </p> </td> <td><p>Confidence intervals for parameters of mkinfit objects</p></td> @@ -135,15 +163,6 @@ more datasets</p></td> </td> <td><p>Calculate the minimum error to assume in order to pass the variance test</p></td> </tr><tr><td> - <p><code><a href="endpoints.html">endpoints()</a></code> </p> - </td> - <td><p>Function to calculate endpoints for further use from kinetic models fitted -with mkinfit</p></td> - </tr><tr><td> - <p><code><a href="aw.html">aw()</a></code> </p> - </td> - <td><p>Calculate Akaike weights for model averaging</p></td> - </tr><tr><td> <p><code><a href="CAKE_export.html">CAKE_export()</a></code> </p> </td> <td><p>Export a list of datasets format to a CAKE study file</p></td> @@ -164,22 +183,27 @@ of an mmkin object</p></td> <p><code><a href="AIC.mmkin.html">AIC(<i><mmkin></i>)</a></code> <code><a href="AIC.mmkin.html">BIC(<i><mmkin></i>)</a></code> </p> </td> <td><p>Calculate the AIC for a column of an mmkin object</p></td> + </tr><tr><td> + <p><code><a href="summary.mmkin.html">summary(<i><mmkin></i>)</a></code> <code><a href="summary.mmkin.html">print(<i><summary.mmkin></i>)</a></code> </p> + </td> + <td><p>Summary method for class "mmkin"</p></td> </tr></tbody><tbody><tr><th colspan="2"> <h2 id="mixed-models">Mixed models <a href="#mixed-models" class="anchor" aria-hidden="true"></a></h2> - <p class="section-desc"></p><p>Create and work with nonlinear mixed effects models</p> + <p class="section-desc"></p><p>Create and work with nonlinear hierarchical models</p> </th> </tr></tbody><tbody><tr><td> <p><code><a href="nlme.mmkin.html">nlme(<i><mmkin></i>)</a></code> <code><a href="nlme.mmkin.html">print(<i><nlme.mmkin></i>)</a></code> <code><a href="nlme.mmkin.html">update(<i><nlme.mmkin></i>)</a></code> </p> </td> <td><p>Create an nlme model for an mmkin row object</p></td> </tr><tr><td> - <p><code><a href="saem.html">saem()</a></code> <code><a href="saem.html">print(<i><saem.mmkin></i>)</a></code> <code><a href="saem.html">saemix_model()</a></code> <code><a href="saem.html">saemix_data()</a></code> </p> + <p><code><a href="saem.html">saem()</a></code> <code><a href="saem.html">print(<i><saem.mmkin></i>)</a></code> <code><a href="saem.html">saemix_model()</a></code> <code><a href="saem.html">saemix_data()</a></code> <code><a href="saem.html">parms(<i><saem.mmkin></i>)</a></code> </p> </td> <td><p>Fit nonlinear mixed models with SAEM</p></td> </tr><tr><td> - <p><code><a href="nlmixr.mmkin.html">nlmixr(<i><mmkin></i>)</a></code> <code><a href="nlmixr.mmkin.html">print(<i><nlmixr.mmkin></i>)</a></code> <code><a href="nlmixr.mmkin.html">nlmixr_model()</a></code> <code><a href="nlmixr.mmkin.html">nlmixr_data()</a></code> </p> + <p><code><a href="mhmkin.html">mhmkin()</a></code> <code><a href="mhmkin.html">`[`(<i><mhmkin></i>)</a></code> <code><a href="mhmkin.html">print(<i><mhmkin></i>)</a></code> </p> </td> - <td><p>Fit nonlinear mixed models using nlmixr</p></td> + <td><p>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</p></td> </tr><tr><td> <p><code><a href="plot.mixed.mmkin.html">plot(<i><mixed.mmkin></i>)</a></code> </p> </td> @@ -189,14 +213,18 @@ of an mmkin object</p></td> </td> <td><p>Summary method for class "nlme.mmkin"</p></td> </tr><tr><td> - <p><code><a href="summary.nlmixr.mmkin.html">summary(<i><nlmixr.mmkin></i>)</a></code> <code><a href="summary.nlmixr.mmkin.html">print(<i><summary.nlmixr.mmkin></i>)</a></code> </p> - </td> - <td><p>Summary method for class "nlmixr.mmkin"</p></td> - </tr><tr><td> <p><code><a href="summary.saem.mmkin.html">summary(<i><saem.mmkin></i>)</a></code> <code><a href="summary.saem.mmkin.html">print(<i><summary.saem.mmkin></i>)</a></code> </p> </td> <td><p>Summary method for class "saem.mmkin"</p></td> </tr><tr><td> + <p><code><a href="anova.saem.mmkin.html">anova(<i><saem.mmkin></i>)</a></code> </p> + </td> + <td><p>Anova method for saem.mmkin objects</p></td> + </tr><tr><td> + <p><code><a href="logLik.saem.mmkin.html">logLik(<i><saem.mmkin></i>)</a></code> </p> + </td> + <td><p>logLik method for saem.mmkin objects</p></td> + </tr><tr><td> <p><code><a href="nlme.html">nlme_function()</a></code> <code><a href="nlme.html">nlme_data()</a></code> </p> </td> <td><p>Helper functions to create nlme models from mmkin row objects</p></td> @@ -209,7 +237,7 @@ of an mmkin object</p></td> </td> <td><p>Create a mixed effects model from an mmkin row object</p></td> </tr><tr><td> - <p><code><a href="reexports.html">reexports</a></code> </p> + <p><code><a href="reexports.html">reexports</a></code> <code><a href="reexports.html">intervals</a></code> <code><a href="reexports.html">lrtest</a></code> <code><a href="reexports.html">nlme</a></code> </p> </td> <td><p>Objects exported from other packages</p></td> </tr><tr><td> @@ -217,9 +245,17 @@ of an mmkin object</p></td> </td> <td><p>Confidence intervals for parameters in saem.mmkin objects</p></td> </tr><tr><td> - <p><code><a href="intervals.nlmixr.mmkin.html">intervals(<i><nlmixr.mmkin></i>)</a></code> </p> + <p><code><a href="multistart.html">multistart()</a></code> <code><a href="multistart.html">print(<i><multistart></i>)</a></code> <code><a href="multistart.html">best()</a></code> <code><a href="multistart.html">which.best()</a></code> </p> + </td> + <td><p>Perform a hierarchical model fit with multiple starting values</p></td> + </tr><tr><td> + <p><code><a href="llhist.html">llhist()</a></code> </p> </td> - <td><p>Confidence intervals for parameters in nlmixr.mmkin objects</p></td> + <td><p>Plot the distribution of log likelihoods from multistart objects</p></td> + </tr><tr><td> + <p><code><a href="parplot.html">parplot()</a></code> </p> + </td> + <td><p>Plot parameter variability of multistart objects</p></td> </tr></tbody><tbody><tr><th colspan="2"> <h2 id="datasets-and-known-results">Datasets and known results <a href="#datasets-and-known-results" class="anchor" aria-hidden="true"></a></h2> <p class="section-desc"></p> @@ -313,6 +349,10 @@ of an mmkin object</p></td> </td> <td><p>Normalisation factors for aerobic soil degradation according to FOCUS guidance</p></td> </tr><tr><td> + <p><code><a href="set_nd_nq.html">set_nd_nq()</a></code> <code><a href="set_nd_nq.html">set_nd_nq_focus()</a></code> </p> + </td> + <td><p>Set non-detects and unquantified values in residue series without replicates</p></td> + </tr><tr><td> <p><code><a href="max_twa_parent.html">max_twa_parent()</a></code> <code><a href="max_twa_parent.html">max_twa_sfo()</a></code> <code><a href="max_twa_parent.html">max_twa_fomc()</a></code> <code><a href="max_twa_parent.html">max_twa_dfop()</a></code> <code><a href="max_twa_parent.html">max_twa_hs()</a></code> </p> </td> <td><p>Function to calculate maximum time weighted average concentrations from @@ -342,10 +382,6 @@ kinetic models fitted with mkinfit</p></td> </td> <td><p>Function to perform isometric log-ratio transformation</p></td> </tr><tr><td> - <p><code><a href="tffm0.html">tffm0()</a></code> <code><a href="tffm0.html">invtffm0()</a></code> </p> - </td> - <td><p>Transform formation fractions as in the first published mkin version</p></td> - </tr><tr><td> <p><code><a href="logLik.mkinfit.html">logLik(<i><mkinfit></i>)</a></code> </p> </td> <td><p>Calculated the log-likelihood of a fitted mkinfit object</p></td> @@ -442,7 +478,7 @@ kinetic models fitted with mkinfit</p></td> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/intervals.saem.mmkin.html b/docs/dev/reference/intervals.saem.mmkin.html index 8e6a348b..ee714ad0 100644 --- a/docs/dev/reference/intervals.saem.mmkin.html +++ b/docs/dev/reference/intervals.saem.mmkin.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,6 +41,9 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -84,27 +87,36 @@ </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html" class="external-link">intervals</a></span><span class="op">(</span><span class="va">object</span>, level <span class="op">=</span> <span class="fl">0.95</span>, backtransform <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html" class="external-link">intervals</a></span><span class="op">(</span><span class="va">object</span>, level <span class="op">=</span> <span class="fl">0.95</span>, backtransform <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>object</dt> <dd><p>The fitted saem.mmkin object</p></dd> + + <dt>level</dt> <dd><p>The confidence level. Must be the default of 0.95 as this is what is available in the saemix object</p></dd> + + <dt>backtransform</dt> <dd><p>In case the model was fitted with mkin transformations, should we backtransform the parameters where a one to one correlation between transformed and backtransformed parameters exists?</p></dd> + + <dt>...</dt> <dd><p>For compatibility with the generic method</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>An object with 'intervals.saem.mmkin' and 'intervals.lme' in the + + +<p>An object with 'intervals.saem.mmkin' and 'intervals.lme' in the class attribute</p> </div> @@ -120,7 +132,7 @@ class attribute</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/llhist.html b/docs/dev/reference/llhist.html new file mode 100644 index 00000000..e110416e --- /dev/null +++ b/docs/dev/reference/llhist.html @@ -0,0 +1,148 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Plot the distribution of log likelihoods from multistart objects — llhist • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Plot the distribution of log likelihoods from multistart objects — llhist"><meta property="og:description" content="Produces a histogram of log-likelihoods. In addition, the likelihood of the +original fit is shown as a red vertical line."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Plot the distribution of log likelihoods from multistart objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/llhist.R" class="external-link"><code>R/llhist.R</code></a></small> + <div class="hidden name"><code>llhist.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Produces a histogram of log-likelihoods. In addition, the likelihood of the +original fit is shown as a red vertical line.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">llhist</span><span class="op">(</span><span class="va">object</span>, breaks <span class="op">=</span> <span class="st">"Sturges"</span>, lpos <span class="op">=</span> <span class="st">"topleft"</span>, main <span class="op">=</span> <span class="st">""</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The <a href="multistart.html">multistart</a> object</p></dd> + + +<dt>breaks</dt> +<dd><p>Passed to <a href="https://rdrr.io/r/graphics/hist.html" class="external-link">hist</a></p></dd> + + +<dt>lpos</dt> +<dd><p>Positioning of the legend.</p></dd> + + +<dt>main</dt> +<dd><p>Title of the plot</p></dd> + + +<dt>...</dt> +<dd><p>Passed to <a href="https://rdrr.io/r/graphics/hist.html" class="external-link">hist</a></p></dd> + +</dl></div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="multistart.html">multistart</a></p></div> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/logLik.saem.mmkin.html b/docs/dev/reference/logLik.saem.mmkin.html new file mode 100644 index 00000000..99b3b906 --- /dev/null +++ b/docs/dev/reference/logLik.saem.mmkin.html @@ -0,0 +1,135 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>logLik method for saem.mmkin objects — logLik.saem.mmkin • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script 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data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>logLik method for saem.mmkin objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/saem.R" class="external-link"><code>R/saem.R</code></a></small> + <div class="hidden name"><code>logLik.saem.mmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>logLik method for saem.mmkin objects</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/logLik.html" class="external-link">logLik</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span>, method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"is"</span>, <span class="st">"lin"</span>, <span class="st">"gq"</span><span class="op">)</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The fitted <a href="saem.html">saem.mmkin</a> object</p></dd> + + +<dt>...</dt> +<dd><p>Passed to <a href="https://rdrr.io/pkg/saemix/man/logLik.html" class="external-link">saemix::logLik.SaemixObject</a></p></dd> + + +<dt>method</dt> +<dd><p>Passed to <a href="https://rdrr.io/pkg/saemix/man/logLik.html" class="external-link">saemix::logLik.SaemixObject</a></p></dd> + +</dl></div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/mean_degparms.html b/docs/dev/reference/mean_degparms.html index d348fa74..67db1868 100644 --- a/docs/dev/reference/mean_degparms.html +++ b/docs/dev/reference/mean_degparms.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,6 +41,9 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -84,26 +87,47 @@ </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">mean_degparms</span><span class="op">(</span><span class="va">object</span>, random <span class="op">=</span> <span class="cn">FALSE</span>, test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>, conf.level <span class="op">=</span> <span class="fl">0.6</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mean_degparms</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> random <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> default_log_parms <span class="op">=</span> <span class="cn">NA</span></span> +<span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>object</dt> <dd><p>An mmkin row object containing several fits of the same model to different datasets</p></dd> + + <dt>random</dt> <dd><p>Should a list with fixed and random effects be returned?</p></dd> + + <dt>test_log_parms</dt> <dd><p>If TRUE, log parameters are only considered in the mean calculations if their untransformed counterparts (most likely rate constants) pass the t-test for significant difference from zero.</p></dd> + + <dt>conf.level</dt> <dd><p>Possibility to adjust the required confidence level for parameter that are tested if requested by 'test_log_parms'.</p></dd> + + +<dt>default_log_parms</dt> +<dd><p>If set to a numeric value, this is used +as a default value for the tested log parameters that failed the +t-test.</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>If random is FALSE (default), a named vector containing mean values + + +<p>If random is FALSE (default), a named vector containing mean values of the fitted degradation model parameters. If random is TRUE, a list with fixed and random effects, in the format required by the start argument of nlme for the case of a single grouping variable ds.</p> @@ -121,7 +145,7 @@ nlme for the case of a single grouping variable ds.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/mhmkin.html b/docs/dev/reference/mhmkin.html new file mode 100644 index 00000000..e77aace3 --- /dev/null +++ b/docs/dev/reference/mhmkin.html @@ -0,0 +1,213 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models — mhmkin • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models — mhmkin"><meta property="og:description" content="The name of the methods expresses that (multiple) hierarchichal +(also known as multilevel) multicompartment kinetic models are +fitted. Our kinetic models are nonlinear, so we can use various nonlinear +mixed-effects model fitting functions."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mhmkin.R" class="external-link"><code>R/mhmkin.R</code></a></small> + <div class="hidden name"><code>mhmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The name of the methods expresses that (<strong>m</strong>ultiple) <strong>h</strong>ierarchichal +(also known as multilevel) <strong>m</strong>ulticompartment <strong>kin</strong>etic models are +fitted. Our kinetic models are nonlinear, so we can use various nonlinear +mixed-effects model fitting functions.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre><code>mhmkin(objects, backend = "saemix", algorithm = "saem", ...) + +# S3 method for list +mhmkin( + objects, + backend = "saemix", + ..., + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), + cluster = NULL +) + +# S3 method for mhmkin +[(x, i, j, ..., drop = FALSE) + +# S3 method for mhmkin +print(x, ...)</code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>objects</dt> +<dd><p>A list of <a href="mmkin.html">mmkin</a> objects containing fits of the same +degradation models to the same data, but using different error models.</p></dd> + + +<dt>backend</dt> +<dd><p>The backend to be used for fitting. Currently, only saemix is +supported</p></dd> + + +<dt>algorithm</dt> +<dd><p>The algorithm to be used for fitting (currently not used)</p></dd> + + +<dt>...</dt> +<dd><p>Further arguments that will be passed to the nonlinear mixed-effects +model fitting function.</p></dd> + + +<dt>cores</dt> +<dd><p>The number of cores to be used for multicore processing. This +is only used when the <code>cluster</code> argument is <code>NULL</code>. On Windows +machines, cores > 1 is not supported, you need to use the <code>cluster</code> +argument to use multiple logical processors. Per default, all cores detected +by <code><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">parallel::detectCores()</a></code> are used, except on Windows where the default +is 1.</p></dd> + + +<dt>cluster</dt> +<dd><p>A cluster as returned by makeCluster to be used for +parallel execution.</p></dd> + + +<dt>x</dt> +<dd><p>An mhmkin object.</p></dd> + + +<dt>i</dt> +<dd><p>Row index selecting the fits for specific models</p></dd> + + +<dt>j</dt> +<dd><p>Column index selecting the fits to specific datasets</p></dd> + + +<dt>drop</dt> +<dd><p>If FALSE, the method always returns an mhmkin object, otherwise +either a list of fit objects or a single fit object.</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>A two-dimensional <a href="https://rdrr.io/r/base/array.html" class="external-link">array</a> of fit objects and/or try-errors that can +be indexed using the degradation model names for the first index (row index) +and the error model names for the second index (column index), with class +attribute 'mhmkin'.</p> + + +<p>An object of class <code>mhmkin</code>.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><code>[.mhmkin</code> for subsetting mhmkin objects</p></div> + </div> + <div id="author"> + <h2>Author</h2> + <p>Johannes Ranke</p> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/mkinds.html b/docs/dev/reference/mkinds.html index 0d1de46d..b571e3a0 100644 --- a/docs/dev/reference/mkinds.html +++ b/docs/dev/reference/mkinds.html @@ -1,70 +1,15 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - <head> - <meta charset="utf-8"> -<meta http-equiv="X-UA-Compatible" content="IE=edge"> -<meta name="viewport" content="width=device-width, initial-scale=1.0"> - -<title>A dataset class for mkin — mkinds • mkin</title> - - -<!-- jquery --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script> -<!-- Bootstrap --> - -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" /> - -<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script> - -<!-- bootstrap-toc --> -<link rel="stylesheet" href="../bootstrap-toc.css"> -<script src="../bootstrap-toc.js"></script> - -<!-- Font Awesome icons --> -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" /> -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" /> - -<!-- clipboard.js --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script> - -<!-- headroom.js --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script> - -<!-- pkgdown --> -<link href="../pkgdown.css" rel="stylesheet"> -<script src="../pkgdown.js"></script> - - - - -<meta property="og:title" content="A dataset class for mkin — mkinds" /> -<meta property="og:description" content="At the moment this dataset class is hardly used in mkin. For example, +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>A dataset class for mkin — mkinds • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="A dataset class for mkin — mkinds"><meta property="og:description" content="At the moment this dataset class is hardly used in mkin. For example, mkinfit does not take mkinds datasets as argument, but works with dataframes such as the on contained in the data field of mkinds objects. Some datasets -provided by this package come as mkinds objects nevertheless." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +provided by this package come as mkinds objects nevertheless."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> -<![endif]--> - - - - </head> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -75,23 +20,21 @@ provided by this package come as mkinds objects nevertheless." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -101,6 +44,9 @@ provided by this package come as mkinds objects nevertheless." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -115,34 +61,27 @@ provided by this package come as mkinds objects nevertheless." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>A dataset class for mkin</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/mkinds.R'><code>R/mkinds.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mkinds.R" class="external-link"><code>R/mkinds.R</code></a></small> <div class="hidden name"><code>mkinds.Rd</code></div> </div> @@ -153,118 +92,148 @@ such as the on contained in the data field of mkinds objects. Some datasets provided by this package come as mkinds objects nevertheless.</p> </div> - <pre class="usage"><span class='co'># S3 method for mkinds</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span><span class='op'>)</span></pre> + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mkinds</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>x</dt> +<dd><p>An mkinds object.</p></dd> + + +<dt>data</dt> +<dd><p>Should the data be printed?</p></dd> + + +<dt>...</dt> +<dd><p>Not used.</p></dd> - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>x</th> - <td><p>An mkinds object.</p></td> - </tr> - <tr> - <th>data</th> - <td><p>Should the data be printed?</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Not used.</p></td> - </tr> - </table> +</dl></div> + <div id="public-fields"> + <h2>Public fields</h2> + <p></p><div class="r6-fields"><dl><dt><code>title</code></dt> +<dd><p>A full title for the dataset</p></dd> - <h2 class="hasAnchor" id="public-fields"><a class="anchor" href="#public-fields"></a>Public fields</h2> - <p><div class="r6-fields"></p><dl> -<dt><code>title</code></dt><dd><p>A full title for the dataset</p></dd> +<dt><code>sampling_times</code></dt> +<dd><p>The sampling times</p></dd> -<dt><code>sampling_times</code></dt><dd><p>The sampling times</p></dd> -<dt><code>time_unit</code></dt><dd><p>The time unit</p></dd> +<dt><code>time_unit</code></dt> +<dd><p>The time unit</p></dd> -<dt><code>observed</code></dt><dd><p>Names of the observed variables</p></dd> -<dt><code>unit</code></dt><dd><p>The unit of the observations</p></dd> +<dt><code>observed</code></dt> +<dd><p>Names of the observed variables</p></dd> -<dt><code>replicates</code></dt><dd><p>The maximum number of replicates per sampling time</p></dd> -<dt><code>data</code></dt><dd><p>A data frame with at least the columns name, time +<dt><code>unit</code></dt> +<dd><p>The unit of the observations</p></dd> + + +<dt><code>replicates</code></dt> +<dd><p>The maximum number of replicates per sampling time</p></dd> + + +<dt><code>data</code></dt> +<dd><p>A data frame with at least the columns name, time and value in order to be compatible with mkinfit</p></dd> -</dl><p></div></p> - <h2 class="hasAnchor" id="methods"><a class="anchor" href="#methods"></a>Methods</h2> +</dl><p></p></div> + </div> + <div id="methods"> + <h2>Methods</h2> -<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Public methods</h3> +<div class="section"> +<h3 id="public-methods">Public methods<a class="anchor" aria-label="anchor" href="#public-methods"></a></h3> + +<ul><li><p><a href="#method-mkinds-new"><code>mkinds$new()</code></a></p></li> +<li><p><a href="#method-mkinds-clone"><code>mkinds$clone()</code></a></p></li> +</ul></div><p></p><hr><a id="method-mkinds-new"></a><div class="section"> +<h3 id="method-new-">Method <code>new()</code><a class="anchor" aria-label="anchor" href="#method-new-"></a></h3> +<p>Create a new mkinds object</p><div class="section"> +<h4 id="usage">Usage<a class="anchor" aria-label="anchor" href="#usage"></a></h4> +<p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va"><a href="../reference/mkinds.html">mkinds</a></span><span class="op">$</span><span class="fu">new</span><span class="op">(</span>title <span class="op">=</span> <span class="st">""</span>, <span class="va">data</span>, time_unit <span class="op">=</span> <span class="cn">NA</span>, unit <span class="op">=</span> <span class="cn">NA</span><span class="op">)</span></span></code></pre></div><p></p></div> +</div> -<ul> -<li><p><a href='#method-new'><code>mkinds$new()</code></a></p></li> -<li><p><a href='#method-clone'><code>mkinds$clone()</code></a></p></li> -</ul> -<p><hr> -<a id="method-new"></a></p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Method <code>new()</code></h3> -<p>Create a new mkinds object</p><h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Usage</h4> -<p><div class="r"></p><pre><span class='va'>mkinds</span><span class='op'>$</span><span class='fu'>new</span><span class='op'>(</span>title <span class='op'>=</span> <span class='st'>""</span>, <span class='va'>data</span>, time_unit <span class='op'>=</span> <span class='cn'>NA</span>, unit <span class='op'>=</span> <span class='cn'>NA</span><span class='op'>)</span></pre><p></div></p> +<div class="section"> +<h4 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h4> +<p></p><div class="arguments"><dl><dt><code>title</code></dt> +<dd><p>The dataset title</p></dd> -<h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Arguments</h4> -<p><div class="arguments"></p><dl> -<dt><code>title</code></dt><dd><p>The dataset title</p></dd> -<dt><code>data</code></dt><dd><p>The data</p></dd> +<dt><code>data</code></dt> +<dd><p>The data</p></dd> -<dt><code>time_unit</code></dt><dd><p>The time unit</p></dd> -<dt><code>unit</code></dt><dd><p>The unit of the observations</p></dd> +<dt><code>time_unit</code></dt> +<dd><p>The time unit</p></dd> -</dl><p></div></p> -<p><hr> -<a id="method-clone"></a></p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Method <code>clone()</code></h3> -<p>The objects of this class are cloneable with this method.</p><h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Usage</h4> -<p><div class="r"></p><pre><span class='va'>mkinds</span><span class='op'>$</span><span class='fu'>clone</span><span class='op'>(</span>deep <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span></pre><p></div></p> -<h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Arguments</h4> -<p><div class="arguments"></p><dl> -<dt><code>deep</code></dt><dd><p>Whether to make a deep clone.</p></dd> +<dt><code>unit</code></dt> +<dd><p>The unit of the observations</p></dd> -</dl><p></div></p> +</dl><p></p></div> +</div> + +</div><p></p><hr><a id="method-mkinds-clone"></a><div class="section"> +<h3 id="method-clone-">Method <code>clone()</code><a class="anchor" aria-label="anchor" href="#method-clone-"></a></h3> +<p>The objects of this class are cloneable with this method.</p><div class="section"> +<h4 id="usage-1">Usage<a class="anchor" aria-label="anchor" href="#usage-1"></a></h4> +<p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va">mkinds</span><span class="op">$</span><span class="fu">clone</span><span class="op">(</span>deep <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div><p></p></div> +</div> + +<div class="section"> +<h4 id="arguments-1">Arguments<a class="anchor" aria-label="anchor" href="#arguments-1"></a></h4> +<p></p><div class="arguments"><dl><dt><code>deep</code></dt> +<dd><p>Whether to make a deep clone.</p></dd> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='va'>mds</span> <span class='op'><-</span> <span class='va'>mkinds</span><span class='op'>$</span><span class='fu'>new</span><span class='op'>(</span><span class='st'>"FOCUS A"</span>, <span class='va'>FOCUS_2006_A</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mds</span><span class='op'>)</span> -</div><div class='output co'>#> <mkinds> with $title: FOCUS A -#> Observed compounds $observed: parent -#> Sampling times $sampling_times: -#> 0, 3, 7, 14, 30, 62, 90, 118 -#> With a maximum of 1 replicates</div><div class='input'> -</div></pre> +</dl><p></p></div> +</div> + +</div> + + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">mds</span> <span class="op"><-</span> <span class="va">mkinds</span><span class="op">$</span><span class="fu">new</span><span class="op">(</span><span class="st">"FOCUS A"</span>, <span class="va">FOCUS_2006_A</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">mds</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: FOCUS A </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 3, 7, 14, 30, 62, 90, 118 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 1 replicates</span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - 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Time normalisation factors are initialised with a value of 1 for each -dataset if no data are supplied." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +dataset if no data are supplied."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" 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version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -101,6 +44,9 @@ dataset if no data are supplied." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -115,34 +61,27 @@ dataset if no data are supplied." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>A class for dataset groups for mkin</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/mkinds.R'><code>R/mkinds.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mkinds.R" class="external-link"><code>R/mkinds.R</code></a></small> <div class="hidden name"><code>mkindsg.Rd</code></div> </div> @@ -153,308 +92,336 @@ so that combined evaluations are desirable.</p> dataset if no data are supplied.</p> </div> - <pre class="usage"><span class='co'># S3 method for mkindsg</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span>, verbose <span class='op'>=</span> <span class='va'>data</span>, <span class='va'>...</span><span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>x</th> - <td><p>An mkindsg object.</p></td> - </tr> - <tr> - <th>data</th> - <td><p>Should the mkinds objects be printed with their data?</p></td> - </tr> - <tr> - <th>verbose</th> - <td><p>Should the mkinds objects be printed?</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Not used.</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="public-fields"><a class="anchor" href="#public-fields"></a>Public fields</h2> - - <p><div class="r6-fields"></p><dl> -<dt><code>title</code></dt><dd><p>A title for the dataset group</p></dd> - -<dt><code>ds</code></dt><dd><p>A list of mkinds objects</p></dd> - -<dt><code>observed_n</code></dt><dd><p>Occurrence counts of compounds in datasets</p></dd> - -<dt><code>f_time_norm</code></dt><dd><p>Time normalisation factors</p></dd> - -<dt><code>meta</code></dt><dd><p>A data frame with a row for each dataset, + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mkindsg</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, verbose <span class="op">=</span> <span class="va">data</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>x</dt> +<dd><p>An mkindsg object.</p></dd> + + +<dt>data</dt> +<dd><p>Should the mkinds objects be printed with their data?</p></dd> + + +<dt>verbose</dt> +<dd><p>Should the mkinds objects be printed?</p></dd> + + +<dt>...</dt> +<dd><p>Not used.</p></dd> + +</dl></div> + <div id="public-fields"> + <h2>Public fields</h2> + <p></p><div class="r6-fields"><dl><dt><code>title</code></dt> +<dd><p>A title for the dataset group</p></dd> + + +<dt><code>ds</code></dt> +<dd><p>A list of mkinds objects</p></dd> + + +<dt><code>observed_n</code></dt> +<dd><p>Occurrence counts of compounds in datasets</p></dd> + + +<dt><code>f_time_norm</code></dt> +<dd><p>Time normalisation factors</p></dd> + + +<dt><code>meta</code></dt> +<dd><p>A data frame with a row for each dataset, containing additional information in the form of categorical data (factors) or numerical data (e.g. temperature, moisture, or covariates like soil pH).</p></dd> -</dl><p></div></p> - <h2 class="hasAnchor" id="methods"><a class="anchor" href="#methods"></a>Methods</h2> +</dl><p></p></div> + </div> + <div id="methods"> + <h2>Methods</h2> -<h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Public methods</h3> - -<ul> -<li><p><a href='#method-new'><code>mkindsg$new()</code></a></p></li> -<li><p><a href='#method-clone'><code>mkindsg$clone()</code></a></p></li> -</ul> -<p><hr> -<a id="method-new"></a></p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Method <code>new()</code></h3> -<p>Create a new mkindsg object</p><h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Usage</h4> -<p><div class="r"></p><pre><span class='va'>mkindsg</span><span class='op'>$</span><span class='fu'>new</span><span class='op'>(</span>title <span class='op'>=</span> <span class='st'>""</span>, <span class='va'>ds</span>, f_time_norm <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span><span class='op'>(</span><span class='fl'>1</span>, <span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span><span class='op'>)</span>, <span class='va'>meta</span><span class='op'>)</span></pre><p></div></p> - -<h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Arguments</h4> -<p><div class="arguments"></p><dl> -<dt><code>title</code></dt><dd><p>The title</p></dd> - -<dt><code>ds</code></dt><dd><p>A list of mkinds objects</p></dd> - -<dt><code>f_time_norm</code></dt><dd><p>Time normalisation factors</p></dd> - -<dt><code>meta</code></dt><dd><p>The meta data</p></dd> - -</dl><p></div></p> -<p><hr> -<a id="method-clone"></a></p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Method <code>clone()</code></h3> -<p>The objects of this class are cloneable with this method.</p><h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Usage</h4> -<p><div class="r"></p><pre><span class='va'>mkindsg</span><span class='op'>$</span><span class='fu'>clone</span><span class='op'>(</span>deep <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span></pre><p></div></p> - -<h4 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Arguments</h4> -<p><div class="arguments"></p><dl> -<dt><code>deep</code></dt><dd><p>Whether to make a deep clone.</p></dd> - -</dl><p></div></p> - - - - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='va'>mdsg</span> <span class='op'><-</span> <span class='va'>mkindsg</span><span class='op'>$</span><span class='fu'>new</span><span class='op'>(</span><span class='st'>"Experimental X"</span>, <span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span><span class='op'>)</span> -</div><div class='output co'>#> <mkindsg> holding 5 mkinds objects -#> Title $title: Experimental X -#> Occurrence of observed compounds $observed_n: -#> parent A1 -#> 5 5 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <mkindsg> holding 5 mkinds objects -#> Title $title: Experimental X -#> Occurrence of observed compounds $observed_n: -#> parent A1 -#> 5 5 -#> -#> Datasets $ds: -#> <mkinds> with $title: Soil 6 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> -#> <mkinds> with $title: Soil 7 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 3, 7, 14, 30, 60, 90, 120, 180 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> -#> <mkinds> with $title: Soil 8 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 1, 3, 8, 14, 27, 48, 70 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> -#> <mkinds> with $title: Soil 9 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> -#> <mkinds> with $title: Soil 10 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 8, 14, 21, 41, 63, 91, 120 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>mdsg</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <mkindsg> holding 5 mkinds objects -#> Title $title: Experimental X -#> Occurrence of observed compounds $observed_n: -#> parent A1 -#> 5 5 -#> -#> Datasets $ds: -#> <mkinds> with $title: Soil 6 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> time parent A1 -#> 1 0 97.2 NA -#> 2 0 96.4 NA -#> 3 3 71.1 4.3 -#> 4 3 69.2 4.6 -#> 5 6 58.1 7.0 -#> 6 6 56.6 7.2 -#> 7 10 44.4 8.2 -#> 8 10 43.4 8.0 -#> 9 20 33.3 11.0 -#> 10 20 29.2 13.7 -#> 11 34 17.6 11.5 -#> 12 34 18.0 12.7 -#> 13 55 10.5 14.9 -#> 14 55 9.3 14.5 -#> 15 90 4.5 12.1 -#> 16 90 4.7 12.3 -#> 17 112 3.0 9.9 -#> 18 112 3.4 10.2 -#> 19 132 2.3 8.8 -#> 20 132 2.7 7.8 -#> -#> <mkinds> with $title: Soil 7 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 3, 7, 14, 30, 60, 90, 120, 180 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> time parent A1 -#> 1 0 93.6 NA -#> 2 0 92.3 NA -#> 3 3 87.0 3.9 -#> 4 3 82.2 3.1 -#> 5 7 74.0 6.9 -#> 6 7 73.9 6.6 -#> 7 14 64.2 10.4 -#> 8 14 69.5 8.3 -#> 9 30 54.0 14.4 -#> 10 30 54.6 13.7 -#> 11 60 41.1 22.1 -#> 12 60 38.4 22.3 -#> 13 90 32.5 27.5 -#> 14 90 35.5 25.4 -#> 15 120 28.1 28.0 -#> 16 120 29.0 26.6 -#> 17 180 26.5 25.8 -#> 18 180 27.6 25.3 -#> -#> <mkinds> with $title: Soil 8 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 1, 3, 8, 14, 27, 48, 70 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> time parent A1 -#> 1 0 91.9 NA -#> 2 0 90.8 NA -#> 3 1 64.9 9.6 -#> 4 1 66.2 7.7 -#> 5 3 43.5 15.0 -#> 6 3 44.1 15.1 -#> 7 8 18.3 21.2 -#> 8 8 18.1 21.1 -#> 9 14 10.2 19.7 -#> 10 14 10.8 18.9 -#> 11 27 4.9 17.5 -#> 12 27 3.3 15.9 -#> 13 48 1.6 9.5 -#> 14 48 1.5 9.8 -#> 15 70 1.1 6.2 -#> 16 70 0.9 6.1 -#> -#> <mkinds> with $title: Soil 9 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> time parent A1 -#> 1 0 99.8 NA -#> 2 0 98.3 NA -#> 3 1 77.1 4.2 -#> 4 1 77.2 3.9 -#> 5 3 59.0 7.4 -#> 6 3 58.1 7.9 -#> 7 8 27.4 14.5 -#> 8 8 29.2 13.7 -#> 9 14 19.1 14.2 -#> 10 14 29.6 12.2 -#> 11 27 10.1 13.7 -#> 12 27 18.2 13.2 -#> 13 48 4.5 13.6 -#> 14 48 9.1 15.4 -#> 15 70 2.3 10.4 -#> 16 70 2.9 11.6 -#> 17 91 2.0 10.0 -#> 18 91 1.8 9.5 -#> 19 120 2.0 9.1 -#> 20 120 2.2 9.0 -#> -#> <mkinds> with $title: Soil 10 -#> Observed compounds $observed: parent, A1 -#> Sampling times $sampling_times: -#> 0, 8, 14, 21, 41, 63, 91, 120 -#> With a maximum of 2 replicates -#> Time unit: days -#> Observation unit: \%AR -#> time parent A1 -#> 1 0 96.1 NA -#> 2 0 94.3 NA -#> 3 8 73.9 3.3 -#> 4 8 73.9 3.4 -#> 5 14 69.4 3.9 -#> 6 14 73.1 2.9 -#> 7 21 65.6 6.4 -#> 8 21 65.3 7.2 -#> 9 41 55.9 9.1 -#> 10 41 54.4 8.5 -#> 11 63 47.0 11.7 -#> 12 63 49.3 12.0 -#> 13 91 44.7 13.3 -#> 14 91 46.7 13.2 -#> 15 120 42.1 14.3 -#> 16 120 41.3 12.1</div><div class='input'> -</div></pre> +<div class="section"> +<h3 id="public-methods">Public methods<a class="anchor" aria-label="anchor" href="#public-methods"></a></h3> + +<ul><li><p><a href="#method-mkindsg-new"><code>mkindsg$new()</code></a></p></li> +<li><p><a href="#method-mkindsg-clone"><code>mkindsg$clone()</code></a></p></li> +</ul></div><p></p><hr><a id="method-mkindsg-new"></a><div class="section"> +<h3 id="method-new-">Method <code>new()</code><a class="anchor" aria-label="anchor" href="#method-new-"></a></h3> +<p>Create a new mkindsg object</p><div class="section"> +<h4 id="usage">Usage<a class="anchor" aria-label="anchor" href="#usage"></a></h4> +<p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va"><a href="../reference/mkindsg.html">mkindsg</a></span><span class="op">$</span><span class="fu">new</span><span class="op">(</span>title <span class="op">=</span> <span class="st">""</span>, <span class="va">ds</span>, f_time_norm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span><span class="op">)</span>, <span class="va">meta</span><span class="op">)</span></span></code></pre></div><p></p></div> +</div> + +<div class="section"> +<h4 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h4> +<p></p><div class="arguments"><dl><dt><code>title</code></dt> +<dd><p>The title</p></dd> + + +<dt><code>ds</code></dt> +<dd><p>A list of mkinds objects</p></dd> + + +<dt><code>f_time_norm</code></dt> +<dd><p>Time normalisation factors</p></dd> + + +<dt><code>meta</code></dt> +<dd><p>The meta data</p></dd> + + +</dl><p></p></div> +</div> + +</div><p></p><hr><a id="method-mkindsg-clone"></a><div class="section"> +<h3 id="method-clone-">Method <code>clone()</code><a class="anchor" aria-label="anchor" href="#method-clone-"></a></h3> +<p>The objects of this class are cloneable with this method.</p><div class="section"> +<h4 id="usage-1">Usage<a class="anchor" aria-label="anchor" href="#usage-1"></a></h4> +<p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va">mkindsg</span><span class="op">$</span><span class="fu">clone</span><span class="op">(</span>deep <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div><p></p></div> +</div> + +<div class="section"> +<h4 id="arguments-1">Arguments<a class="anchor" aria-label="anchor" href="#arguments-1"></a></h4> +<p></p><div class="arguments"><dl><dt><code>deep</code></dt> +<dd><p>Whether to make a deep clone.</p></dd> + + +</dl><p></p></div> +</div> + +</div> + + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">mdsg</span> <span class="op"><-</span> <span class="va">mkindsg</span><span class="op">$</span><span class="fu">new</span><span class="op">(</span><span class="st">"Experimental X"</span>, <span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">mdsg</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 5 mkinds objects</span> +<span class="r-out co"><span class="r-pr">#></span> Title $title: Experimental X </span> +<span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> +<span class="r-out co"><span class="r-pr">#></span> parent A1 </span> +<span class="r-out co"><span class="r-pr">#></span> 5 5 </span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">mdsg</span>, verbose <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 5 mkinds objects</span> +<span class="r-out co"><span class="r-pr">#></span> Title $title: Experimental X </span> +<span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> +<span class="r-out co"><span class="r-pr">#></span> parent A1 </span> +<span class="r-out co"><span class="r-pr">#></span> 5 5 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Datasets $ds:</span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 6 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 7 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 3, 7, 14, 30, 60, 90, 120, 180 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 8 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 1, 3, 8, 14, 27, 48, 70 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 9 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 10 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 8, 14, 21, 41, 63, 91, 120 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">mdsg</span>, verbose <span class="op">=</span> <span class="cn">TRUE</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> <mkindsg> holding 5 mkinds objects</span> +<span class="r-out co"><span class="r-pr">#></span> Title $title: Experimental X </span> +<span class="r-out co"><span class="r-pr">#></span> Occurrence of observed compounds $observed_n:</span> +<span class="r-out co"><span class="r-pr">#></span> parent A1 </span> +<span class="r-out co"><span class="r-pr">#></span> 5 5 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Datasets $ds:</span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 6 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> time parent A1</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 97.2 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0 96.4 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 3 3 71.1 4.3</span> +<span class="r-out co"><span class="r-pr">#></span> 4 3 69.2 4.6</span> +<span class="r-out co"><span class="r-pr">#></span> 5 6 58.1 7.0</span> +<span class="r-out co"><span class="r-pr">#></span> 6 6 56.6 7.2</span> +<span class="r-out co"><span class="r-pr">#></span> 7 10 44.4 8.2</span> +<span class="r-out co"><span class="r-pr">#></span> 8 10 43.4 8.0</span> +<span class="r-out co"><span class="r-pr">#></span> 9 20 33.3 11.0</span> +<span class="r-out co"><span class="r-pr">#></span> 10 20 29.2 13.7</span> +<span class="r-out co"><span class="r-pr">#></span> 11 34 17.6 11.5</span> +<span class="r-out co"><span class="r-pr">#></span> 12 34 18.0 12.7</span> +<span class="r-out co"><span class="r-pr">#></span> 13 55 10.5 14.9</span> +<span class="r-out co"><span class="r-pr">#></span> 14 55 9.3 14.5</span> +<span class="r-out co"><span class="r-pr">#></span> 15 90 4.5 12.1</span> +<span class="r-out co"><span class="r-pr">#></span> 16 90 4.7 12.3</span> +<span class="r-out co"><span class="r-pr">#></span> 17 112 3.0 9.9</span> +<span class="r-out co"><span class="r-pr">#></span> 18 112 3.4 10.2</span> +<span class="r-out co"><span class="r-pr">#></span> 19 132 2.3 8.8</span> +<span class="r-out co"><span class="r-pr">#></span> 20 132 2.7 7.8</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 7 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 3, 7, 14, 30, 60, 90, 120, 180 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> time parent A1</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 93.6 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0 92.3 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 3 3 87.0 3.9</span> +<span class="r-out co"><span class="r-pr">#></span> 4 3 82.2 3.1</span> +<span class="r-out co"><span class="r-pr">#></span> 5 7 74.0 6.9</span> +<span class="r-out co"><span class="r-pr">#></span> 6 7 73.9 6.6</span> +<span class="r-out co"><span class="r-pr">#></span> 7 14 64.2 10.4</span> +<span class="r-out co"><span class="r-pr">#></span> 8 14 69.5 8.3</span> +<span class="r-out co"><span class="r-pr">#></span> 9 30 54.0 14.4</span> +<span class="r-out co"><span class="r-pr">#></span> 10 30 54.6 13.7</span> +<span class="r-out co"><span class="r-pr">#></span> 11 60 41.1 22.1</span> +<span class="r-out co"><span class="r-pr">#></span> 12 60 38.4 22.3</span> +<span class="r-out co"><span class="r-pr">#></span> 13 90 32.5 27.5</span> +<span class="r-out co"><span class="r-pr">#></span> 14 90 35.5 25.4</span> +<span class="r-out co"><span class="r-pr">#></span> 15 120 28.1 28.0</span> +<span class="r-out co"><span class="r-pr">#></span> 16 120 29.0 26.6</span> +<span class="r-out co"><span class="r-pr">#></span> 17 180 26.5 25.8</span> +<span class="r-out co"><span class="r-pr">#></span> 18 180 27.6 25.3</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 8 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 1, 3, 8, 14, 27, 48, 70 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> time parent A1</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 91.9 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0 90.8 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 3 1 64.9 9.6</span> +<span class="r-out co"><span class="r-pr">#></span> 4 1 66.2 7.7</span> +<span class="r-out co"><span class="r-pr">#></span> 5 3 43.5 15.0</span> +<span class="r-out co"><span class="r-pr">#></span> 6 3 44.1 15.1</span> +<span class="r-out co"><span class="r-pr">#></span> 7 8 18.3 21.2</span> +<span class="r-out co"><span class="r-pr">#></span> 8 8 18.1 21.1</span> +<span class="r-out co"><span class="r-pr">#></span> 9 14 10.2 19.7</span> +<span class="r-out co"><span class="r-pr">#></span> 10 14 10.8 18.9</span> +<span class="r-out co"><span class="r-pr">#></span> 11 27 4.9 17.5</span> +<span class="r-out co"><span class="r-pr">#></span> 12 27 3.3 15.9</span> +<span class="r-out co"><span class="r-pr">#></span> 13 48 1.6 9.5</span> +<span class="r-out co"><span class="r-pr">#></span> 14 48 1.5 9.8</span> +<span class="r-out co"><span class="r-pr">#></span> 15 70 1.1 6.2</span> +<span class="r-out co"><span class="r-pr">#></span> 16 70 0.9 6.1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 9 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> time parent A1</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 99.8 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0 98.3 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 3 1 77.1 4.2</span> +<span class="r-out co"><span class="r-pr">#></span> 4 1 77.2 3.9</span> +<span class="r-out co"><span class="r-pr">#></span> 5 3 59.0 7.4</span> +<span class="r-out co"><span class="r-pr">#></span> 6 3 58.1 7.9</span> +<span class="r-out co"><span class="r-pr">#></span> 7 8 27.4 14.5</span> +<span class="r-out co"><span class="r-pr">#></span> 8 8 29.2 13.7</span> +<span class="r-out co"><span class="r-pr">#></span> 9 14 19.1 14.2</span> +<span class="r-out co"><span class="r-pr">#></span> 10 14 29.6 12.2</span> +<span class="r-out co"><span class="r-pr">#></span> 11 27 10.1 13.7</span> +<span class="r-out co"><span class="r-pr">#></span> 12 27 18.2 13.2</span> +<span class="r-out co"><span class="r-pr">#></span> 13 48 4.5 13.6</span> +<span class="r-out co"><span class="r-pr">#></span> 14 48 9.1 15.4</span> +<span class="r-out co"><span class="r-pr">#></span> 15 70 2.3 10.4</span> +<span class="r-out co"><span class="r-pr">#></span> 16 70 2.9 11.6</span> +<span class="r-out co"><span class="r-pr">#></span> 17 91 2.0 10.0</span> +<span class="r-out co"><span class="r-pr">#></span> 18 91 1.8 9.5</span> +<span class="r-out co"><span class="r-pr">#></span> 19 120 2.0 9.1</span> +<span class="r-out co"><span class="r-pr">#></span> 20 120 2.2 9.0</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> <mkinds> with $title: Soil 10 </span> +<span class="r-out co"><span class="r-pr">#></span> Observed compounds $observed: parent, A1 </span> +<span class="r-out co"><span class="r-pr">#></span> Sampling times $sampling_times:</span> +<span class="r-out co"><span class="r-pr">#></span> 0, 8, 14, 21, 41, 63, 91, 120 </span> +<span class="r-out co"><span class="r-pr">#></span> With a maximum of 2 replicates</span> +<span class="r-out co"><span class="r-pr">#></span> Time unit: days </span> +<span class="r-out co"><span class="r-pr">#></span> Observation unit: \%AR </span> +<span class="r-out co"><span class="r-pr">#></span> time parent A1</span> +<span class="r-out co"><span class="r-pr">#></span> 1 0 96.1 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 2 0 94.3 NA</span> +<span class="r-out co"><span class="r-pr">#></span> 3 8 73.9 3.3</span> +<span class="r-out co"><span class="r-pr">#></span> 4 8 73.9 3.4</span> +<span class="r-out co"><span class="r-pr">#></span> 5 14 69.4 3.9</span> +<span class="r-out co"><span class="r-pr">#></span> 6 14 73.1 2.9</span> +<span class="r-out co"><span class="r-pr">#></span> 7 21 65.6 6.4</span> +<span class="r-out co"><span class="r-pr">#></span> 8 21 65.3 7.2</span> +<span class="r-out co"><span class="r-pr">#></span> 9 41 55.9 9.1</span> +<span class="r-out co"><span class="r-pr">#></span> 10 41 54.4 8.5</span> +<span class="r-out co"><span class="r-pr">#></span> 11 63 47.0 11.7</span> +<span class="r-out co"><span class="r-pr">#></span> 12 63 49.3 12.0</span> +<span class="r-out co"><span class="r-pr">#></span> 13 91 44.7 13.3</span> +<span class="r-out co"><span class="r-pr">#></span> 14 91 46.7 13.2</span> +<span class="r-out co"><span class="r-pr">#></span> 15 120 42.1 14.3</span> +<span class="r-out co"><span class="r-pr">#></span> 16 120 41.3 12.1</span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" 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property="og:description" content="This function maximises the likelihood of the observed data using the Port algorithm stats::nlminb(), and the specified initial or fixed parameters and starting values. In each step of the optimisation, the kinetic model is solved using the function mkinpredict(), except @@ -48,28 +7,14 @@ if an analytical solution is implemented, in which case the model is solved using the degradation function in the mkinmod object. The parameters of the selected error model are fitted simultaneously with the degradation model parameters, as both of them are arguments of the -likelihood function." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +likelihood function."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> -<![endif]--> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - - - </head> - - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -80,23 +25,21 @@ likelihood function." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -106,6 +49,9 @@ likelihood function." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -120,91 +66,84 @@ likelihood function." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Fit a kinetic model to data with one or more state variables</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/mkinfit.R'><code>R/mkinfit.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mkinfit.R" class="external-link"><code>R/mkinfit.R</code></a></small> <div class="hidden name"><code>mkinfit.Rd</code></div> </div> <div class="ref-description"> <p>This function maximises the likelihood of the observed data using the Port -algorithm <code><a href='https://rdrr.io/r/stats/nlminb.html'>stats::nlminb()</a></code>, and the specified initial or fixed +algorithm <code><a href="https://rdrr.io/r/stats/nlminb.html" class="external-link">stats::nlminb()</a></code>, and the specified initial or fixed parameters and starting values. In each step of the optimisation, the -kinetic model is solved using the function <code><a href='mkinpredict.html'>mkinpredict()</a></code>, except +kinetic model is solved using the function <code><a href="mkinpredict.html">mkinpredict()</a></code>, except if an analytical solution is implemented, in which case the model is solved -using the degradation function in the <a href='mkinmod.html'>mkinmod</a> object. The +using the degradation function in the <a href="mkinmod.html">mkinmod</a> object. The parameters of the selected error model are fitted simultaneously with the degradation model parameters, as both of them are arguments of the likelihood function.</p> </div> - <pre class="usage"><span class='fu'>mkinfit</span><span class='op'>(</span> - <span class='va'>mkinmod</span>, - <span class='va'>observed</span>, - parms.ini <span class='op'>=</span> <span class='st'>"auto"</span>, - state.ini <span class='op'>=</span> <span class='st'>"auto"</span>, - err.ini <span class='op'>=</span> <span class='st'>"auto"</span>, - fixed_parms <span class='op'>=</span> <span class='cn'>NULL</span>, - fixed_initials <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>mkinmod</span><span class='op'>$</span><span class='va'>diffs</span><span class='op'>)</span><span class='op'>[</span><span class='op'>-</span><span class='fl'>1</span><span class='op'>]</span>, - from_max_mean <span class='op'>=</span> <span class='cn'>FALSE</span>, - solution_type <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"auto"</span>, <span class='st'>"analytical"</span>, <span class='st'>"eigen"</span>, <span class='st'>"deSolve"</span><span class='op'>)</span>, - method.ode <span class='op'>=</span> <span class='st'>"lsoda"</span>, - use_compiled <span class='op'>=</span> <span class='st'>"auto"</span>, - control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>eval.max <span class='op'>=</span> <span class='fl'>300</span>, iter.max <span class='op'>=</span> <span class='fl'>200</span><span class='op'>)</span>, - transform_rates <span class='op'>=</span> <span class='cn'>TRUE</span>, - transform_fractions <span class='op'>=</span> <span class='cn'>TRUE</span>, - quiet <span class='op'>=</span> <span class='cn'>FALSE</span>, - atol <span class='op'>=</span> <span class='fl'>1e-08</span>, - rtol <span class='op'>=</span> <span class='fl'>1e-10</span>, - error_model <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"const"</span>, <span class='st'>"obs"</span>, <span class='st'>"tc"</span><span class='op'>)</span>, - error_model_algorithm <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"auto"</span>, <span class='st'>"d_3"</span>, <span class='st'>"direct"</span>, <span class='st'>"twostep"</span>, <span class='st'>"threestep"</span>, - <span class='st'>"fourstep"</span>, <span class='st'>"IRLS"</span>, <span class='st'>"OLS"</span><span class='op'>)</span>, - reweight.tol <span class='op'>=</span> <span class='fl'>1e-08</span>, - reweight.max.iter <span class='op'>=</span> <span class='fl'>10</span>, - trace_parms <span class='op'>=</span> <span class='cn'>FALSE</span>, - test_residuals <span class='op'>=</span> <span class='cn'>FALSE</span>, - <span class='va'>...</span> -<span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>mkinmod</th> - <td><p>A list of class <a href='mkinmod.html'>mkinmod</a>, containing the kinetic + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mkinfit</span><span class="op">(</span></span> +<span> <span class="va">mkinmod</span>,</span> +<span> <span class="va">observed</span>,</span> +<span> parms.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> state.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> err.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> fixed_parms <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> fixed_initials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">diffs</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>,</span> +<span> from_max_mean <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> solution_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"analytical"</span>, <span class="st">"eigen"</span>, <span class="st">"deSolve"</span><span class="op">)</span>,</span> +<span> method.ode <span class="op">=</span> <span class="st">"lsoda"</span>,</span> +<span> use_compiled <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>eval.max <span class="op">=</span> <span class="fl">300</span>, iter.max <span class="op">=</span> <span class="fl">200</span><span class="op">)</span>,</span> +<span> transform_rates <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> transform_fractions <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> atol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> rtol <span class="op">=</span> <span class="fl">1e-10</span>,</span> +<span> error_model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"obs"</span>, <span class="st">"tc"</span><span class="op">)</span>,</span> +<span> error_model_algorithm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"d_3"</span>, <span class="st">"direct"</span>, <span class="st">"twostep"</span>, <span class="st">"threestep"</span>, <span class="st">"fourstep"</span>,</span> +<span> <span class="st">"IRLS"</span>, <span class="st">"OLS"</span><span class="op">)</span>,</span> +<span> reweight.tol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> reweight.max.iter <span class="op">=</span> <span class="fl">10</span>,</span> +<span> trace_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> test_residuals <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>mkinmod</dt> +<dd><p>A list of class <a href="mkinmod.html">mkinmod</a>, containing the kinetic model to be fitted to the data, or one of the shorthand names ("SFO", "FOMC", "DFOP", "HS", "SFORB", "IORE"). If a shorthand name is given, a parent only degradation model is generated for the variable with the -highest value in <code>observed</code>.</p></td> - </tr> - <tr> - <th>observed</th> - <td><p>A dataframe with the observed data. The first column called +highest value in <code>observed</code>.</p></dd> + + +<dt>observed</dt> +<dd><p>A dataframe with the observed data. The first column called "name" must contain the name of the observed variable for each data point. The second column must contain the times of observation, named "time". The third column must be named "value" and contain the observed values. @@ -212,11 +151,11 @@ Zero values in the "value" column will be removed, with a warning, in order to avoid problems with fitting the two-component error model. This is not expected to be a problem, because in general, values of zero are not observed in degradation data, because there is a lower limit of -detection.</p></td> - </tr> - <tr> - <th>parms.ini</th> - <td><p>A named vector of initial values for the parameters, +detection.</p></dd> + + +<dt>parms.ini</dt> +<dd><p>A named vector of initial values for the parameters, including parameters to be optimised and potentially also fixed parameters as indicated by <code>fixed_parms</code>. If set to "auto", initial values for rate constants are set to default values. Using parameter names that are @@ -225,113 +164,113 @@ not in the model gives an error.</p> needs. You can use the parameter lists "bparms.ode" from a previously fitted model, which contains the differential equation parameters from this model. This works nicely if the models are nested. An example is -given below.</p></td> - </tr> - <tr> - <th>state.ini</th> - <td><p>A named vector of initial values for the state variables of +given below.</p></dd> + + +<dt>state.ini</dt> +<dd><p>A named vector of initial values for the state variables of the model. In case the observed variables are represented by more than one model variable, the names will differ from the names of the observed -variables (see <code>map</code> component of <a href='mkinmod.html'>mkinmod</a>). The default +variables (see <code>map</code> component of <a href="mkinmod.html">mkinmod</a>). The default is to set the initial value of the first model variable to the mean of the time zero values for the variable with the maximum observed value, and all others to 0. If this variable has no time zero observations, its initial -value is set to 100.</p></td> - </tr> - <tr> - <th>err.ini</th> - <td><p>A named vector of initial values for the error model +value is set to 100.</p></dd> + + +<dt>err.ini</dt> +<dd><p>A named vector of initial values for the error model parameters to be optimised. If set to "auto", initial values are set to default values. Otherwise, inital values for all error model parameters -must be given.</p></td> - </tr> - <tr> - <th>fixed_parms</th> - <td><p>The names of parameters that should not be optimised but +must be given.</p></dd> + + +<dt>fixed_parms</dt> +<dd><p>The names of parameters that should not be optimised but rather kept at the values specified in <code>parms.ini</code>. Alternatively, a named numeric vector of parameters to be fixed, regardless of the values -in parms.ini.</p></td> - </tr> - <tr> - <th>fixed_initials</th> - <td><p>The names of model variables for which the initial +in parms.ini.</p></dd> + + +<dt>fixed_initials</dt> +<dd><p>The names of model variables for which the initial state at time 0 should be excluded from the optimisation. Defaults to all -state variables except for the first one.</p></td> - </tr> - <tr> - <th>from_max_mean</th> - <td><p>If this is set to TRUE, and the model has only one +state variables except for the first one.</p></dd> + + +<dt>from_max_mean</dt> +<dd><p>If this is set to TRUE, and the model has only one observed variable, then data before the time of the maximum observed value (after averaging for each sampling time) are discarded, and this time is subtracted from all remaining time values, so the time of the maximum -observed mean value is the new time zero.</p></td> - </tr> - <tr> - <th>solution_type</th> - <td><p>If set to "eigen", the solution of the system of +observed mean value is the new time zero.</p></dd> + + +<dt>solution_type</dt> +<dd><p>If set to "eigen", the solution of the system of differential equations is based on the spectral decomposition of the coefficient matrix in cases that this is possible. If set to "deSolve", a -numerical <a href='https://rdrr.io/pkg/deSolve/man/ode.html'>ode solver from package deSolve</a> is used. If +numerical <a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">ode solver from package deSolve</a> is used. If set to "analytical", an analytical solution of the model is used. This is only implemented for relatively simple degradation models. The default is "auto", which uses "analytical" if possible, otherwise "deSolve" if a compiler is present, and "eigen" if no compiler is present and the model -can be expressed using eigenvalues and eigenvectors.</p></td> - </tr> - <tr> - <th>method.ode</th> - <td><p>The solution method passed via <code><a href='mkinpredict.html'>mkinpredict()</a></code> -to <code><a href='https://rdrr.io/pkg/deSolve/man/ode.html'>deSolve::ode()</a></code> in case the solution type is "deSolve". The default -"lsoda" is performant, but sometimes fails to converge.</p></td> - </tr> - <tr> - <th>use_compiled</th> - <td><p>If set to <code>FALSE</code>, no compiled version of the -<a href='mkinmod.html'>mkinmod</a> model is used in the calls to <code><a href='mkinpredict.html'>mkinpredict()</a></code> even if a compiled -version is present.</p></td> - </tr> - <tr> - <th>control</th> - <td><p>A list of control arguments passed to <code><a href='https://rdrr.io/r/stats/nlminb.html'>stats::nlminb()</a></code>.</p></td> - </tr> - <tr> - <th>transform_rates</th> - <td><p>Boolean specifying if kinetic rate constants should +can be expressed using eigenvalues and eigenvectors.</p></dd> + + +<dt>method.ode</dt> +<dd><p>The solution method passed via <code><a href="mkinpredict.html">mkinpredict()</a></code> +to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code> in case the solution type is "deSolve". The default +"lsoda" is performant, but sometimes fails to converge.</p></dd> + + +<dt>use_compiled</dt> +<dd><p>If set to <code>FALSE</code>, no compiled version of the +<a href="mkinmod.html">mkinmod</a> model is used in the calls to <code><a href="mkinpredict.html">mkinpredict()</a></code> even if a compiled +version is present.</p></dd> + + +<dt>control</dt> +<dd><p>A list of control arguments passed to <code><a href="https://rdrr.io/r/stats/nlminb.html" class="external-link">stats::nlminb()</a></code>.</p></dd> + + +<dt>transform_rates</dt> +<dd><p>Boolean specifying if kinetic rate constants should be transformed in the model specification used in the fitting for better compliance with the assumption of normal distribution of the estimator. If TRUE, also alpha and beta parameters of the FOMC model are log-transformed, as well as k1 and k2 rate constants for the DFOP and HS models and the break point tb of the HS model. If FALSE, zero is used as -a lower bound for the rates in the optimisation.</p></td> - </tr> - <tr> - <th>transform_fractions</th> - <td><p>Boolean specifying if formation fractions +a lower bound for the rates in the optimisation.</p></dd> + + +<dt>transform_fractions</dt> +<dd><p>Boolean specifying if formation fractions should be transformed in the model specification used in the fitting for better compliance with the assumption of normal distribution of the estimator. The default (TRUE) is to do transformations. If TRUE, the g parameter of the DFOP model is also transformed. Transformations -are described in <a href='transform_odeparms.html'>transform_odeparms</a>.</p></td> - </tr> - <tr> - <th>quiet</th> - <td><p>Suppress printing out the current value of the negative -log-likelihood after each improvement?</p></td> - </tr> - <tr> - <th>atol</th> - <td><p>Absolute error tolerance, passed to <code><a href='https://rdrr.io/pkg/deSolve/man/ode.html'>deSolve::ode()</a></code>. Default -is 1e-8, which is lower than the default in the <code><a href='https://rdrr.io/pkg/deSolve/man/lsoda.html'>deSolve::lsoda()</a></code> -function which is used per default.</p></td> - </tr> - <tr> - <th>rtol</th> - <td><p>Absolute error tolerance, passed to <code><a href='https://rdrr.io/pkg/deSolve/man/ode.html'>deSolve::ode()</a></code>. Default -is 1e-10, much lower than in <code><a href='https://rdrr.io/pkg/deSolve/man/lsoda.html'>deSolve::lsoda()</a></code>.</p></td> - </tr> - <tr> - <th>error_model</th> - <td><p>If the error model is "const", a constant standard +are described in <a href="transform_odeparms.html">transform_odeparms</a>.</p></dd> + + +<dt>quiet</dt> +<dd><p>Suppress printing out the current value of the negative +log-likelihood after each improvement?</p></dd> + + +<dt>atol</dt> +<dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default +is 1e-8, which is lower than the default in the <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code> +function which is used per default.</p></dd> + + +<dt>rtol</dt> +<dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default +is 1e-10, much lower than in <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>.</p></dd> + + +<dt>error_model</dt> +<dd><p>If the error model is "const", a constant standard deviation is assumed.</p> <p>If the error model is "obs", each observed variable is assumed to have its own variance.</p> @@ -340,11 +279,11 @@ error model similar to the one described by Rocke and Lorenzato (1995) is used for setting up the likelihood function. Note that this model deviates from the model by Rocke and Lorenzato, as their model implies that the errors follow a lognormal distribution for large values, not a -normal distribution as assumed by this method.</p></td> - </tr> - <tr> - <th>error_model_algorithm</th> - <td><p>If "auto", the selected algorithm depends on +normal distribution as assumed by this method.</p></dd> + + +<dt>error_model_algorithm</dt> +<dd><p>If "auto", the selected algorithm depends on the error model. If the error model is "const", unweighted nonlinear least squares fitting ("OLS") is selected. If the error model is "obs", or "tc", the "d_3" algorithm is selected.</p> @@ -367,372 +306,392 @@ degradation and error model parameters.</p> unweighted least squares, and then iterates optimization of the error model parameters and subsequent optimization of the degradation model using those error model parameters, until the error model parameters -converge.</p></td> - </tr> - <tr> - <th>reweight.tol</th> - <td><p>Tolerance for the convergence criterion calculated from -the error model parameters in IRLS fits.</p></td> - </tr> - <tr> - <th>reweight.max.iter</th> - <td><p>Maximum number of iterations in IRLS fits.</p></td> - </tr> - <tr> - <th>trace_parms</th> - <td><p>Should a trace of the parameter values be listed?</p></td> - </tr> - <tr> - <th>test_residuals</th> - <td><p>Should the residuals be tested for normal distribution?</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Further arguments that will be passed on to -<code><a href='https://rdrr.io/pkg/deSolve/man/ode.html'>deSolve::ode()</a></code>.</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>A list with "mkinfit" in the class attribute.</p> - <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> +converge.</p></dd> + + +<dt>reweight.tol</dt> +<dd><p>Tolerance for the convergence criterion calculated from +the error model parameters in IRLS fits.</p></dd> + +<dt>reweight.max.iter</dt> +<dd><p>Maximum number of iterations in IRLS fits.</p></dd> + + +<dt>trace_parms</dt> +<dd><p>Should a trace of the parameter values be listed?</p></dd> + + +<dt>test_residuals</dt> +<dd><p>Should the residuals be tested for normal distribution?</p></dd> + + +<dt>...</dt> +<dd><p>Further arguments that will be passed on to +<code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>.</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>A list with "mkinfit" in the class attribute.</p> + </div> + <div id="details"> + <h2>Details</h2> <p>Per default, parameters in the kinetic models are internally transformed in order to better satisfy the assumption of a normal distribution of their estimators.</p> - <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2> - + </div> + <div id="note"> + <h2>Note</h2> <p>When using the "IORE" submodel for metabolites, fitting with "transform_rates = TRUE" (the default) often leads to failures of the numerical ODE solver. In this situation it may help to switch off the internal rate transformation.</p> - <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2> - + </div> + <div id="references"> + <h2>References</h2> <p>Rocke DM and Lorenzato S (1995) A two-component model for measurement error in analytical chemistry. <em>Technometrics</em> 37(2), 176-184.</p> <p>Ranke J and Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data. <em>Environments</em> 6(12) 124 -doi: <a href='https://doi.org/10.3390/environments6120124'>10.3390/environments6120124</a> +<a href="https://doi.org/10.3390/environments6120124" class="external-link">doi:10.3390/environments6120124</a> .</p> - <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2> - - <div class='dont-index'><p><a href='summary.mkinfit.html'>summary.mkinfit</a>, <a href='plot.mkinfit.html'>plot.mkinfit</a>, <a href='parms.html'>parms</a> and <a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a>.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="summary.mkinfit.html">summary.mkinfit</a>, <a href="plot.mkinfit.html">plot.mkinfit</a>, <a href="parms.html">parms</a> and <a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a>.</p> <p>Comparisons of models fitted to the same data can be made using -<code><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></code> by virtue of the method <code><a href='logLik.mkinfit.html'>logLik.mkinfit</a></code>.</p> +<code><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></code> by virtue of the method <code><a href="logLik.mkinfit.html">logLik.mkinfit</a></code>.</p> <p>Fitting of several models to several datasets in a single call to -<code><a href='mmkin.html'>mmkin</a></code>.</p></div> - <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> - +<code><a href="mmkin.html">mmkin</a></code>.</p></div> + </div> + <div id="author"> + <h2>Author</h2> <p>Johannes Ranke</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='co'># Use shorthand notation for parent only degradation</span> -<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>FOCUS_2006_C</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Feb 15 17:09:39 2021 -#> Date of summary: Mon Feb 15 17:09:39 2021 -#> -#> Equations: -#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -#> -#> Model predictions using solution type analytical -#> -#> Fitted using 222 model solutions performed in 0.045 s -#> -#> Error model: Constant variance -#> -#> Error model algorithm: OLS -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 85.1 state -#> alpha 1.0 deparm -#> beta 10.0 deparm -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 85.100000 -Inf Inf -#> log_alpha 0.000000 -Inf Inf -#> log_beta 2.302585 -Inf Inf -#> -#> Fixed parameter values: -#> None -#> -#> Results: -#> -#> AIC BIC logLik -#> 44.68652 45.47542 -18.34326 -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 85.87000 1.8070 81.23000 90.5200 -#> log_alpha 0.05192 0.1353 -0.29580 0.3996 -#> log_beta 0.65100 0.2287 0.06315 1.2390 -#> sigma 1.85700 0.4378 0.73200 2.9830 -#> -#> Parameter correlation: -#> parent_0 log_alpha log_beta sigma -#> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.772e-08 -#> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.005e-07 -#> log_beta -3.142e-01 9.564e-01 1.000e+00 8.541e-08 -#> sigma 4.772e-08 1.005e-07 8.541e-08 1.000e+00 -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 85.870 47.530 3.893e-08 81.2300 90.520 -#> alpha 1.053 7.393 3.562e-04 0.7439 1.491 -#> beta 1.917 4.373 3.601e-03 1.0650 3.451 -#> sigma 1.857 4.243 4.074e-03 0.7320 2.983 -#> -#> FOCUS Chi2 error levels in percent: -#> err.min n.optim df -#> All data 6.657 3 6 -#> parent 6.657 3 6 -#> -#> Estimated disappearance times: -#> DT50 DT90 DT50back -#> parent 1.785 15.15 4.56 -#> -#> Data: -#> time variable observed predicted residual -#> 0 parent 85.1 85.875 -0.7749 -#> 1 parent 57.9 55.191 2.7091 -#> 3 parent 29.9 31.845 -1.9452 -#> 7 parent 14.6 17.012 -2.4124 -#> 14 parent 9.7 9.241 0.4590 -#> 28 parent 6.6 4.754 1.8460 -#> 63 parent 4.0 2.102 1.8977 -#> 91 parent 3.9 1.441 2.4590 -#> 119 parent 0.6 1.092 -0.4919</div><div class='input'> -<span class='co'># One parent compound, one metabolite, both single first order.</span> -<span class='co'># We remove zero values from FOCUS dataset D in order to avoid warnings</span> -<span class='va'>FOCUS_D</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> -<span class='co'># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span> -<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> - parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> -<span class='co'># Fit the model quietly to the FOCUS example dataset D using defaults</span> -<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='img'><img src='mkinfit-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># As lower parent values appear to have lower variance, we try an alternative error model</span> -<span class='va'>fit.tc</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -<span class='co'># This avoids the warning, and the likelihood ratio test confirms it is preferable</span> -<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>fit.tc</span>, <span class='va'>fit</span><span class='op'>)</span> -</div><div class='output co'>#> Likelihood ratio test -#> -#> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0 -#> Model 2: SFO_SFO with error model const and fixed parameter(s) m1_0 -#> #Df LogLik Df Chisq Pr(>Chisq) -#> 1 6 -64.983 -#> 2 5 -97.224 -1 64.483 9.737e-16 *** -#> --- -#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='co'># We can also allow for different variances of parent and metabolite as error model</span> -<span class='va'>fit.obs</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> -<span class='co'># The two-component error model has significantly higher likelihood</span> -<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>fit.obs</span>, <span class='va'>fit.tc</span><span class='op'>)</span> -</div><div class='output co'>#> Likelihood ratio test -#> -#> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0 -#> Model 2: SFO_SFO with error model obs and fixed parameter(s) m1_0 -#> #Df LogLik Df Chisq Pr(>Chisq) -#> 1 6 -64.983 -#> 2 6 -96.936 0 63.907 < 2.2e-16 *** -#> --- -#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</div><div class='input'><span class='fu'><a href='parms.html'>parms</a></span><span class='op'>(</span><span class='va'>fit.tc</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 k_parent k_m1 f_parent_to_m1 sigma_low -#> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049883e-03 -#> rsd_high -#> 7.928118e-02 </div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fit.tc</span><span class='op'>)</span> -</div><div class='output co'>#> $ff -#> parent_m1 parent_sink -#> 0.5083933 0.4916067 -#> -#> $distimes -#> DT50 DT90 -#> parent 6.89313 22.89848 -#> m1 134.15634 445.65772 -#> </div><div class='input'> -<span class='co'># We can show a quick (only one replication) benchmark for this case, as we</span> -<span class='co'># have several alternative solution methods for the model. We skip</span> -<span class='co'># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span> -<span class='co'># benchmark vignette</span> -<span class='co'># \dontrun{</span> -<span class='kw'>if</span><span class='op'>(</span><span class='kw'><a href='https://rdrr.io/r/base/library.html'>require</a></span><span class='op'>(</span><span class='va'><a href='http://rbenchmark.googlecode.com'>rbenchmark</a></span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span> - <span class='fu'><a href='https://rdrr.io/pkg/rbenchmark/man/benchmark.html'>benchmark</a></span><span class='op'>(</span>replications <span class='op'>=</span> <span class='fl'>1</span>, order <span class='op'>=</span> <span class='st'>"relative"</span>, columns <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"test"</span>, <span class='st'>"relative"</span>, <span class='st'>"elapsed"</span><span class='op'>)</span>, - deSolve_compiled <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, - solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, use_compiled <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - eigen <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, - solution_type <span class='op'>=</span> <span class='st'>"eigen"</span><span class='op'>)</span>, - analytical <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, - solution_type <span class='op'>=</span> <span class='st'>"analytical"</span><span class='op'>)</span><span class='op'>)</span> -<span class='op'>}</span> -</div><div class='output co'>#> test relative elapsed -#> 3 analytical 1.000 0.563 -#> 1 deSolve_compiled 1.702 0.958 -#> 2 eigen 2.597 1.462</div><div class='input'><span class='co'># }</span> - -<span class='co'># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span> -<span class='co'># \dontrun{</span> -<span class='va'>FOMC_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> - parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fit.FOMC_SFO</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='co'># Again, we get a warning and try a more sophisticated error model</span> -<span class='va'>fit.FOMC_SFO.tc</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -<span class='co'># This model has a higher likelihood, but not significantly so</span> -<span class='fu'><a href='https://rdrr.io/pkg/lmtest/man/lrtest.html'>lrtest</a></span><span class='op'>(</span><span class='va'>fit.tc</span>, <span class='va'>fit.FOMC_SFO.tc</span><span class='op'>)</span> -</div><div class='output co'>#> Likelihood ratio test -#> -#> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0 -#> Model 2: SFO_SFO with error model tc and fixed parameter(s) m1_0 -#> #Df LogLik Df Chisq Pr(>Chisq) -#> 1 7 -64.829 -#> 2 6 -64.983 -1 0.3075 0.5792</div><div class='input'><span class='co'># Also, the missing standard error for log_beta and the t-tests for alpha</span> -<span class='co'># and beta indicate overparameterisation</span> -<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.FOMC_SFO.tc</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: NaNs produced</span></div><div class='output co'>#> <span class='warning'>Warning: diag(.) had 0 or NA entries; non-finite result is doubtful</span></div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Feb 15 17:09:50 2021 -#> Date of summary: Mon Feb 15 17:09:50 2021 -#> -#> Equations: -#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -#> d_m1/dt = + f_parent_to_m1 * (alpha/beta) * 1/((time/beta) + 1) * -#> parent - k_m1 * m1 -#> -#> Model predictions using solution type deSolve -#> -#> Fitted using 3729 model solutions performed in 2.815 s -#> -#> Error model: Two-component variance function -#> -#> Error model algorithm: d_3 -#> Direct fitting and three-step fitting yield approximately the same likelihood -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.75 state -#> alpha 1.00 deparm -#> beta 10.00 deparm -#> k_m1 0.10 deparm -#> f_parent_to_m1 0.50 deparm -#> sigma_low 0.10 error -#> rsd_high 0.10 error -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 100.750000 -Inf Inf -#> log_k_m1 -2.302585 -Inf Inf -#> f_parent_qlogis 0.000000 -Inf Inf -#> log_alpha 0.000000 -Inf Inf -#> log_beta 2.302585 -Inf Inf -#> sigma_low 0.100000 0 Inf -#> rsd_high 0.100000 0 Inf -#> -#> Fixed parameter values: -#> value type -#> m1_0 0 state -#> -#> Results: -#> -#> AIC BIC logLik -#> 143.658 155.1211 -64.82902 -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 101.600000 2.6400000 96.240000 107.000000 -#> log_k_m1 -5.284000 0.0929100 -5.474000 -5.095000 -#> f_parent_qlogis 0.001426 0.0767000 -0.155000 0.157800 -#> log_alpha 5.522000 0.0077320 5.506000 5.538000 -#> log_beta 7.806000 NaN NaN NaN -#> sigma_low 0.002488 0.0002431 0.001992 0.002984 -#> rsd_high 0.079210 0.0093280 0.060180 0.098230 -#> -#> Parameter correlation: -#> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta -#> parent_0 1.000000 -0.095226 -0.76678 0.70544 NaN -#> log_k_m1 -0.095226 1.000000 0.51432 -0.14387 NaN -#> f_parent_qlogis -0.766780 0.514321 1.00000 -0.61396 NaN -#> log_alpha 0.705444 -0.143872 -0.61396 1.00000 NaN -#> log_beta NaN NaN NaN NaN 1 -#> sigma_low 0.016073 0.001586 0.01548 5.87007 NaN -#> rsd_high 0.006626 -0.011700 -0.05357 0.04849 NaN -#> sigma_low rsd_high -#> parent_0 0.016073 0.006626 -#> log_k_m1 0.001586 -0.011700 -#> f_parent_qlogis 0.015476 -0.053566 -#> log_alpha 5.870075 0.048487 -#> log_beta NaN NaN -#> sigma_low 1.000000 -0.652558 -#> rsd_high -0.652558 1.000000 -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02 -#> k_m1 5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03 -#> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01 -#> alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02 -#> beta 2.455e+03 0.5549 2.915e-01 NA NA -#> sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03 -#> rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02 -#> -#> FOCUS Chi2 error levels in percent: -#> err.min n.optim df -#> All data 6.781 5 14 -#> parent 7.141 3 6 -#> m1 4.640 2 8 -#> -#> Resulting formation fractions: -#> ff -#> parent_m1 0.5004 -#> parent_sink 0.4996 -#> -#> Estimated disappearance times: -#> DT50 DT90 DT50back -#> parent 6.812 22.7 6.834 -#> m1 136.661 454.0 NA</div><div class='input'> -<span class='co'># We can easily use starting parameters from the parent only fit (only for illustration)</span> -<span class='va'>fit.FOMC</span> <span class='op'>=</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -<span class='va'>fit.FOMC_SFO</span> <span class='op'><-</span> <span class='fu'>mkinfit</span><span class='op'>(</span><span class='va'>FOMC_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, - parms.ini <span class='op'>=</span> <span class='va'>fit.FOMC</span><span class='op'>$</span><span class='va'>bparms.ode</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -<span class='co'># }</span> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Use shorthand notation for parent only degradation</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:29:10 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:29:10 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 222 model solutions performed in 0.045 s</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model algorithm: OLS </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for parameters to be optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value type</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 85.1 state</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 1.0 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> beta 10.0 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for the transformed parameters actually optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 85.100000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.000000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta 2.302585 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 44.68652 45.47542 -18.34326</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised, transformed parameters with symmetric confidence intervals:</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 85.87000 1.8070 81.23000 90.5200</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.05192 0.1353 -0.29580 0.3996</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta 0.65100 0.2287 0.06315 1.2390</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.85700 0.4378 0.73200 2.9830</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_alpha log_beta sigma</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.772e-08</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.005e-07</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta -3.142e-01 9.564e-01 1.000e+00 8.541e-08</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 4.772e-08 1.005e-07 8.541e-08 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> +<span class="r-out co"><span class="r-pr">#></span> t-test (unrealistically) based on the assumption of normal distribution</span> +<span class="r-out co"><span class="r-pr">#></span> for estimators of untransformed parameters.</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate t value Pr(>t) Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 85.870 47.530 3.893e-08 81.2300 90.520</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 1.053 7.393 3.562e-04 0.7439 1.491</span> +<span class="r-out co"><span class="r-pr">#></span> beta 1.917 4.373 3.601e-03 1.0650 3.451</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.857 4.243 4.074e-03 0.7320 2.983</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> FOCUS Chi2 error levels in percent:</span> +<span class="r-out co"><span class="r-pr">#></span> err.min n.optim df</span> +<span class="r-out co"><span class="r-pr">#></span> All data 6.657 3 6</span> +<span class="r-out co"><span class="r-pr">#></span> parent 6.657 3 6</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back</span> +<span class="r-out co"><span class="r-pr">#></span> parent 1.785 15.15 4.56</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> time variable observed predicted residual</span> +<span class="r-out co"><span class="r-pr">#></span> 0 parent 85.1 85.875 -0.7749</span> +<span class="r-out co"><span class="r-pr">#></span> 1 parent 57.9 55.191 2.7091</span> +<span class="r-out co"><span class="r-pr">#></span> 3 parent 29.9 31.845 -1.9452</span> +<span class="r-out co"><span class="r-pr">#></span> 7 parent 14.6 17.012 -2.4124</span> +<span class="r-out co"><span class="r-pr">#></span> 14 parent 9.7 9.241 0.4590</span> +<span class="r-out co"><span class="r-pr">#></span> 28 parent 6.6 4.754 1.8460</span> +<span class="r-out co"><span class="r-pr">#></span> 63 parent 4.0 2.102 1.8977</span> +<span class="r-out co"><span class="r-pr">#></span> 91 parent 3.9 1.441 2.4590</span> +<span class="r-out co"><span class="r-pr">#></span> 119 parent 0.6 1.092 -0.4919</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># One parent compound, one metabolite, both single first order.</span></span></span> +<span class="r-in"><span><span class="co"># We remove zero values from FOCUS dataset D in order to avoid warnings</span></span></span> +<span class="r-in"><span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span></span></span> +<span class="r-in"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Fit the model quietly to the FOCUS example dataset D using defaults</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="plot.mkinfit.html">plot_sep</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="mkinfit-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># As lower parent values appear to have lower variance, we try an alternative error model</span></span></span> +<span class="r-in"><span><span class="va">fit.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This avoids the warning, and the likelihood ratio test confirms it is preferable</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> Model 2: SFO_SFO with error model const and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> #Df LogLik Df Chisq Pr(>Chisq) </span> +<span class="r-out co"><span class="r-pr">#></span> 1 6 -64.983 </span> +<span class="r-out co"><span class="r-pr">#></span> 2 5 -97.224 -1 64.483 9.737e-16 ***</span> +<span class="r-out co"><span class="r-pr">#></span> ---</span> +<span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> +<span class="r-in"><span><span class="co"># We can also allow for different variances of parent and metabolite as error model</span></span></span> +<span class="r-in"><span><span class="va">fit.obs</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># The two-component error model has significantly higher likelihood</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.obs</span>, <span class="va">fit.tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> Model 2: SFO_SFO with error model obs and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> #Df LogLik Df Chisq Pr(>Chisq) </span> +<span class="r-out co"><span class="r-pr">#></span> 1 6 -64.983 </span> +<span class="r-out co"><span class="r-pr">#></span> 2 6 -96.936 0 63.907 < 2.2e-16 ***</span> +<span class="r-out co"><span class="r-pr">#></span> ---</span> +<span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> +<span class="r-in"><span><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 k_parent k_m1 f_parent_to_m1 sigma_low </span> +<span class="r-out co"><span class="r-pr">#></span> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049883e-03 </span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high </span> +<span class="r-out co"><span class="r-pr">#></span> 7.928118e-02 </span> +<span class="r-in"><span><span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> $ff</span> +<span class="r-out co"><span class="r-pr">#></span> parent_m1 parent_sink </span> +<span class="r-out co"><span class="r-pr">#></span> 0.5083933 0.4916067 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $distimes</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> +<span class="r-out co"><span class="r-pr">#></span> parent 6.89313 22.89848</span> +<span class="r-out co"><span class="r-pr">#></span> m1 134.15634 445.65772</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can show a quick (only one replication) benchmark for this case, as we</span></span></span> +<span class="r-in"><span><span class="co"># have several alternative solution methods for the model. We skip</span></span></span> +<span class="r-in"><span><span class="co"># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span></span></span> +<span class="r-in"><span><span class="co"># benchmark vignette</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="kw">if</span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/rbenchmark/man/benchmark.html" class="external-link">benchmark</a></span><span class="op">(</span>replications <span class="op">=</span> <span class="fl">1</span>, order <span class="op">=</span> <span class="st">"relative"</span>, columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"test"</span>, <span class="st">"relative"</span>, <span class="st">"elapsed"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> deSolve_compiled <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, use_compiled <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> eigen <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"eigen"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> analytical <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"analytical"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Loading required package: rbenchmark</span> +<span class="r-out co"><span class="r-pr">#></span> test relative elapsed</span> +<span class="r-out co"><span class="r-pr">#></span> 3 analytical 1.000 0.577</span> +<span class="r-out co"><span class="r-pr">#></span> 1 deSolve_compiled 1.537 0.887</span> +<span class="r-out co"><span class="r-pr">#></span> 2 eigen 2.551 1.472</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Again, we get a warning and try a more sophisticated error model</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This model has a higher likelihood, but not significantly so</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit.FOMC_SFO.tc</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> Model 2: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> +<span class="r-out co"><span class="r-pr">#></span> #Df LogLik Df Chisq Pr(>Chisq)</span> +<span class="r-out co"><span class="r-pr">#></span> 1 7 -64.829 </span> +<span class="r-out co"><span class="r-pr">#></span> 2 6 -64.983 -1 0.3075 0.5792</span> +<span class="r-in"><span><span class="co"># Also, the missing standard error for log_beta and the t-tests for alpha</span></span></span> +<span class="r-in"><span><span class="co"># and beta indicate overparameterisation</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit.FOMC_SFO.tc</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>NaNs produced</span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>NaNs produced</span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>diag(.) had 0 or NA entries; non-finite result is doubtful</span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:29:21 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:29:21 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_m1/dt = + f_parent_to_m1 * (alpha/beta) * 1/((time/beta) + 1) *</span> +<span class="r-out co"><span class="r-pr">#></span> parent - k_m1 * m1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type deSolve </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 3729 model solutions performed in 2.48 s</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model: Two-component variance function </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model algorithm: d_3 </span> +<span class="r-out co"><span class="r-pr">#></span> Direct fitting and three-step fitting yield approximately the same likelihood </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for parameters to be optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value type</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.75 state</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 1.00 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> beta 10.00 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 0.10 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.50 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.10 error</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.10 error</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for the transformed parameters actually optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.750000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -2.302585 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.000000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.000000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta 2.302585 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.100000 0 Inf</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.100000 0 Inf</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> value type</span> +<span class="r-out co"><span class="r-pr">#></span> m1_0 0 state</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 143.658 155.1211 -64.82902</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised, transformed parameters with symmetric confidence intervals:</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 101.600000 2.6400000 96.240000 107.000000</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -5.284000 0.0929100 -5.474000 -5.095000</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.001426 0.0767000 -0.155000 0.157800</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.522000 0.0077320 5.506000 5.538000</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta 7.806000 NaN NaN NaN</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.002488 0.0002431 0.001992 0.002984</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.079210 0.0093280 0.060180 0.098230</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000000 -0.095226 -0.76678 0.70544 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.095226 1.000000 0.51432 -0.14387 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.766780 0.514321 1.00000 -0.61396 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.705444 -0.143872 -0.61396 1.00000 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN NaN NaN 1</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.016073 0.001586 0.01548 5.87007 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.006626 -0.011700 -0.05357 0.04849 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low rsd_high</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 0.016073 0.006626</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 0.001586 -0.011700</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.015476 -0.053566</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.870075 0.048487</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 1.000000 -0.652558</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high -0.652558 1.000000</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> +<span class="r-out co"><span class="r-pr">#></span> t-test (unrealistically) based on the assumption of normal distribution</span> +<span class="r-out co"><span class="r-pr">#></span> for estimators of untransformed parameters.</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate t value Pr(>t) Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02</span> +<span class="r-out co"><span class="r-pr">#></span> beta 2.455e+03 0.5549 2.915e-01 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> FOCUS Chi2 error levels in percent:</span> +<span class="r-out co"><span class="r-pr">#></span> err.min n.optim df</span> +<span class="r-out co"><span class="r-pr">#></span> All data 6.781 5 14</span> +<span class="r-out co"><span class="r-pr">#></span> parent 7.141 3 6</span> +<span class="r-out co"><span class="r-pr">#></span> m1 4.640 2 8</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> +<span class="r-out co"><span class="r-pr">#></span> ff</span> +<span class="r-out co"><span class="r-pr">#></span> parent_m1 0.5004</span> +<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.4996</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back</span> +<span class="r-out co"><span class="r-pr">#></span> parent 6.812 22.7 6.834</span> +<span class="r-out co"><span class="r-pr">#></span> m1 136.661 454.0 NA</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can easily use starting parameters from the parent only fit (only for illustration)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC</span> <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span></span> +<span class="r-in"><span> parms.ini <span class="op">=</span> <span class="va">fit.FOMC</span><span class="op">$</span><span class="va">bparms.ode</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" 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It is +inspired by the article on practical identifiabiliy in the frame of nonlinear +mixed-effects models by Duchesne et al (2021)."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Perform a hierarchical model fit with multiple starting values</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/multistart.R" class="external-link"><code>R/multistart.R</code></a></small> + <div class="hidden name"><code>multistart.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The purpose of this method is to check if a certain algorithm for fitting +nonlinear hierarchical models (also known as nonlinear mixed-effects models) +will reliably yield results that are sufficiently similar to each other, if +started with a certain range of reasonable starting parameters. It is +inspired by the article on practical identifiabiliy in the frame of nonlinear +mixed-effects models by Duchesne et al (2021).</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">multistart</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> n <span class="op">=</span> <span class="fl">50</span>,</span> +<span> cores <span class="op">=</span> <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Sys.info.html" class="external-link">Sys.info</a></span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="st">"sysname"</span><span class="op">]</span> <span class="op">==</span> <span class="st">"Windows"</span><span class="op">)</span> <span class="fl">1</span> <span class="kw">else</span> <span class="fu">parallel</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">detectCores</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> cluster <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu">multistart</span><span class="op">(</span><span class="va">object</span>, n <span class="op">=</span> <span class="fl">50</span>, cores <span class="op">=</span> <span class="fl">1</span>, cluster <span class="op">=</span> <span class="cn">NULL</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for multistart</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="fu">best</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for default</span></span> +<span><span class="fu">best</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="fu">which.best</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for default</span></span> +<span><span class="fu">which.best</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The fit object to work with</p></dd> + + +<dt>n</dt> +<dd><p>How many different combinations of starting parameters should be +used?</p></dd> + + +<dt>cores</dt> +<dd><p>How many fits should be run in parallel (only on posix platforms)?</p></dd> + + +<dt>cluster</dt> +<dd><p>A cluster as returned by <a href="https://rdrr.io/r/parallel/makeCluster.html" class="external-link">parallel::makeCluster</a> to be used +for parallel execution.</p></dd> + + +<dt>...</dt> +<dd><p>Passed to the update function.</p></dd> + + +<dt>x</dt> +<dd><p>The multistart object to print</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>A list of <a href="saem.html">saem.mmkin</a> objects, with class attributes +'multistart.saem.mmkin' and 'multistart'.</p> + + +<p>The object with the highest likelihood</p> + + +<p>The index of the object with the highest likelihood</p> + </div> + <div id="references"> + <h2>References</h2> + <p>Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +identifiability in the frame of nonlinear mixed effects models: the example +of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +doi: 10.1186/s12859-021-04373-4.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="parplot.html">parplot</a>, <a href="llhist.html">llhist</a></p></div> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/mkin/">mkin</a></span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">7</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span> <span class="op"><-</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span><span class="op">[[</span><span class="va">i</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span><span class="op">[</span><span class="va">ds_i</span><span class="op">$</span><span class="va">name</span> <span class="op">==</span> <span class="st">"DMTAP"</span>, <span class="st">"name"</span><span class="op">]</span> <span class="op"><-</span> <span class="st">"DMTA"</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op"><-</span> <span class="va">ds_i</span><span class="op">$</span><span class="va">time</span> <span class="op">*</span> <span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">f_time_norm</span><span class="op">[</span><span class="va">i</span><span class="op">]</span></span></span> +<span class="r-in"><span> <span class="va">ds_i</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">dimethenamid_2018</span><span class="op">$</span><span class="va">ds</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="va">ds</span><span class="op">$</span><span class="va">title</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/cbind.html" class="external-link">rbind</a></span><span class="op">(</span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span>, <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 1"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="va">dmta_ds</span><span class="op">[[</span><span class="st">"Elliot 2"</span><span class="op">]</span><span class="op">]</span> <span class="op"><-</span> <span class="cn">NULL</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="va">dmta_ds</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">7</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_full</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_full_multi</span> <span class="op"><-</span> <span class="fu">multistart</span><span class="op">(</span><span class="va">f_saem_full</span>, n <span class="op">=</span> <span class="fl">16</span>, cores <span class="op">=</span> <span class="fl">16</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_full_multi</span>, lpos <span class="op">=</span> <span class="st">"topleft"</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="multistart-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_full</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "sd(log_k2)"</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_saem_reduced</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_full</span>, no_random_effect <span class="op">=</span> <span class="st">"log_k2"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_reduced</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> character(0)</span> +<span class="r-in"><span><span class="co"># On Windows, we need to create a cluster first. When working with</span></span></span> +<span class="r-in"><span><span class="co"># such a cluster, we need to export the mmkin object to the cluster</span></span></span> +<span class="r-in"><span><span class="co"># nodes, as it is referred to when updating the saem object on the nodes.</span></span></span> +<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">parallel</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">cl</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/parallel/makeCluster.html" class="external-link">makePSOCKcluster</a></span><span class="op">(</span><span class="fl">12</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_reduced_multi</span> <span class="op"><-</span> <span class="fu">multistart</span><span class="op">(</span><span class="va">f_saem_reduced</span>, n <span class="op">=</span> <span class="fl">16</span>, cluster <span class="op">=</span> <span class="va">cl</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="parplot.html">parplot</a></span><span class="op">(</span><span class="va">f_saem_reduced_multi</span>, lpos <span class="op">=</span> <span class="st">"topright"</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="multistart-2.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/parallel/makeCluster.html" class="external-link">stopCluster</a></span><span class="op">(</span><span class="va">cl</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/nlme.mmkin-1.png b/docs/dev/reference/nlme.mmkin-1.png Binary files differindex d93b0950..45e4eebe 100644 --- a/docs/dev/reference/nlme.mmkin-1.png +++ b/docs/dev/reference/nlme.mmkin-1.png diff --git a/docs/dev/reference/nlme.mmkin-2.png b/docs/dev/reference/nlme.mmkin-2.png Binary files differindex 5afccfbb..b9a68e92 100644 --- a/docs/dev/reference/nlme.mmkin-2.png +++ b/docs/dev/reference/nlme.mmkin-2.png diff --git a/docs/dev/reference/nlme.mmkin-3.png b/docs/dev/reference/nlme.mmkin-3.png Binary files differindex bf3aac6c..2a724bed 100644 --- a/docs/dev/reference/nlme.mmkin-3.png +++ b/docs/dev/reference/nlme.mmkin-3.png diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html index e138ddd4..2bbadb88 100644 --- a/docs/dev/reference/nlme.mmkin.html +++ b/docs/dev/reference/nlme.mmkin.html @@ -19,7 +19,7 @@ have been obtained by fitting the same model to a list of datasets."><meta name= </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -28,7 +28,7 @@ have been obtained by fitting the same model to a list of datasets."><meta name= <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -43,6 +43,9 @@ have been obtained by fitting the same model to a list of datasets."><meta name= <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -88,78 +91,115 @@ have been obtained by fitting the same model to a list of datasets.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for mmkin</span> -<span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span> - <span class="va">model</span>, - data <span class="op">=</span> <span class="st">"auto"</span>, - fixed <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">as.list</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="fu"><a href="mean_degparms.html">mean_degparms</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>, <span class="kw">function</span><span class="op">(</span><span class="va">el</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/eval.html" class="external-link">eval</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/parse.html" class="external-link">parse</a></span><span class="op">(</span>text <span class="op">=</span> - <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="va">el</span>, <span class="fl">1</span>, sep <span class="op">=</span> <span class="st">"~"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>, - random <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/pdDiag.html" class="external-link">pdDiag</a></span><span class="op">(</span><span class="va">fixed</span><span class="op">)</span>, - <span class="va">groups</span>, - start <span class="op">=</span> <span class="fu"><a href="mean_degparms.html">mean_degparms</a></span><span class="op">(</span><span class="va">model</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, - correlation <span class="op">=</span> <span class="cn">NULL</span>, - weights <span class="op">=</span> <span class="cn">NULL</span>, - <span class="va">subset</span>, - method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ML"</span>, <span class="st">"REML"</span><span class="op">)</span>, - na.action <span class="op">=</span> <span class="va">na.fail</span>, - <span class="va">naPattern</span>, - control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>, - verbose <span class="op">=</span> <span class="cn">FALSE</span> -<span class="op">)</span> - -<span class="co"># S3 method for nlme.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for nlme.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span></span> +<span> <span class="va">model</span>,</span> +<span> data <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> fixed <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">as.list</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="fu"><a href="mean_degparms.html">mean_degparms</a></span><span class="op">(</span><span class="va">model</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>, <span class="kw">function</span><span class="op">(</span><span class="va">el</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/eval.html" class="external-link">eval</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/parse.html" class="external-link">parse</a></span><span class="op">(</span>text <span class="op">=</span></span> +<span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="va">el</span>, <span class="fl">1</span>, sep <span class="op">=</span> <span class="st">"~"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>,</span> +<span> random <span class="op">=</span> <span class="fu">pdDiag</span><span class="op">(</span><span class="va">fixed</span><span class="op">)</span>,</span> +<span> <span class="va">groups</span>,</span> +<span> start <span class="op">=</span> <span class="fu"><a href="mean_degparms.html">mean_degparms</a></span><span class="op">(</span><span class="va">model</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, test_log_parms <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span> +<span> correlation <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> weights <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> <span class="va">subset</span>,</span> +<span> method <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"ML"</span>, <span class="st">"REML"</span><span class="op">)</span>,</span> +<span> na.action <span class="op">=</span> <span class="va">na.fail</span>,</span> +<span> <span class="va">naPattern</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for nlme.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for nlme.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>model</dt> <dd><p>An <a href="mmkin.html">mmkin</a> row object.</p></dd> + + <dt>data</dt> <dd><p>Ignored, data are taken from the mmkin model</p></dd> + + <dt>fixed</dt> <dd><p>Ignored, all degradation parameters fitted in the mmkin model are used as fixed parameters</p></dd> + + <dt>random</dt> <dd><p>If not specified, no correlations between random effects are set up for the optimised degradation model parameters. This is achieved by using the <a href="https://rdrr.io/pkg/nlme/man/pdDiag.html" class="external-link">nlme::pdDiag</a> method.</p></dd> + + <dt>groups</dt> <dd><p>See the documentation of nlme</p></dd> + + <dt>start</dt> <dd><p>If not specified, mean values of the fitted degradation parameters taken from the mmkin object are used</p></dd> + + <dt>correlation</dt> <dd><p>See the documentation of nlme</p></dd> + + <dt>weights</dt> <dd><p>passed to nlme</p></dd> + + <dt>subset</dt> <dd><p>passed to nlme</p></dd> + + <dt>method</dt> <dd><p>passed to nlme</p></dd> + + <dt>na.action</dt> <dd><p>passed to nlme</p></dd> + + <dt>naPattern</dt> <dd><p>passed to nlme</p></dd> + + <dt>control</dt> <dd><p>passed to nlme</p></dd> + + <dt>verbose</dt> <dd><p>passed to nlme</p></dd> + + <dt>x</dt> <dd><p>An nlme.mmkin object to print</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + + <dt>...</dt> <dd><p>Update specifications passed to update.nlme</p></dd> + + <dt>object</dt> <dd><p>An nlme.mmkin object to update</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>Upon success, a fitted 'nlme.mmkin' object, which is an nlme object + + +<p>Upon success, a fitted 'nlme.mmkin' object, which is an nlme object with additional elements. It also inherits from 'mixed.mmkin'.</p> </div> <div id="details"> @@ -182,20 +222,19 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span>, <span class="va">name</span> <span class="op">==</span> <span class="st">"parent"</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span> -<span class="r-in"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://svn.r-project.org/R-packages/trunk/nlme/" class="external-link">nlme</a></span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_nlme_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_nlme_dfop</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_sfo</span>, <span class="va">f_nlme_dfop</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span>, <span class="va">name</span> <span class="op">==</span> <span class="st">"parent"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span> <span class="va">f</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://svn.r-project.org/R-packages/trunk/nlme/" class="external-link">nlme</a></span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_dfop</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_sfo</span>, <span class="va">f_nlme_dfop</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Model df AIC BIC logLik Test L.Ratio p-value</span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_sfo 1 5 625.0539 637.5529 -307.5269 </span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop 2 9 495.1270 517.6253 -238.5635 1 vs 2 137.9269 <.0001</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by maximum likelihood</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Structural model:</span> @@ -220,50 +259,50 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class="r-out co"><span class="r-pr">#></span> parent_0 log_k1 log_k2 g_qlogis Residual</span> <span class="r-out co"><span class="r-pr">#></span> StdDev: 2.488 0.8447 1.33 0.4652 2.321</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="nlme.mmkin-1.png" alt="" width="700" height="433"></span> -<span class="r-in"> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_dfop</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $distimes</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_k1 DT50_k2</span> <span class="r-out co"><span class="r-pr">#></span> parent 10.79857 100.7937 30.34193 4.193938 43.85443</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">ds_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">m_sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"min"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">m_sfo_sfo_ff</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">m_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_2</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">m_sfo_sfo</span>,</span> -<span class="r-in"> <span class="st">"SFO-SFO-ff"</span> <span class="op">=</span> <span class="va">m_sfo_sfo_ff</span>,</span> -<span class="r-in"> <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">m_dfop_sfo</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">ds_2</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_nlme_sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">ds_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">m_sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"min"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">m_sfo_sfo_ff</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">m_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">f_2</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">m_sfo_sfo</span>,</span></span> +<span class="r-in"><span> <span class="st">"SFO-SFO-ff"</span> <span class="op">=</span> <span class="va">m_sfo_sfo_ff</span>,</span></span> +<span class="r-in"><span> <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">m_dfop_sfo</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">ds_2</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="nlme.mmkin-2.png" alt="" width="700" height="433"></span> -<span class="r-in"></span> -<span class="r-in"> <span class="co"># With formation fractions this does not coverge with defaults</span></span> -<span class="r-in"> <span class="co"># f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])</span></span> -<span class="r-in"> <span class="co">#plot(f_nlme_sfo_sfo_ff)</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="co"># For the following, we need to increase pnlsMaxIter and the tolerance</span></span> -<span class="r-in"> <span class="co"># to get convergence</span></span> -<span class="r-in"> <span class="va">f_nlme_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span>,</span> -<span class="r-in"> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">5e-4</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="co"># With formation fractions this does not coverge with defaults</span></span></span> +<span class="r-in"><span> <span class="co"># f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])</span></span></span> +<span class="r-in"><span> <span class="co">#plot(f_nlme_sfo_sfo_ff)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="co"># For the following, we need to increase pnlsMaxIter and the tolerance</span></span></span> +<span class="r-in"><span> <span class="co"># to get convergence</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span>,</span></span> +<span class="r-in"><span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">5e-4</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="nlme.mmkin-3.png" alt="" width="700" height="433"></span> -<span class="r-in"></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span>, <span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span>, <span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Model df AIC BIC logLik Test L.Ratio p-value</span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 </span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_sfo_sfo 2 9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274 <.0001</span> -<span class="r-in"></span> -<span class="r-in"> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $ff</span> <span class="r-out co"><span class="r-pr">#></span> parent_sink parent_A1 A1_sink </span> <span class="r-out co"><span class="r-pr">#></span> 0.5912432 0.4087568 1.0000000 </span> @@ -273,7 +312,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class="r-out co"><span class="r-pr">#></span> parent 19.13518 63.5657</span> <span class="r-out co"><span class="r-pr">#></span> A1 66.02155 219.3189</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $ff</span> <span class="r-out co"><span class="r-pr">#></span> parent_A1 parent_sink </span> <span class="r-out co"><span class="r-pr">#></span> 0.2768574 0.7231426 </span> @@ -283,17 +322,17 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class="r-out co"><span class="r-pr">#></span> parent 11.07091 104.6320 31.49737 4.462383 46.20825</span> <span class="r-out co"><span class="r-pr">#></span> A1 162.30519 539.1662 NA NA NA</span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"></span> -<span class="r-in"> <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="fu">findFunction</span><span class="op">(</span><span class="st">"varConstProp"</span><span class="op">)</span><span class="op">)</span> <span class="op">></span> <span class="fl">0</span><span class="op">)</span> <span class="op">{</span> <span class="co"># tc error model for nlme available</span></span> -<span class="r-in"> <span class="co"># Attempts to fit metabolite kinetics with the tc error model are possible,</span></span> -<span class="r-in"> <span class="co"># but need tweeking of control values and sometimes do not converge</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_tc</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">f_nlme_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">f_nlme_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_nlme_sfo</span>, <span class="va">f_nlme_sfo_tc</span>, <span class="va">f_nlme_dfop</span>, <span class="va">f_nlme_dfop_tc</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_dfop_tc</span><span class="op">)</span></span> -<span class="r-in"> <span class="op">}</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="fu">findFunction</span><span class="op">(</span><span class="st">"varConstProp"</span><span class="op">)</span><span class="op">)</span> <span class="op">></span> <span class="fl">0</span><span class="op">)</span> <span class="op">{</span> <span class="co"># tc error model for nlme available</span></span></span> +<span class="r-in"><span> <span class="co"># Attempts to fit metabolite kinetics with the tc error model are possible,</span></span></span> +<span class="r-in"><span> <span class="co"># but need tweeking of control values and sometimes do not converge</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">f_tc</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_sfo_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_tc</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_dfop_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_tc</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_nlme_sfo</span>, <span class="va">f_nlme_sfo_tc</span>, <span class="va">f_nlme_dfop</span>, <span class="va">f_nlme_dfop_tc</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_dfop_tc</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="op">}</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by maximum likelihood</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Structural model:</span> @@ -324,10 +363,10 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class="r-out co"><span class="r-pr">#></span> Parameter estimates:</span> <span class="r-out co"><span class="r-pr">#></span> const prop </span> <span class="r-out co"><span class="r-pr">#></span> 2.23223147 0.01262395 </span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_2_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_2</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span> -<span class="r-in"> <span class="va">f_nlme_sfo_sfo_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2_obs</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo_obs</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">f_2_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_2</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">f_nlme_sfo_sfo_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2_obs</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_nlme_sfo_sfo_obs</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by maximum likelihood</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Structural model:</span> @@ -357,23 +396,23 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class="r-out co"><span class="r-pr">#></span> Parameter estimates:</span> <span class="r-out co"><span class="r-pr">#></span> parent A1 </span> <span class="r-out co"><span class="r-pr">#></span> 1.0000000 0.2049995 </span> -<span class="r-in"> <span class="va">f_nlme_dfop_sfo_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2_obs</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span>,</span> -<span class="r-in"> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">5e-4</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="va">f_2_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_2</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"> <span class="co"># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations</span></span> -<span class="r-in"> <span class="co"># f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ],</span></span> -<span class="r-in"> <span class="co"># control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm</span></span> -<span class="r-in"></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span>, <span class="va">f_nlme_dfop_sfo_obs</span><span class="op">)</span></span> +<span class="r-in"><span> <span class="va">f_nlme_dfop_sfo_obs</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_2_obs</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span>,</span></span> +<span class="r-in"><span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">5e-4</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="va">f_2_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_2</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="co"># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations</span></span></span> +<span class="r-in"><span> <span class="co"># f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ],</span></span></span> +<span class="r-in"><span> <span class="co"># control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_nlme_dfop_sfo</span>, <span class="va">f_nlme_dfop_sfo_obs</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Model df AIC BIC logLik Test L.Ratio</span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 </span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop_sfo_obs 2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32091</span> <span class="r-out co"><span class="r-pr">#></span> p-value</span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop_sfo </span> <span class="r-out co"><span class="r-pr">#></span> f_nlme_dfop_sfo_obs <.0001</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -388,7 +427,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/parhist.html b/docs/dev/reference/parhist.html new file mode 100644 index 00000000..27fc116f --- /dev/null +++ b/docs/dev/reference/parhist.html @@ -0,0 +1,169 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Plot parameter distributions from multistart objects — parhist • mkin</title><!-- jquery --><script 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property="og:description" content="Produces a boxplot with all parameters from the multiple runs, scaled +either by the parameters of the run with the highest likelihood, +or by their medians as proposed in the paper by Duchesne et al. (2021)."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Plot parameter distributions from multistart objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/parhist.R" class="external-link"><code>R/parhist.R</code></a></small> + <div class="hidden name"><code>parhist.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Produces a boxplot with all parameters from the multiple runs, scaled +either by the parameters of the run with the highest likelihood, +or by their medians as proposed in the paper by Duchesne et al. (2021).</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">parhist</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> llmin <span class="op">=</span> <span class="op">-</span><span class="cn">Inf</span>,</span> +<span> scale <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"best"</span>, <span class="st">"median"</span><span class="op">)</span>,</span> +<span> lpos <span class="op">=</span> <span class="st">"bottomleft"</span>,</span> +<span> main <span class="op">=</span> <span class="st">""</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The <a href="multistart.html">multistart</a> object</p></dd> + + +<dt>llmin</dt> +<dd><p>The minimum likelihood of objects to be shown</p></dd> + + +<dt>scale</dt> +<dd><p>By default, scale parameters using the best available fit. +If 'median', parameters are scaled using the median parameters from all fits.</p></dd> + + +<dt>lpos</dt> +<dd><p>Positioning of the legend.</p></dd> + + +<dt>main</dt> +<dd><p>Title of the plot</p></dd> + + +<dt>...</dt> +<dd><p>Passed to <a href="https://rdrr.io/r/graphics/boxplot.html" class="external-link">boxplot</a></p></dd> + +</dl></div> + <div id="references"> + <h2>References</h2> + <p>Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +identifiability in the frame of nonlinear mixed effects models: the example +of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +doi: 10.1186/s12859-021-04373-4.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="multistart.html">multistart</a></p></div> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/parms.html b/docs/dev/reference/parms.html index 9f6f4225..949bb2f9 100644 --- a/docs/dev/reference/parms.html +++ b/docs/dev/reference/parms.html @@ -1,69 +1,14 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - <head> - <meta charset="utf-8"> -<meta http-equiv="X-UA-Compatible" content="IE=edge"> -<meta name="viewport" content="width=device-width, initial-scale=1.0"> - 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- +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - </head> - - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -74,23 +19,21 @@ considering the error structure that was assumed for the fit." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -100,12 +43,18 @@ considering the error structure that was assumed for the fit." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -114,185 +63,199 @@ considering the error structure that was assumed for the fit." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> - <h1>Extract model parameters from mkinfit models</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/parms.mkinfit.R'><code>R/parms.mkinfit.R</code></a></small> + <h1>Extract model parameters</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/parms.R" class="external-link"><code>R/parms.R</code></a></small> <div class="hidden name"><code>parms.Rd</code></div> </div> <div class="ref-description"> - <p>This function always returns degradation model parameters as well as error -model parameters, in order to avoid working with a fitted model without -considering the error structure that was assumed for the fit.</p> + <p>This function returns degradation model parameters as well as error +model parameters per default, in order to avoid working with a fitted model +without considering the error structure that was assumed for the fit.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">parms</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu">parms</span><span class="op">(</span><span class="va">object</span>, transformed <span class="op">=</span> <span class="cn">FALSE</span>, errparms <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">parms</span><span class="op">(</span><span class="va">object</span>, transformed <span class="op">=</span> <span class="cn">FALSE</span>, errparms <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for multistart</span></span> +<span><span class="fu">parms</span><span class="op">(</span><span class="va">object</span>, exclude_failed <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> - <pre class="usage"><span class='fu'>parms</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>...</span><span class='op'>)</span> + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>A fitted model object.</p></dd> -<span class='co'># S3 method for mkinfit</span> -<span class='fu'>parms</span><span class='op'>(</span><span class='va'>object</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span><span class='op'>)</span> -<span class='co'># S3 method for mmkin</span> -<span class='fu'>parms</span><span class='op'>(</span><span class='va'>object</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span><span class='op'>)</span></pre> +<dt>...</dt> +<dd><p>Not used</p></dd> - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>object</th> - <td><p>A fitted model object. Methods are implemented for -<code><a href='mkinfit.html'>mkinfit()</a></code> objects and for <code><a href='mmkin.html'>mmkin()</a></code> objects.</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Not used</p></td> - </tr> - <tr> - <th>transformed</th> - <td><p>Should the parameters be returned -as used internally during the optimisation?</p></td> - </tr> - </table> - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> +<dt>transformed</dt> +<dd><p>Should the parameters be returned as used internally +during the optimisation?</p></dd> - <p>For mkinfit objects, a numeric vector of fitted model parameters. -For mmkin row objects, a matrix with the parameters with a -row for each dataset. If the mmkin object has more than one row, a list of -such matrices is returned.</p> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'><span class='co'># mkinfit objects</span> -<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>FOCUS_2006_C</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -<span class='fu'>parms</span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 k_parent sigma -#> 82.4921598 0.3060633 4.6730124 </div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fit</span>, transformed <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 log_k_parent sigma -#> 82.492160 -1.183963 4.673012 </div><div class='input'> -<span class='co'># mmkin objects</span> -<span class='va'>ds</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>, - <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</span><span class='op'>[</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Dataset"</span>, <span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>)</span> -<span class='co'># \dontrun{</span> -<span class='va'>fits</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span> -<span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450 -#> k_parent 0.05794659 0.009647805 0.2102974 0.1232258 0.00720421 -#> sigma 5.15274487 7.040168584 3.6769645 6.4669234 6.50457673</div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span><span class='op'>[</span>, <span class='fl'>2</span><span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> $SFO -#> Dataset 7 -#> parent_0 82.666781678 -#> k_parent 0.009647805 -#> sigma 7.040168584 -#> -#> $FOMC -#> Dataset 7 -#> parent_0 92.6837649 -#> alpha 0.4967832 -#> beta 14.1451255 -#> sigma 1.9167519 -#> -#> $DFOP -#> Dataset 7 -#> parent_0 91.058971589 -#> k1 0.044946770 -#> k2 0.002868336 -#> g 0.526942415 -#> sigma 2.221302196 -#> </div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span><span class='op'>)</span> -</div><div class='output co'>#> $SFO -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450 -#> k_parent 0.05794659 0.009647805 0.2102974 0.1232258 0.00720421 -#> sigma 5.15274487 7.040168584 3.6769645 6.4669234 6.50457673 -#> -#> $FOMC -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481459 -#> alpha 1.338667 0.4967832 1.639099 1.074460 0.2805272 -#> beta 13.033315 14.1451255 5.007077 4.397126 6.9052224 -#> sigma 1.847671 1.9167519 1.066063 3.146056 1.6222778 -#> -#> $DFOP -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 96.55213663 91.058971589 90.34509493 98.14858820 94.311323734 -#> k1 0.21954588 0.044946770 0.41232288 0.31697588 0.080663857 -#> k2 0.02957934 0.002868336 0.07581766 0.03260384 0.003425417 -#> g 0.44845068 0.526942415 0.66091967 0.65322767 0.342652880 -#> sigma 1.35690468 2.221302196 1.34169076 2.87159846 1.942067831 -#> </div><div class='input'><span class='fu'>parms</span><span class='op'>(</span><span class='va'>fits</span>, transformed <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> $SFO -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 88.522754 82.666782 86.854731 91.777931 82.148094 -#> log_k_parent -2.848234 -4.641025 -1.559232 -2.093737 -4.933090 -#> sigma 5.152745 7.040169 3.676964 6.466923 6.504577 -#> -#> $FOMC -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 95.5585751 92.6837649 90.7197870 98.38393897 94.848146 -#> log_alpha 0.2916741 -0.6996015 0.4941466 0.07181816 -1.271085 -#> log_beta 2.5675088 2.6493701 1.6108523 1.48095106 1.932278 -#> sigma 1.8476712 1.9167519 1.0660627 3.14605557 1.622278 -#> -#> $DFOP -#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 -#> parent_0 96.5521366 91.0589716 90.3450949 98.1485882 94.3113237 -#> log_k1 -1.5161940 -3.1022764 -0.8859486 -1.1489296 -2.5174647 -#> log_k2 -3.5206791 -5.8540232 -2.5794240 -3.4233253 -5.6765322 -#> g_qlogis -0.2069326 0.1078741 0.6673953 0.6332573 -0.6514943 -#> sigma 1.3569047 2.2213022 1.3416908 2.8715985 1.9420678 -#> </div><div class='input'><span class='co'># }</span> -</div></pre> +<dt>errparms</dt> +<dd><p>Should the error model parameters be returned +in addition to the degradation parameters?</p></dd> + + +<dt>exclude_failed</dt> +<dd><p>For <a href="multistart.html">multistart</a> objects, should rows for failed fits +be removed from the returned parameter matrix?</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>Depending on the object, a numeric vector of fitted model parameters, +a matrix (e.g. for mmkin row objects), or a list of matrices (e.g. for +mmkin objects with more than one row).</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="saem.html">saem</a>, <a href="multistart.html">multistart</a></p></div> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># mkinfit objects</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 k_parent sigma </span> +<span class="r-out co"><span class="r-pr">#></span> 82.4921598 0.3060633 4.6730124 </span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fit</span>, transformed <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_parent sigma </span> +<span class="r-out co"><span class="r-pr">#></span> 82.492160 -1.183963 4.673012 </span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># mmkin objects</span></span></span> +<span class="r-in"><span><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fits</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.05794659 0.009647805 0.2102974 0.1232258 0.00720421</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 5.15274487 7.040168584 3.6769645 6.4669234 6.50457673</span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fits</span><span class="op">[</span>, <span class="fl">2</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> $SFO</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 82.666781678</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.009647805</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 7.040168584</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $FOMC</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 92.6837649</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 0.4967832</span> +<span class="r-out co"><span class="r-pr">#></span> beta 14.1451255</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.9167519</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $DFOP</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 91.058971589</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.044946770</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.002868336</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.526942415</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 2.221302196</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> $SFO</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.05794659 0.009647805 0.2102974 0.1232258 0.00720421</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 5.15274487 7.040168584 3.6769645 6.4669234 6.50457673</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $FOMC</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481459</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 1.338667 0.4967832 1.639099 1.074460 0.2805272</span> +<span class="r-out co"><span class="r-pr">#></span> beta 13.033315 14.1451255 5.007077 4.397126 6.9052224</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.847671 1.9167519 1.066063 3.146056 1.6222778</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $DFOP</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 96.55213663 91.058971589 90.34509493 98.14858820 94.311323734</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.21954588 0.044946770 0.41232288 0.31697588 0.080663857</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.02957934 0.002868336 0.07581766 0.03260384 0.003425417</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.44845068 0.526942415 0.66091967 0.65322767 0.342652880</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.35690468 2.221302196 1.34169076 2.87159846 1.942067831</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span><span class="fu">parms</span><span class="op">(</span><span class="va">fits</span>, transformed <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> $SFO</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 88.522754 82.666782 86.854731 91.777931 82.148094</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -2.848234 -4.641025 -1.559232 -2.093737 -4.933090</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 5.152745 7.040169 3.676964 6.466923 6.504577</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $FOMC</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 95.5585751 92.6837649 90.7197870 98.38393897 94.848146</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.2916741 -0.6996015 0.4941466 0.07181816 -1.271085</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta 2.5675088 2.6493701 1.6108523 1.48095106 1.932278</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.8476712 1.9167519 1.0660627 3.14605557 1.622278</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $DFOP</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 96.5521366 91.0589716 90.3450949 98.1485882 94.3113237</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -1.5161940 -3.1022764 -0.8859486 -1.1489296 -2.5174647</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.5206791 -5.8540232 -2.5794240 -3.4233253 -5.6765322</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.2069326 0.1078741 0.6673953 0.6332573 -0.6514943</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.3569047 2.2213022 1.3416908 2.8715985 1.9420678</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/parplot.html 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(2021)."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Plot parameter variability of multistart objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/parplot.R" class="external-link"><code>R/parplot.R</code></a></small> + <div class="hidden name"><code>parplot.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Produces a boxplot with all parameters from the multiple runs, scaled +either by the parameters of the run with the highest likelihood, +or by their medians as proposed in the paper by Duchesne et al. (2021).</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">parplot</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for multistart.saem.mmkin</span></span> +<span><span class="fu">parplot</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> llmin <span class="op">=</span> <span class="op">-</span><span class="cn">Inf</span>,</span> +<span> scale <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"best"</span>, <span class="st">"median"</span><span class="op">)</span>,</span> +<span> lpos <span class="op">=</span> <span class="st">"bottomleft"</span>,</span> +<span> main <span class="op">=</span> <span class="st">""</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The <a href="multistart.html">multistart</a> object</p></dd> + + +<dt>...</dt> +<dd><p>Passed to <a href="https://rdrr.io/r/graphics/boxplot.html" class="external-link">boxplot</a></p></dd> + + +<dt>llmin</dt> +<dd><p>The minimum likelihood of objects to be shown</p></dd> + + +<dt>scale</dt> +<dd><p>By default, scale parameters using the best available fit. +If 'median', parameters are scaled using the median parameters from all fits.</p></dd> + + +<dt>lpos</dt> +<dd><p>Positioning of the legend.</p></dd> + + +<dt>main</dt> +<dd><p>Title of the plot</p></dd> + +</dl></div> + <div id="references"> + <h2>References</h2> + <p>Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +identifiability in the frame of nonlinear mixed effects models: the example +of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +doi: 10.1186/s12859-021-04373-4.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><a href="multistart.html">multistart</a></p></div> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/plot.mixed.mmkin-2.png b/docs/dev/reference/plot.mixed.mmkin-2.png Binary files differindex 67c9b8ab..8678c166 100644 --- a/docs/dev/reference/plot.mixed.mmkin-2.png +++ b/docs/dev/reference/plot.mixed.mmkin-2.png diff --git a/docs/dev/reference/plot.mixed.mmkin-3.png b/docs/dev/reference/plot.mixed.mmkin-3.png Binary files differindex 7e2876b3..9bd01852 100644 --- a/docs/dev/reference/plot.mixed.mmkin-3.png +++ b/docs/dev/reference/plot.mixed.mmkin-3.png diff --git a/docs/dev/reference/plot.mixed.mmkin-4.png b/docs/dev/reference/plot.mixed.mmkin-4.png Binary files differindex 945c4d41..d2fa1ae1 100644 --- a/docs/dev/reference/plot.mixed.mmkin-4.png +++ b/docs/dev/reference/plot.mixed.mmkin-4.png diff --git a/docs/dev/reference/plot.mixed.mmkin.html b/docs/dev/reference/plot.mixed.mmkin.html index 19b8e2c1..83017908 100644 --- a/docs/dev/reference/plot.mixed.mmkin.html +++ b/docs/dev/reference/plot.mixed.mmkin.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -26,7 +26,7 @@ <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -41,6 +41,9 @@ <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -84,90 +87,139 @@ </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for mixed.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span> - <span class="va">x</span>, - i <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">ncol</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">mmkin</span><span class="op">)</span>, - obs_vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">map</span><span class="op">)</span>, - standardized <span class="op">=</span> <span class="cn">TRUE</span>, - xlab <span class="op">=</span> <span class="st">"Time"</span>, - xlim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">$</span><span class="va">time</span><span class="op">)</span>, - resplot <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"predicted"</span>, <span class="st">"time"</span><span class="op">)</span>, - pred_over <span class="op">=</span> <span class="cn">NULL</span>, - test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>, - conf.level <span class="op">=</span> <span class="fl">0.6</span>, - ymax <span class="op">=</span> <span class="st">"auto"</span>, - maxabs <span class="op">=</span> <span class="st">"auto"</span>, - ncol.legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op"><=</span> <span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span>, <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op"><=</span> <span class="fl">8</span>, <span class="fl">3</span>, <span class="fl">4</span><span class="op">)</span><span class="op">)</span>, - nrow.legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span><span class="op">/</span><span class="va">ncol.legend</span><span class="op">)</span>, - rel.height.legend <span class="op">=</span> <span class="fl">0.02</span> <span class="op">+</span> <span class="fl">0.07</span> <span class="op">*</span> <span class="va">nrow.legend</span>, - rel.height.bottom <span class="op">=</span> <span class="fl">1.1</span>, - pch_ds <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span>, - col_ds <span class="op">=</span> <span class="va">pch_ds</span> <span class="op">+</span> <span class="fl">1</span>, - lty_ds <span class="op">=</span> <span class="va">col_ds</span>, - frame <span class="op">=</span> <span class="cn">TRUE</span>, - <span class="va">...</span> -<span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mixed.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span></span> +<span> <span class="va">x</span>,</span> +<span> i <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fu"><a href="https://rdrr.io/r/base/nrow.html" class="external-link">ncol</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">mmkin</span><span class="op">)</span>,</span> +<span> obs_vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">map</span><span class="op">)</span>,</span> +<span> standardized <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> xlab <span class="op">=</span> <span class="st">"Time"</span>,</span> +<span> xlim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">$</span><span class="va">time</span><span class="op">)</span>,</span> +<span> resplot <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"predicted"</span>, <span class="st">"time"</span><span class="op">)</span>,</span> +<span> pred_over <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> default_log_parms <span class="op">=</span> <span class="cn">NA</span>,</span> +<span> ymax <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> maxabs <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> ncol.legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op"><=</span> <span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span>, <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op"><=</span> <span class="fl">8</span>, <span class="fl">3</span>, <span class="fl">4</span><span class="op">)</span><span class="op">)</span>,</span> +<span> nrow.legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">ceiling</a></span><span class="op">(</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">+</span> <span class="fl">1</span><span class="op">)</span><span class="op">/</span><span class="va">ncol.legend</span><span class="op">)</span>,</span> +<span> rel.height.legend <span class="op">=</span> <span class="fl">0.02</span> <span class="op">+</span> <span class="fl">0.07</span> <span class="op">*</span> <span class="va">nrow.legend</span>,</span> +<span> rel.height.bottom <span class="op">=</span> <span class="fl">1.1</span>,</span> +<span> pch_ds <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">i</span><span class="op">)</span>,</span> +<span> col_ds <span class="op">=</span> <span class="va">pch_ds</span> <span class="op">+</span> <span class="fl">1</span>,</span> +<span> lty_ds <span class="op">=</span> <span class="va">col_ds</span>,</span> +<span> frame <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>x</dt> <dd><p>An object of class <a href="mixed.html">mixed.mmkin</a>, <a href="saem.html">saem.mmkin</a> or <a href="nlme.mmkin.html">nlme.mmkin</a></p></dd> + + <dt>i</dt> <dd><p>A numeric index to select datasets for which to plot the individual predictions, in case plots get too large</p></dd> + + <dt>obs_vars</dt> <dd><p>A character vector of names of the observed variables for which the data and the model should be plotted. Defauls to all observed variables in the model.</p></dd> + + <dt>standardized</dt> <dd><p>Should the residuals be standardized? Only takes effect if <code>resplot = "time"</code>.</p></dd> + + <dt>xlab</dt> <dd><p>Label for the x axis.</p></dd> + + <dt>xlim</dt> <dd><p>Plot range in x direction.</p></dd> + + <dt>resplot</dt> <dd><p>Should the residuals plotted against time or against predicted values?</p></dd> + + <dt>pred_over</dt> <dd><p>Named list of alternative predictions as obtained from <a href="mkinpredict.html">mkinpredict</a> with a compatible <a href="mkinmod.html">mkinmod</a>.</p></dd> + + <dt>test_log_parms</dt> <dd><p>Passed to <a href="mean_degparms.html">mean_degparms</a> in the case of an <a href="mixed.html">mixed.mmkin</a> object</p></dd> + + <dt>conf.level</dt> <dd><p>Passed to <a href="mean_degparms.html">mean_degparms</a> in the case of an <a href="mixed.html">mixed.mmkin</a> object</p></dd> + + +<dt>default_log_parms</dt> +<dd><p>Passed to <a href="mean_degparms.html">mean_degparms</a> in the case of an +<a href="mixed.html">mixed.mmkin</a> object</p></dd> + + <dt>ymax</dt> <dd><p>Vector of maximum y axis values</p></dd> + + <dt>maxabs</dt> <dd><p>Maximum absolute value of the residuals. This is used for the scaling of the y axis and defaults to "auto".</p></dd> + + <dt>ncol.legend</dt> <dd><p>Number of columns to use in the legend</p></dd> + + <dt>nrow.legend</dt> <dd><p>Number of rows to use in the legend</p></dd> + + <dt>rel.height.legend</dt> <dd><p>The relative height of the legend shown on top</p></dd> + + <dt>rel.height.bottom</dt> <dd><p>The relative height of the bottom plot row</p></dd> + + <dt>pch_ds</dt> <dd><p>Symbols to be used for plotting the data.</p></dd> + + <dt>col_ds</dt> <dd><p>Colors used for plotting the observed data and the corresponding model prediction lines for the different datasets.</p></dd> + + <dt>lty_ds</dt> <dd><p>Line types to be used for the model predictions.</p></dd> + + <dt>frame</dt> <dd><p>Should a frame be drawn around the plots?</p></dd> + + <dt>...</dt> <dd><p>Further arguments passed to <code><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></code>.</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>The function is called for its side effect.</p> + + +<p>The function is called for its side effect.</p> </div> <div id="author"> <h2>Author</h2> @@ -176,42 +228,41 @@ corresponding model prediction lines for the different datasets.</p></dd> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="st">"ds "</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span> -<span class="r-in"><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">f</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span>, <span class="fl">3</span><span class="op">:</span><span class="fl">4</span><span class="op">]</span>, standardized <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="st">"ds "</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">f</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f</span><span class="op">[</span>, <span class="fl">3</span><span class="op">:</span><span class="fl">4</span><span class="op">]</span>, standardized <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="plot.mixed.mmkin-1.png" alt="" width="700" height="433"></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># For this fit we need to increase pnlsMaxiter, and we increase the</span></span> -<span class="r-in"><span class="co"># tolerance in order to speed up the fit for this example evaluation</span></span> -<span class="r-in"><span class="co"># It still takes 20 seconds to run</span></span> -<span class="r-in"><span class="va">f_nlme</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span>, control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">1e-3</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># For this fit we need to increase pnlsMaxiter, and we increase the</span></span></span> +<span class="r-in"><span><span class="co"># tolerance in order to speed up the fit for this example evaluation</span></span></span> +<span class="r-in"><span><span class="co"># It still takes 20 seconds to run</span></span></span> +<span class="r-in"><span><span class="va">f_nlme</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f</span>, control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>pnlsMaxIter <span class="op">=</span> <span class="fl">120</span>, tolerance <span class="op">=</span> <span class="fl">1e-3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlme</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="plot.mixed.mmkin-2.png" alt="" width="700" height="433"></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_saem</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in saem(f, transformations = "saemix"):</span> unused argument (transformations = "saemix")</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in plot(f_saem):</span> object 'f_saem' not found</span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_obs</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_nlmix</span> <span class="op"><-</span> <span class="fu">nlmix</span><span class="op">(</span><span class="va">f_obs</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_saem</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f</span>, transformations <span class="op">=</span> <span class="st">"saemix"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mixed.mmkin-3.png" alt="" width="700" height="433"></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_obs</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_nlmix</span> <span class="op"><-</span> <span class="fu">nlmix</span><span class="op">(</span><span class="va">f_obs</span><span class="op">)</span></span></span> <span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in nlmix(f_obs):</span> could not find function "nlmix"</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlmix</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_nlmix</span><span class="op">)</span></span></span> <span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in plot(f_nlmix):</span> object 'f_nlmix' not found</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># We can overlay the two variants if we generate predictions</span></span> -<span class="r-in"><span class="va">pred_nlme</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span> -<span class="r-in"> <span class="va">f_nlme</span><span class="op">$</span><span class="va">bparms.optim</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="va">f_nlme</span><span class="op">$</span><span class="va">bparms.optim</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>, A1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">180</span>, by <span class="op">=</span> <span class="fl">0.2</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem</span>, pred_over <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>nlme <span class="op">=</span> <span class="va">pred_nlme</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in plot(f_saem, pred_over = list(nlme = pred_nlme)):</span> object 'f_saem' not found</span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can overlay the two variants if we generate predictions</span></span></span> +<span class="r-in"><span><span class="va">pred_nlme</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span></span> +<span class="r-in"><span> <span class="va">f_nlme</span><span class="op">$</span><span class="va">bparms.optim</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="va">f_nlme</span><span class="op">$</span><span class="va">bparms.optim</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>, A1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">180</span>, by <span class="op">=</span> <span class="fl">0.2</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem</span>, pred_over <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>nlme <span class="op">=</span> <span class="va">pred_nlme</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mixed.mmkin-4.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -226,7 +277,7 @@ corresponding model prediction lines for the different datasets.</p></dd> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/plot.mkinfit-1.png b/docs/dev/reference/plot.mkinfit-1.png Binary files differindex e5da9f1c..ea1032fb 100644 --- a/docs/dev/reference/plot.mkinfit-1.png +++ b/docs/dev/reference/plot.mkinfit-1.png diff --git 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class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -100,6 +43,9 @@ observed data together with the solution of the fitted model." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -114,279 +60,285 @@ observed data together with the solution of the fitted model." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Plot the observed data and the fitted model of an mkinfit object</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/plot.mkinfit.R'><code>R/plot.mkinfit.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/plot.mkinfit.R" class="external-link"><code>R/plot.mkinfit.R</code></a></small> <div class="hidden name"><code>plot.mkinfit.Rd</code></div> </div> <div class="ref-description"> <p>Solves the differential equations with the optimised and fixed parameters -from a previous successful call to <code><a href='mkinfit.html'>mkinfit</a></code> and plots the +from a previous successful call to <code><a href="mkinfit.html">mkinfit</a></code> and plots the observed data together with the solution of the fitted model.</p> </div> - <pre class="usage"><span class='co'># S3 method for mkinfit</span> -<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span> - <span class='va'>x</span>, - fit <span class='op'>=</span> <span class='va'>x</span>, - obs_vars <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>mkinmod</span><span class='op'>$</span><span class='va'>map</span><span class='op'>)</span>, - xlab <span class='op'>=</span> <span class='st'>"Time"</span>, - ylab <span class='op'>=</span> <span class='st'>"Residue"</span>, - xlim <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/range.html'>range</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>data</span><span class='op'>$</span><span class='va'>time</span><span class='op'>)</span>, - ylim <span class='op'>=</span> <span class='st'>"default"</span>, - col_obs <span class='op'>=</span> <span class='fl'>1</span><span class='op'>:</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>obs_vars</span><span class='op'>)</span>, - pch_obs <span class='op'>=</span> <span class='va'>col_obs</span>, - lty_obs <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span><span class='op'>(</span><span class='fl'>1</span>, <span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='va'>obs_vars</span><span class='op'>)</span><span class='op'>)</span>, - add <span class='op'>=</span> <span class='cn'>FALSE</span>, - legend <span class='op'>=</span> <span class='op'>!</span><span class='va'>add</span>, - show_residuals <span class='op'>=</span> <span class='cn'>FALSE</span>, - show_errplot <span class='op'>=</span> <span class='cn'>FALSE</span>, - maxabs <span class='op'>=</span> <span class='st'>"auto"</span>, - sep_obs <span class='op'>=</span> <span class='cn'>FALSE</span>, - rel.height.middle <span class='op'>=</span> <span class='fl'>0.9</span>, - row_layout <span class='op'>=</span> <span class='cn'>FALSE</span>, - lpos <span class='op'>=</span> <span class='st'>"topright"</span>, - inset <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0.05</span>, <span class='fl'>0.05</span><span class='op'>)</span>, - show_errmin <span class='op'>=</span> <span class='cn'>FALSE</span>, - errmin_digits <span class='op'>=</span> <span class='fl'>3</span>, - frame <span class='op'>=</span> <span class='cn'>TRUE</span>, - <span class='va'>...</span> -<span class='op'>)</span> - -<span class='fu'>plot_sep</span><span class='op'>(</span> - <span class='va'>fit</span>, - show_errmin <span class='op'>=</span> <span class='cn'>TRUE</span>, - show_residuals <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/identical.html'>identical</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>err_mod</span>, <span class='st'>"const"</span><span class='op'>)</span>, <span class='cn'>TRUE</span>, <span class='st'>"standardized"</span><span class='op'>)</span>, - <span class='va'>...</span> -<span class='op'>)</span> - -<span class='fu'>plot_res</span><span class='op'>(</span> - <span class='va'>fit</span>, - sep_obs <span class='op'>=</span> <span class='cn'>FALSE</span>, - show_errmin <span class='op'>=</span> <span class='va'>sep_obs</span>, - standardized <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/ifelse.html'>ifelse</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/identical.html'>identical</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>err_mod</span>, <span class='st'>"const"</span><span class='op'>)</span>, <span class='cn'>FALSE</span>, <span class='cn'>TRUE</span><span class='op'>)</span>, - <span class='va'>...</span> -<span class='op'>)</span> - -<span class='fu'>plot_err</span><span class='op'>(</span><span class='va'>fit</span>, sep_obs <span class='op'>=</span> <span class='cn'>FALSE</span>, show_errmin <span class='op'>=</span> <span class='va'>sep_obs</span>, <span class='va'>...</span><span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>x</th> - <td><p>Alias for fit introduced for compatibility with the generic S3 -method.</p></td> - </tr> - <tr> - <th>fit</th> - <td><p>An object of class <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> - </tr> - <tr> - <th>obs_vars</th> - <td><p>A character vector of names of the observed variables for + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span></span> +<span> <span class="va">x</span>,</span> +<span> fit <span class="op">=</span> <span class="va">x</span>,</span> +<span> obs_vars <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">fit</span><span class="op">$</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">map</span><span class="op">)</span>,</span> +<span> xlab <span class="op">=</span> <span class="st">"Time"</span>,</span> +<span> ylab <span class="op">=</span> <span class="st">"Residue"</span>,</span> +<span> xlim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/range.html" class="external-link">range</a></span><span class="op">(</span><span class="va">fit</span><span class="op">$</span><span class="va">data</span><span class="op">$</span><span class="va">time</span><span class="op">)</span>,</span> +<span> ylim <span class="op">=</span> <span class="st">"default"</span>,</span> +<span> col_obs <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">obs_vars</span><span class="op">)</span>,</span> +<span> pch_obs <span class="op">=</span> <span class="va">col_obs</span>,</span> +<span> lty_obs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fu"><a href="https://rdrr.io/r/base/length.html" class="external-link">length</a></span><span class="op">(</span><span class="va">obs_vars</span><span class="op">)</span><span class="op">)</span>,</span> +<span> add <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> legend <span class="op">=</span> <span class="op">!</span><span class="va">add</span>,</span> +<span> show_residuals <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> show_errplot <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> maxabs <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> sep_obs <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> rel.height.middle <span class="op">=</span> <span class="fl">0.9</span>,</span> +<span> row_layout <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> lpos <span class="op">=</span> <span class="st">"topright"</span>,</span> +<span> inset <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0.05</span>, <span class="fl">0.05</span><span class="op">)</span>,</span> +<span> show_errmin <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> errmin_digits <span class="op">=</span> <span class="fl">3</span>,</span> +<span> frame <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="fu">plot_sep</span><span class="op">(</span></span> +<span> <span class="va">fit</span>,</span> +<span> show_errmin <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> show_residuals <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">fit</span><span class="op">$</span><span class="va">err_mod</span>, <span class="st">"const"</span><span class="op">)</span>, <span class="cn">TRUE</span>, <span class="st">"standardized"</span><span class="op">)</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="fu">plot_res</span><span class="op">(</span></span> +<span> <span class="va">fit</span>,</span> +<span> sep_obs <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> show_errmin <span class="op">=</span> <span class="va">sep_obs</span>,</span> +<span> standardized <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/ifelse.html" class="external-link">ifelse</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">fit</span><span class="op">$</span><span class="va">err_mod</span>, <span class="st">"const"</span><span class="op">)</span>, <span class="cn">FALSE</span>, <span class="cn">TRUE</span><span class="op">)</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="fu">plot_err</span><span class="op">(</span><span class="va">fit</span>, sep_obs <span class="op">=</span> <span class="cn">FALSE</span>, show_errmin <span class="op">=</span> <span class="va">sep_obs</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>x</dt> +<dd><p>Alias for fit introduced for compatibility with the generic S3 +method.</p></dd> + + +<dt>fit</dt> +<dd><p>An object of class <code><a href="mkinfit.html">mkinfit</a></code>.</p></dd> + + +<dt>obs_vars</dt> +<dd><p>A character vector of names of the observed variables for which the data and the model should be plotted. Defauls to all observed -variables in the model.</p></td> - </tr> - <tr> - <th>xlab</th> - <td><p>Label for the x axis.</p></td> - </tr> - <tr> - <th>ylab</th> - <td><p>Label for the y axis.</p></td> - </tr> - <tr> - <th>xlim</th> - <td><p>Plot range in x direction.</p></td> - </tr> - <tr> - <th>ylim</th> - <td><p>Plot range in y direction.</p></td> - </tr> - <tr> - <th>col_obs</th> - <td><p>Colors used for plotting the observed data and the -corresponding model prediction lines.</p></td> - </tr> - <tr> - <th>pch_obs</th> - <td><p>Symbols to be used for plotting the data.</p></td> - </tr> - <tr> - <th>lty_obs</th> - <td><p>Line types to be used for the model predictions.</p></td> - </tr> - <tr> - <th>add</th> - <td><p>Should the plot be added to an existing plot?</p></td> - </tr> - <tr> - <th>legend</th> - <td><p>Should a legend be added to the plot?</p></td> - </tr> - <tr> - <th>show_residuals</th> - <td><p>Should residuals be shown? If only one plot of the +variables in the model.</p></dd> + + +<dt>xlab</dt> +<dd><p>Label for the x axis.</p></dd> + + +<dt>ylab</dt> +<dd><p>Label for the y axis.</p></dd> + + +<dt>xlim</dt> +<dd><p>Plot range in x direction.</p></dd> + + +<dt>ylim</dt> +<dd><p>Plot range in y direction. If given as a list, plot ranges +for the different plot rows can be given for row layout.</p></dd> + + +<dt>col_obs</dt> +<dd><p>Colors used for plotting the observed data and the +corresponding model prediction lines.</p></dd> + + +<dt>pch_obs</dt> +<dd><p>Symbols to be used for plotting the data.</p></dd> + + +<dt>lty_obs</dt> +<dd><p>Line types to be used for the model predictions.</p></dd> + + +<dt>add</dt> +<dd><p>Should the plot be added to an existing plot?</p></dd> + + +<dt>legend</dt> +<dd><p>Should a legend be added to the plot?</p></dd> + + +<dt>show_residuals</dt> +<dd><p>Should residuals be shown? If only one plot of the fits is shown, the residual plot is in the lower third of the plot. Otherwise, i.e. if "sep_obs" is given, the residual plots will be located to the right of the plots of the fitted curves. If this is set to 'standardized', a plot of the residuals divided by the standard deviation -given by the fitted error model will be shown.</p></td> - </tr> - <tr> - <th>show_errplot</th> - <td><p>Should squared residuals and the error model be shown? +given by the fitted error model will be shown.</p></dd> + + +<dt>show_errplot</dt> +<dd><p>Should squared residuals and the error model be shown? If only one plot of the fits is shown, this plot is in the lower third of the plot. Otherwise, i.e. if "sep_obs" is given, the residual plots will -be located to the right of the plots of the fitted curves.</p></td> - </tr> - <tr> - <th>maxabs</th> - <td><p>Maximum absolute value of the residuals. This is used for the -scaling of the y axis and defaults to "auto".</p></td> - </tr> - <tr> - <th>sep_obs</th> - <td><p>Should the observed variables be shown in separate subplots? +be located to the right of the plots of the fitted curves.</p></dd> + + +<dt>maxabs</dt> +<dd><p>Maximum absolute value of the residuals. This is used for the +scaling of the y axis and defaults to "auto".</p></dd> + + +<dt>sep_obs</dt> +<dd><p>Should the observed variables be shown in separate subplots? If yes, residual plots requested by "show_residuals" will be shown next -to, not below the plot of the fits.</p></td> - </tr> - <tr> - <th>rel.height.middle</th> - <td><p>The relative height of the middle plot, if more -than two rows of plots are shown.</p></td> - </tr> - <tr> - <th>row_layout</th> - <td><p>Should we use a row layout where the residual plot or the -error model plot is shown to the right?</p></td> - </tr> - <tr> - <th>lpos</th> - <td><p>Position(s) of the legend(s). Passed to <code><a href='https://rdrr.io/r/graphics/legend.html'>legend</a></code> as +to, not below the plot of the fits.</p></dd> + + +<dt>rel.height.middle</dt> +<dd><p>The relative height of the middle plot, if more +than two rows of plots are shown.</p></dd> + + +<dt>row_layout</dt> +<dd><p>Should we use a row layout where the residual plot or the +error model plot is shown to the right?</p></dd> + + +<dt>lpos</dt> +<dd><p>Position(s) of the legend(s). Passed to <code><a href="https://rdrr.io/r/graphics/legend.html" class="external-link">legend</a></code> as the first argument. If not length one, this should be of the same length -as the obs_var argument.</p></td> - </tr> - <tr> - <th>inset</th> - <td><p>Passed to <code><a href='https://rdrr.io/r/graphics/legend.html'>legend</a></code> if applicable.</p></td> - </tr> - <tr> - <th>show_errmin</th> - <td><p>Should the FOCUS chi2 error value be shown in the upper -margin of the plot?</p></td> - </tr> - <tr> - <th>errmin_digits</th> - <td><p>The number of significant digits for rounding the FOCUS -chi2 error percentage.</p></td> - </tr> - <tr> - <th>frame</th> - <td><p>Should a frame be drawn around the plots?</p></td> - </tr> - <tr> - <th>...</th> - <td><p>Further arguments passed to <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></code>.</p></td> - </tr> - <tr> - <th>standardized</th> - <td><p>When calling 'plot_res', should the residuals be -standardized in the residual plot?</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>The function is called for its side effect.</p> - <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> - - <p>If the current plot device is a <code><a href='https://rdrr.io/pkg/tikzDevice/man/tikz.html'>tikz</a></code> device, then +as the obs_var argument.</p></dd> + + +<dt>inset</dt> +<dd><p>Passed to <code><a href="https://rdrr.io/r/graphics/legend.html" class="external-link">legend</a></code> if applicable.</p></dd> + + +<dt>show_errmin</dt> +<dd><p>Should the FOCUS chi2 error value be shown in the upper +margin of the plot?</p></dd> + + +<dt>errmin_digits</dt> +<dd><p>The number of significant digits for rounding the FOCUS +chi2 error percentage.</p></dd> + + +<dt>frame</dt> +<dd><p>Should a frame be drawn around the plots?</p></dd> + + +<dt>...</dt> +<dd><p>Further arguments passed to <code><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></code>.</p></dd> + + +<dt>standardized</dt> +<dd><p>When calling 'plot_res', should the residuals be +standardized in the residual plot?</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>The function is called for its side effect.</p> + </div> + <div id="details"> + <h2>Details</h2> + <p>If the current plot device is a <code><a href="https://rdrr.io/pkg/tikzDevice/man/tikz.html" class="external-link">tikz</a></code> device, then latex is being used for the formatting of the chi2 error level, if <code>show_errmin = TRUE</code>.</p> - <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> - + </div> + <div id="author"> + <h2>Author</h2> <p>Johannes Ranke</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='co'># One parent compound, one metabolite, both single first order, path from</span> -<span class='co'># parent to sink included</span> -<span class='co'># \dontrun{</span> -<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span>, full <span class='op'>=</span> <span class='st'>"Parent"</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, full <span class='op'>=</span> <span class='st'>"Metabolite M1"</span> <span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>plot_res</span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>plot_res</span><span class='op'>(</span><span class='va'>fit</span>, standardized <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-3.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'>plot_err</span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-4.png' alt='' width='700' height='433' /></div><div class='input'> -<span class='co'># Show the observed variables separately, with residuals</span> -<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>fit</span>, sep_obs <span class='op'>=</span> <span class='cn'>TRUE</span>, show_residuals <span class='op'>=</span> <span class='cn'>TRUE</span>, lpos <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"topright"</span>, <span class='st'>"bottomright"</span><span class='op'>)</span>, - show_errmin <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-5.png' alt='' width='700' height='433' /></div><div class='input'> -<span class='co'># The same can be obtained with less typing, using the convenience function plot_sep</span> -<span class='fu'>plot_sep</span><span class='op'>(</span><span class='va'>fit</span>, lpos <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"topright"</span>, <span class='st'>"bottomright"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-6.png' alt='' width='700' height='433' /></div><div class='input'> -<span class='co'># Show the observed variables separately, with the error model</span> -<span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>fit</span>, sep_obs <span class='op'>=</span> <span class='cn'>TRUE</span>, show_errplot <span class='op'>=</span> <span class='cn'>TRUE</span>, lpos <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"topright"</span>, <span class='st'>"bottomright"</span><span class='op'>)</span>, - show_errmin <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='img'><img src='plot.mkinfit-7.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span> - -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># One parent compound, one metabolite, both single first order, path from</span></span></span> +<span class="r-in"><span><span class="co"># parent to sink included</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span>, full <span class="op">=</span> <span class="st">"Parent"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, full <span class="op">=</span> <span class="st">"Metabolite M1"</span> <span class="op">)</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>Observations with value of zero were removed from the data</span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>Observations with value of zero were removed from the data</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu">plot_res</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-2.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu">plot_res</span><span class="op">(</span><span class="va">fit</span>, standardized <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-3.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu">plot_err</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-4.png" alt="" width="700" height="433"></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Show the observed variables separately, with residuals</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">fit</span>, sep_obs <span class="op">=</span> <span class="cn">TRUE</span>, show_residuals <span class="op">=</span> <span class="cn">TRUE</span>, lpos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"topright"</span>, <span class="st">"bottomright"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> show_errmin <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-5.png" alt="" width="700" height="433"></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># The same can be obtained with less typing, using the convenience function plot_sep</span></span></span> +<span class="r-in"><span><span class="fu">plot_sep</span><span class="op">(</span><span class="va">fit</span>, lpos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"topright"</span>, <span class="st">"bottomright"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-6.png" alt="" width="700" height="433"></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Show the observed variables separately, with the error model</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">fit</span>, sep_obs <span class="op">=</span> <span class="cn">TRUE</span>, show_errplot <span class="op">=</span> <span class="cn">TRUE</span>, lpos <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"topright"</span>, <span class="st">"bottomright"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> show_errmin <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="plot.mkinfit-7.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/reexports.html b/docs/dev/reference/reexports.html index b8ead4b5..0999e346 100644 --- a/docs/dev/reference/reexports.html +++ b/docs/dev/reference/reexports.html @@ -10,10 +10,6 @@ lrtest intervals, nlme - nlmixr -nlmixr - - "><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> @@ -32,7 +28,7 @@ nlmixr </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -41,7 +37,7 @@ nlmixr <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -56,6 +52,9 @@ nlmixr <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -90,7 +89,7 @@ nlmixr <div class="col-md-9 contents"> <div class="page-header"> <h1>Objects exported from other packages</h1> - <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/intervals.R" class="external-link"><code>R/intervals.R</code></a>, <a href="https://github.com/jranke/mkin/blob/HEAD/R/lrtest.mkinfit.R" class="external-link"><code>R/lrtest.mkinfit.R</code></a>, <a href="https://github.com/jranke/mkin/blob/HEAD/R/nlme.mmkin.R" class="external-link"><code>R/nlme.mmkin.R</code></a>, and 1 more</small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/intervals.R" class="external-link"><code>R/intervals.R</code></a>, <a href="https://github.com/jranke/mkin/blob/HEAD/R/lrtest.mkinfit.R" class="external-link"><code>R/lrtest.mkinfit.R</code></a>, <a href="https://github.com/jranke/mkin/blob/HEAD/R/nlme.mmkin.R" class="external-link"><code>R/nlme.mmkin.R</code></a></small> <div class="hidden name"><code>reexports.Rd</code></div> </div> @@ -105,10 +104,6 @@ below to see their documentation.</p> <dd><p><code><a href="https://rdrr.io/pkg/nlme/man/intervals.html" class="external-link">intervals</a></code>, <code><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></code></p></dd> - <dt>nlmixr</dt> -<dd><p><code><a href="https://rdrr.io/pkg/nlmixr/man/nlmixr.html" class="external-link">nlmixr</a></code></p></dd> - - </dl></div> @@ -125,7 +120,7 @@ below to see their documentation.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/saem-1.png b/docs/dev/reference/saem-1.png Binary files differindex 0e87d741..08939d4f 100644 --- a/docs/dev/reference/saem-1.png +++ b/docs/dev/reference/saem-1.png diff --git a/docs/dev/reference/saem-2.png b/docs/dev/reference/saem-2.png Binary files differindex 456a4c58..b737db03 100644 --- a/docs/dev/reference/saem-2.png +++ b/docs/dev/reference/saem-2.png diff --git a/docs/dev/reference/saem-3.png b/docs/dev/reference/saem-3.png Binary files differindex 27d43e53..08e0f544 100644 --- a/docs/dev/reference/saem-3.png +++ b/docs/dev/reference/saem-3.png diff --git a/docs/dev/reference/saem-4.png b/docs/dev/reference/saem-4.png Binary files differindex 5c089bbc..bb775c25 100644 --- a/docs/dev/reference/saem-4.png +++ b/docs/dev/reference/saem-4.png diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index c132647b..c8a7504f 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -19,7 +19,7 @@ Expectation Maximisation algorithm (SAEM)."><meta name="robots" content="noindex </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -28,7 +28,7 @@ Expectation Maximisation algorithm (SAEM)."><meta name="robots" content="noindex <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -43,12 +43,18 @@ Expectation Maximisation algorithm (SAEM)."><meta name="robots" content="noindex <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> - <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> </li> <li> <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> </li> <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> </li> <li> @@ -88,39 +94,51 @@ Expectation Maximisation algorithm (SAEM).</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">saem</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for mmkin</span> -<span class="fu">saem</span><span class="op">(</span> - <span class="va">object</span>, - transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>, - degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>, - test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>, - conf.level <span class="op">=</span> <span class="fl">0.6</span>, - solution_type <span class="op">=</span> <span class="st">"auto"</span>, - nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">300</span>, <span class="fl">100</span><span class="op">)</span>, - control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>displayProgress <span class="op">=</span> <span class="cn">FALSE</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, nbiter.saemix <span class="op">=</span> <span class="va">nbiter.saemix</span>, - save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>, - fail_with_errors <span class="op">=</span> <span class="cn">TRUE</span>, - verbose <span class="op">=</span> <span class="cn">FALSE</span>, - quiet <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span> - -<span class="co"># S3 method for saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span> - -<span class="fu">saemix_model</span><span class="op">(</span> - <span class="va">object</span>, - solution_type <span class="op">=</span> <span class="st">"auto"</span>, - transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>, - degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>, - test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>, - verbose <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span> - -<span class="fu">saemix_data</span><span class="op">(</span><span class="va">object</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">saem</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">saem</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>,</span> +<span> degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> solution_type <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> covariance.model <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> covariates <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> no_random_effect <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">300</span>, <span class="fl">100</span><span class="op">)</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>displayProgress <span class="op">=</span> <span class="cn">FALSE</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, nbiter.saemix <span class="op">=</span> <span class="va">nbiter.saemix</span>,</span> +<span> save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> +<span> fail_with_errors <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="fu">saemix_model</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> solution_type <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>,</span> +<span> degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> covariance.model <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> no_random_effect <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> covariates <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> covariate_models <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="fu">saemix_data</span><span class="op">(</span><span class="va">object</span>, covariates <span class="op">=</span> <span class="cn">NULL</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">object</span>, ci <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> @@ -128,54 +146,115 @@ Expectation Maximisation algorithm (SAEM).</p> <dl><dt>object</dt> <dd><p>An <a href="mmkin.html">mmkin</a> row object containing several fits of the same <a href="mkinmod.html">mkinmod</a> model to different datasets</p></dd> + + <dt>...</dt> <dd><p>Further parameters passed to <a href="https://rdrr.io/pkg/saemix/man/saemixModel.html" class="external-link">saemix::saemixModel</a>.</p></dd> + + <dt>transformations</dt> <dd><p>Per default, all parameter transformations are done in mkin. If this argument is set to 'saemix', parameter transformations -are done in 'saemix' for the supported cases. Currently this is only -supported in cases where the initial concentration of the parent is not fixed, -SFO or DFOP is used for the parent and there is either no metabolite or one.</p></dd> +are done in 'saemix' for the supported cases, i.e. (as of version 1.1.2) +SFO, FOMC, DFOP and HS without fixing <code>parent_0</code>, and SFO or DFOP with +one SFO metabolite.</p></dd> + + <dt>degparms_start</dt> <dd><p>Parameter values given as a named numeric vector will be used to override the starting values obtained from the 'mmkin' object.</p></dd> + + <dt>test_log_parms</dt> <dd><p>If TRUE, an attempt is made to use more robust starting values for population parameters fitted as log parameters in mkin (like rate constants) by only considering rate constants that pass the t-test when calculating mean degradation parameters using <a href="mean_degparms.html">mean_degparms</a>.</p></dd> + + <dt>conf.level</dt> <dd><p>Possibility to adjust the required confidence level for parameter that are tested if requested by 'test_log_parms'.</p></dd> + + <dt>solution_type</dt> <dd><p>Possibility to specify the solution type in case the automatic choice is not desired</p></dd> + + +<dt>covariance.model</dt> +<dd><p>Will be passed to <code><a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel()</a></code>. Per +default, uncorrelated random effects are specified for all degradation +parameters.</p></dd> + + +<dt>covariates</dt> +<dd><p>A data frame with covariate data for use in +'covariate_models', with dataset names as row names.</p></dd> + + +<dt>covariate_models</dt> +<dd><p>A list containing linear model formulas with one explanatory +variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available +in the 'covariates' data frame.</p></dd> + + +<dt>no_random_effect</dt> +<dd><p>Character vector of degradation parameters for +which there should be no variability over the groups. Only used +if the covariance model is not explicitly specified.</p></dd> + + <dt>nbiter.saemix</dt> <dd><p>Convenience option to increase the number of iterations</p></dd> + + <dt>control</dt> <dd><p>Passed to <a href="https://rdrr.io/pkg/saemix/man/saemix.html" class="external-link">saemix::saemix</a>.</p></dd> + + <dt>fail_with_errors</dt> <dd><p>Should a failure to compute standard errors from the inverse of the Fisher Information Matrix be a failure?</p></dd> + + <dt>verbose</dt> <dd><p>Should we print information about created objects of type <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> and <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a>?</p></dd> + + <dt>quiet</dt> <dd><p>Should we suppress the messages saemix prints at the beginning and the end of the optimisation process?</p></dd> + + <dt>x</dt> <dd><p>An saem.mmkin object to print</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + + +<dt>ci</dt> +<dd><p>Should a matrix with estimates and confidence interval boundaries +be returned? If FALSE (default), a vector of estimates is returned.</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>An S3 object of class 'saem.mmkin', containing the fitted + + +<p>An S3 object of class 'saem.mmkin', containing the fitted <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a> as a list component named 'so'. The -object also inherits from 'mixed.mmkin'. -An <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> object. -An <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a> object.</p> +object also inherits from 'mixed.mmkin'.</p> + + +<p>An <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> object.</p> + + +<p>An <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a> object.</p> </div> <div id="details"> <h2>Details</h2> @@ -192,109 +271,424 @@ using <a href="mmkin.html">mmkin</a>.</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_mmkin_parent_p0_fixed</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">ds</span>,</span> -<span class="r-in"> state.ini <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, fixed_initials <span class="op">=</span> <span class="st">"parent"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_p0_fixed</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_p0_fixed</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_mmkin_parent</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="va">f_saem_fomc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="va">f_saem_dfop</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span></span> -<span class="r-in"><span class="co"># functions from saemix</span></span> -<span class="r-in"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent_p0_fixed</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">ds</span>,</span></span> +<span class="r-in"><span> state.ini <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, fixed_initials <span class="op">=</span> <span class="st">"parent"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_p0_fixed</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_p0_fixed</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_fomc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_sfo</span>, <span class="va">f_saem_fomc</span>, <span class="va">f_saem_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Data: 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> npar AIC BIC Lik</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_sfo 5 624.26 622.31 -307.13</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_fomc 7 467.87 465.13 -226.93</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_dfop 9 493.98 490.47 -237.99</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_sfo</span>, <span class="va">f_saem_dfop</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Data: 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> npar AIC BIC Lik Chisq Df Pr(>Chisq) </span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_sfo 5 624.26 622.31 -307.13 </span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_dfop 9 493.98 490.47 -237.99 138.28 4 < 2.2e-16 ***</span> +<span class="r-out co"><span class="r-pr">#></span> ---</span> +<span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "sd(g_qlogis)"</span> +<span class="r-in"><span><span class="va">f_saem_dfop_red</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_dfop</span>, no_random_effect <span class="op">=</span> <span class="st">"g_qlogis"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_dfop</span>, <span class="va">f_saem_dfop_red</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Data: 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> npar AIC BIC Lik Chisq Df Pr(>Chisq)</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_dfop_red 8 490.64 487.52 -237.32 </span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_dfop 9 493.98 490.47 -237.99 0 1 1</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_sfo</span>, <span class="va">f_saem_fomc</span>, <span class="va">f_saem_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Data: 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> npar AIC BIC Lik</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_sfo 5 624.26 622.31 -307.13</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_fomc 7 467.87 465.13 -226.93</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_dfop 9 493.98 490.47 -237.99</span> +<span class="r-in"><span><span class="co"># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span></span></span> +<span class="r-in"><span><span class="co"># functions from saemix</span></span></span> +<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Loading required package: npde</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> Attaching package: ‘npde’</span> -<span class="r-msg co"><span class="r-pr">#></span> The following object is masked from ‘package:nlmixr’:</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> warfarin</span> -<span class="r-msg co"><span class="r-pr">#></span> Package saemix, version 3.0</span> +<span class="r-msg co"><span class="r-pr">#></span> Package saemix, version 3.2</span> <span class="r-msg co"><span class="r-pr">#></span> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span> <span class="r-msg co"><span class="r-pr">#></span> </span> <span class="r-msg co"><span class="r-pr">#></span> Attaching package: ‘saemix’</span> <span class="r-msg co"><span class="r-pr">#></span> The following objects are masked from ‘package:npde’:</span> <span class="r-msg co"><span class="r-pr">#></span> </span> <span class="r-msg co"><span class="r-pr">#></span> kurtosis, skewness</span> -<span class="r-msg co"><span class="r-pr">#></span> The following object is masked from ‘package:RxODE’:</span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-msg co"><span class="r-pr">#></span> phi</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_sfo</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_dfop</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so):</span> object 'f_saem_sfo' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"individual.fit"</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"npde"</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"vpc"</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found</span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_mmkin_parent_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_mmkin_parent</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_fomc_tc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_tc</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so):</span> object 'f_saem_fomc' not found</span> -<span class="r-in"></span> -<span class="r-in"><span class="va">sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_sfo</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_dfop</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span></span> +<span class="r-msg co"><span class="r-pr">#></span> Likelihoods calculated by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC</span> +<span class="r-out co"><span class="r-pr">#></span> 1 624.2598 622.3070</span> +<span class="r-out co"><span class="r-pr">#></span> 2 467.8664 465.1324</span> +<span class="r-out co"><span class="r-pr">#></span> 3 493.9811 490.4660</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="saem-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"individual.fit"</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="saem-2.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"npde"</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Simulating data using nsim = 1000 simulated datasets</span> +<span class="r-out co"><span class="r-pr">#></span> Computing WRES and npde .</span> +<span class="r-msg co"><span class="r-pr">#></span> Please use npdeSaemix to obtain VPC and npde</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"vpc"</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="saem-3.png" alt="" width="700" height="433"></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_mmkin_parent</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_fomc_tc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_tc</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/anova.html" class="external-link">anova</a></span><span class="op">(</span><span class="va">f_saem_fomc</span>, <span class="va">f_saem_fomc_tc</span>, test <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Data: 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> npar AIC BIC Lik Chisq Df Pr(>Chisq)</span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_fomc 7 467.87 465.13 -226.93 </span> +<span class="r-out co"><span class="r-pr">#></span> f_saem_fomc_tc 8 469.80 466.68 -226.90 0.0645 1 0.7995</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">fomc_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">fomc_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="co"># The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,</span></span> -<span class="r-in"><span class="co"># and compiled ODEs for FOMC that are much slower</span></span> -<span class="r-in"><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">sfo_sfo</span>, <span class="st">"FOMC-SFO"</span> <span class="op">=</span> <span class="va">fomc_sfo</span>, <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds</span></span> -<span class="r-in"><span class="co"># each on this system, as we use analytical solutions written for saemix.</span></span> -<span class="r-in"><span class="co"># When using the analytical solutions written for mkin this took around</span></span> -<span class="r-in"><span class="co"># four minutes</span></span> -<span class="r-in"><span class="va">f_saem_sfo_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="co"># We can use print, plot and summary methods to check the results</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'print': object 'f_saem_dfop_sfo' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_dfop_sfo' not found</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_saem_dfop_sfo' not found</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># The following takes about 6 minutes</span></span> -<span class="r-in"><span class="co">#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span></span> -<span class="r-in"><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co">#saemix::compare.saemix(list(</span></span> -<span class="r-in"><span class="co"># f_saem_dfop_sfo$so,</span></span> -<span class="r-in"><span class="co"># f_saem_dfop_sfo_deSolve$so))</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># If the model supports it, we can also use eigenvalue based solutions, which</span></span> -<span class="r-in"><span class="co"># take a similar amount of time</span></span> -<span class="r-in"><span class="co">#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",</span></span> -<span class="r-in"><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span><span class="co"># The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,</span></span></span> +<span class="r-in"><span><span class="co"># and compiled ODEs for FOMC that are much slower</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">sfo_sfo</span>, <span class="st">"FOMC-SFO"</span> <span class="op">=</span> <span class="va">fomc_sfo</span>, <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds</span></span></span> +<span class="r-in"><span><span class="co"># each on this system, as we use analytical solutions written for saemix.</span></span></span> +<span class="r-in"><span><span class="co"># When using the analytical solutions written for mkin this took around</span></span></span> +<span class="r-in"><span><span class="co"># four minutes</span></span></span> +<span class="r-in"><span><span class="va">f_saem_sfo_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># We can use print, plot and summary methods to check the results</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by SAEM</span> +<span class="r-out co"><span class="r-pr">#></span> Structural model:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)</span> +<span class="r-out co"><span class="r-pr">#></span> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time))) * parent - k_A1 * A1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 170 observations of 2 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 842 836.9 -408</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> estimate lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 93.7701 91.1458 96.3945</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_A1 -5.8116 -7.5998 -4.0234</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.9608 -1.3654 -0.5562</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.5841 -3.6876 -1.4805</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.5228 -5.3254 -1.7203</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.1027 -0.8719 0.6665</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 1.8856 1.6676 2.1037</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7668 4.7695</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_A1 1.7447 0.4047 3.0848</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4525 0.1620 0.7431</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.2423 0.4560 2.0285</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.0390 0.7601 3.3180</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3069 1.1947</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="saem-4.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.2 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Oct 26 09:20:37 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Oct 26 09:20:37 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)</span> +<span class="r-out co"><span class="r-pr">#></span> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time))) * parent - k_A1 * A1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 170 observations of 2 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 8.902 s</span> +<span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 10 chains</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model: Constant variance </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Mean of starting values for individual parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 </span> +<span class="r-out co"><span class="r-pr">#></span> 93.8102 -5.3734 -0.9711 -1.8799 -4.2708 </span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis </span> +<span class="r-out co"><span class="r-pr">#></span> 0.1356 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 842 836.9 -408</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 93.7701 91.1458 96.3945</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_A1 -5.8116 -7.5998 -4.0234</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.9608 -1.3654 -0.5562</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.5841 -3.6876 -1.4805</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.5228 -5.3254 -1.7203</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.1027 -0.8719 0.6665</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 1.8856 1.6676 2.1037</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7668 4.7695</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_A1 1.7447 0.4047 3.0848</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4525 0.1620 0.7431</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.2423 0.4560 2.0285</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.0390 0.7601 3.3180</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3069 1.1947</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Correlation: </span> +<span class="r-out co"><span class="r-pr">#></span> parnt_0 lg_k_A1 f_prnt_ log_k1 log_k2 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k_A1 -0.0160 </span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.0263 0.0612 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 0.0100 -0.0014 -0.0033 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 0.0131 0.0050 -0.0011 0.0071 </span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.0419 -0.0199 0.0026 -0.0765 -0.0707</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7668 4.7695</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_A1 1.7447 0.4047 3.0848</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4525 0.1620 0.7431</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.2423 0.4560 2.0285</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.0390 0.7601 3.3180</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3069 1.1947</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 1.886 1.668 2.104</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 93.770115 9.115e+01 96.39447</span> +<span class="r-out co"><span class="r-pr">#></span> k_A1 0.002993 5.005e-04 0.01789</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_A1 0.276720 2.034e-01 0.36443</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.075467 2.503e-02 0.22753</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.029516 4.867e-03 0.17902</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.474353 2.949e-01 0.66073</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> +<span class="r-out co"><span class="r-pr">#></span> ff</span> +<span class="r-out co"><span class="r-pr">#></span> parent_A1 0.2767</span> +<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.7233</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_k1 DT50_k2</span> +<span class="r-out co"><span class="r-pr">#></span> parent 14.56 58.26 17.54 9.185 23.48</span> +<span class="r-out co"><span class="r-pr">#></span> A1 231.62 769.41 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> ds name time observed predicted residual std standardized</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 0 97.2 95.78623 1.41377 1.886 0.749758</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 0 96.4 95.78623 0.61377 1.886 0.325498</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 3 71.1 71.34666 -0.24666 1.886 -0.130812</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 3 69.2 71.34666 -2.14666 1.886 -1.138429</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 6 58.1 56.49768 1.60232 1.886 0.849749</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 6 56.6 56.49768 0.10232 1.886 0.054262</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 10 44.4 44.53511 -0.13511 1.886 -0.071650</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 10 43.4 44.53511 -1.13511 1.886 -0.601974</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 20 33.3 29.77451 3.52549 1.886 1.869656</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 20 29.2 29.77451 -0.57451 1.886 -0.304675</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 34 17.6 19.32540 -1.72540 1.886 -0.915023</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 34 18.0 19.32540 -1.32540 1.886 -0.702894</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 55 10.5 10.42781 0.07219 1.886 0.038282</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 55 9.3 10.42781 -1.12781 1.886 -0.598107</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 90 4.5 3.74190 0.75810 1.886 0.402037</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 90 4.7 3.74190 0.95810 1.886 0.508102</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 112 3.0 1.96485 1.03515 1.886 0.548966</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 112 3.4 1.96485 1.43515 1.886 0.761096</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 132 2.3 1.09395 1.20605 1.886 0.639596</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 parent 132 2.7 1.09395 1.60605 1.886 0.851726</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 3 4.3 4.72702 -0.42702 1.886 -0.226458</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 3 4.6 4.72702 -0.12702 1.886 -0.067361</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 6 7.0 7.51314 -0.51314 1.886 -0.272128</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 6 7.2 7.51314 -0.31314 1.886 -0.166063</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 10 8.2 9.63719 -1.43719 1.886 -0.762179</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 10 8.0 9.63719 -1.63719 1.886 -0.868244</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 20 11.0 11.84931 -0.84931 1.886 -0.450409</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 20 13.7 11.84931 1.85069 1.886 0.981468</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 34 11.5 12.82336 -1.32336 1.886 -0.701808</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 34 12.7 12.82336 -0.12336 1.886 -0.065418</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 55 14.9 12.89456 2.00544 1.886 1.063533</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 55 14.5 12.89456 1.60544 1.886 0.851403</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 90 12.1 11.55919 0.54081 1.886 0.286806</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 90 12.3 11.55919 0.74081 1.886 0.392871</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 112 9.9 10.42334 -0.52334 1.886 -0.277539</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 112 10.2 10.42334 -0.22334 1.886 -0.118442</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 132 8.8 9.37987 -0.57987 1.886 -0.307519</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 6 A1 132 7.8 9.37987 -1.57987 1.886 -0.837844</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 0 93.6 90.95702 2.64298 1.886 1.401639</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 0 92.3 90.95702 1.34298 1.886 0.712217</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 3 87.0 84.77506 2.22494 1.886 1.179942</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 3 82.2 84.77506 -2.57506 1.886 -1.365616</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 7 74.0 77.60962 -3.60962 1.886 -1.914268</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 7 73.9 77.60962 -3.70962 1.886 -1.967301</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 14 64.2 67.50646 -3.30646 1.886 -1.753499</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 14 69.5 67.50646 1.99354 1.886 1.057221</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 30 54.0 52.48909 1.51091 1.886 0.801271</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 30 54.6 52.48909 2.11091 1.886 1.119465</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 60 41.1 39.54372 1.55628 1.886 0.825335</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 60 38.4 39.54372 -1.14372 1.886 -0.606542</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 90 32.5 33.87968 -1.37968 1.886 -0.731676</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 90 35.5 33.87968 1.62032 1.886 0.859298</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 120 28.1 30.41071 -2.31071 1.886 -1.225427</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 120 29.0 30.41071 -1.41071 1.886 -0.748135</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 180 26.5 25.36386 1.13614 1.886 0.602524</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 parent 180 27.6 25.36386 2.23614 1.886 1.185881</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 3 3.9 2.74863 1.15137 1.886 0.610600</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 3 3.1 2.74863 0.35137 1.886 0.186341</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 7 6.9 5.92686 0.97314 1.886 0.516081</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 7 6.6 5.92686 0.67314 1.886 0.356983</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 14 10.4 10.38800 0.01200 1.886 0.006362</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 14 8.3 10.38800 -2.08800 1.886 -1.107320</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 30 14.4 16.93529 -2.53529 1.886 -1.344524</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 30 13.7 16.93529 -3.23529 1.886 -1.715751</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 60 22.1 22.33044 -0.23044 1.886 -0.122209</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 60 22.3 22.33044 -0.03044 1.886 -0.016144</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 90 27.5 24.42300 3.07700 1.886 1.631809</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 90 25.4 24.42300 0.97700 1.886 0.518127</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 120 28.0 25.51140 2.48860 1.886 1.319768</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 120 26.6 25.51140 1.08860 1.886 0.577313</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 180 25.8 26.80282 -1.00282 1.886 -0.531818</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 7 A1 180 25.3 26.80282 -1.50282 1.886 -0.796981</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 0 91.9 91.08733 0.81267 1.886 0.430980</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 0 90.8 91.08733 -0.28733 1.886 -0.152377</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 1 64.9 67.55332 -2.65332 1.886 -1.407123</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 1 66.2 67.55332 -1.35332 1.886 -0.717701</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 3 43.5 41.65811 1.84189 1.886 0.976800</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 3 44.1 41.65811 2.44189 1.886 1.294994</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 8 18.3 19.65773 -1.35773 1.886 -0.720038</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 8 18.1 19.65773 -1.55773 1.886 -0.826103</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 14 10.2 10.65118 -0.45118 1.886 -0.239269</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 14 10.8 10.65118 0.14882 1.886 0.078925</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 27 4.9 3.11694 1.78306 1.886 0.945601</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 27 3.3 3.11694 0.18306 1.886 0.097082</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 48 1.6 0.43165 1.16835 1.886 0.619603</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 48 1.5 0.43165 1.06835 1.886 0.566570</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 70 1.1 0.05441 1.04559 1.886 0.554503</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 parent 70 0.9 0.05441 0.84559 1.886 0.448438</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 1 9.6 7.66431 1.93569 1.886 1.026546</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 1 7.7 7.66431 0.03569 1.886 0.018930</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 3 15.0 15.57948 -0.57948 1.886 -0.307311</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 3 15.1 15.57948 -0.47948 1.886 -0.254279</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 8 21.2 20.38988 0.81012 1.886 0.429625</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 8 21.1 20.38988 0.71012 1.886 0.376593</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 14 19.7 20.16439 -0.46439 1.886 -0.246276</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 14 18.9 20.16439 -1.26439 1.886 -0.670535</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 27 17.5 16.40918 1.09082 1.886 0.578489</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 27 15.9 16.40918 -0.50918 1.886 -0.270030</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 48 9.5 10.12011 -0.62011 1.886 -0.328861</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 48 9.8 10.12011 -0.32011 1.886 -0.169764</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 70 6.2 5.79080 0.40920 1.886 0.217011</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 8 A1 70 6.1 5.79080 0.30920 1.886 0.163979</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 0 99.8 97.38786 2.41214 1.886 1.279218</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 0 98.3 97.38786 0.91214 1.886 0.483731</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 1 77.1 79.25431 -2.15431 1.886 -1.142481</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 1 77.2 79.25431 -2.05431 1.886 -1.089449</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 3 59.0 55.69866 3.30134 1.886 1.750781</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 3 58.1 55.69866 2.40134 1.886 1.273489</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 8 27.4 31.64893 -4.24893 1.886 -2.253314</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 8 29.2 31.64893 -2.44893 1.886 -1.298729</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 14 19.1 22.57316 -3.47316 1.886 -1.841901</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 14 29.6 22.57316 7.02684 1.886 3.726507</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 27 10.1 14.11345 -4.01345 1.886 -2.128430</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 27 18.2 14.11345 4.08655 1.886 2.167199</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 48 4.5 6.95586 -2.45586 1.886 -1.302400</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 48 9.1 6.95586 2.14414 1.886 1.137093</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 70 2.3 3.31753 -1.01753 1.886 -0.539619</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 70 2.9 3.31753 -0.41753 1.886 -0.221424</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 91 2.0 1.63642 0.36358 1.886 0.192816</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 91 1.8 1.63642 0.16358 1.886 0.086751</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 120 2.0 0.61667 1.38333 1.886 0.733614</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 parent 120 2.2 0.61667 1.58333 1.886 0.839679</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 1 4.2 3.67247 0.52753 1.886 0.279763</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 1 3.9 3.67247 0.22753 1.886 0.120666</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 3 7.4 8.36240 -0.96240 1.886 -0.510385</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 3 7.9 8.36240 -0.46240 1.886 -0.245223</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 8 14.5 12.80590 1.69410 1.886 0.898422</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 8 13.7 12.80590 0.89410 1.886 0.474162</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 14 14.2 13.99625 0.20375 1.886 0.108053</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 14 12.2 13.99625 -1.79625 1.886 -0.952596</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 27 13.7 14.22730 -0.52730 1.886 -0.279641</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 27 13.2 14.22730 -1.02730 1.886 -0.544803</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 48 13.6 13.33713 0.26287 1.886 0.139406</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 48 15.4 13.33713 2.06287 1.886 1.093991</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 70 10.4 11.84008 -1.44008 1.886 -0.763708</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 70 11.6 11.84008 -0.24008 1.886 -0.127318</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 91 10.0 10.30732 -0.30732 1.886 -0.162980</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 91 9.5 10.30732 -0.80732 1.886 -0.428142</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 120 9.1 8.33981 0.76019 1.886 0.403149</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 9 A1 120 9.0 8.33981 0.66019 1.886 0.350117</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 0 96.1 93.70349 2.39651 1.886 1.270926</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 0 94.3 93.70349 0.59651 1.886 0.316342</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 8 73.9 77.86253 -3.96253 1.886 -2.101429</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 8 73.9 77.86253 -3.96253 1.886 -2.101429</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 14 69.4 70.18665 -0.78665 1.886 -0.417182</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 14 73.1 70.18665 2.91335 1.886 1.545019</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 21 65.6 64.03245 1.56755 1.886 0.831308</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 21 65.3 64.03245 1.26755 1.886 0.672210</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 41 55.9 54.71491 1.18509 1.886 0.628480</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 41 54.4 54.71491 -0.31491 1.886 -0.167007</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 63 47.0 49.63436 -2.63436 1.886 -1.397065</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 63 49.3 49.63436 -0.33436 1.886 -0.177319</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 91 44.7 45.08853 -0.38853 1.886 -0.206049</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 91 46.7 45.08853 1.61147 1.886 0.854600</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 120 42.1 41.07653 1.02347 1.886 0.542772</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 parent 120 41.3 41.07653 0.22347 1.886 0.118513</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 8 3.3 4.08295 -0.78295 1.886 -0.415218</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 8 3.4 4.08295 -0.68295 1.886 -0.362186</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 14 3.9 6.04367 -2.14367 1.886 -1.136841</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 14 2.9 6.04367 -3.14367 1.886 -1.667165</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 21 6.4 7.59693 -1.19693 1.886 -0.634761</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 21 7.2 7.59693 -0.39693 1.886 -0.210502</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 41 9.1 9.86436 -0.76436 1.886 -0.405361</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 41 8.5 9.86436 -1.36436 1.886 -0.723555</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 63 11.7 10.99397 0.70603 1.886 0.374425</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 63 12.0 10.99397 1.00603 1.886 0.533522</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 91 13.3 11.91274 1.38726 1.886 0.735696</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 91 13.2 11.91274 1.28726 1.886 0.682663</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 120 14.3 12.66519 1.63481 1.886 0.866981</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 120 12.1 12.66519 -0.56519 1.886 -0.299733</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># The following takes about 6 minutes</span></span></span> +<span class="r-in"><span><span class="co">#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span></span></span> +<span class="r-in"><span><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co">#saemix::compare.saemix(list(</span></span></span> +<span class="r-in"><span><span class="co"># f_saem_dfop_sfo$so,</span></span></span> +<span class="r-in"><span><span class="co"># f_saem_dfop_sfo_deSolve$so))</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># If the model supports it, we can also use eigenvalue based solutions, which</span></span></span> +<span class="r-in"><span><span class="co"># take a similar amount of time</span></span></span> +<span class="r-in"><span><span class="co">#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",</span></span></span> +<span class="r-in"><span><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -309,7 +703,7 @@ using <a href="mmkin.html">mmkin</a>.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/reference/set_nd_nq.html b/docs/dev/reference/set_nd_nq.html new file mode 100644 index 00000000..26a28339 --- /dev/null +++ b/docs/dev/reference/set_nd_nq.html @@ -0,0 +1,258 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta 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href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Set non-detects and unquantified values in residue series without replicates — set_nd_nq"><meta property="og:description" content="This function automates replacing unquantified values in residue time and +depth series. For time series, the function performs part of the residue +processing proposed in the FOCUS kinetics guidance for parent compounds +and metabolites. For two-dimensional residue series over time and depth, +it automates the proposal of Boesten et al (2015)."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Set non-detects and unquantified values in residue series without replicates</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/set_nd_nq.R" class="external-link"><code>R/set_nd_nq.R</code></a></small> + <div class="hidden name"><code>set_nd_nq.Rd</code></div> + </div> + + <div class="ref-description"> + <p>This function automates replacing unquantified values in residue time and +depth series. For time series, the function performs part of the residue +processing proposed in the FOCUS kinetics guidance for parent compounds +and metabolites. For two-dimensional residue series over time and depth, +it automates the proposal of Boesten et al (2015).</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">res_raw</span>, <span class="va">lod</span>, loq <span class="op">=</span> <span class="cn">NA</span>, time_zero_presence <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span> +<span></span> +<span><span class="fu">set_nd_nq_focus</span><span class="op">(</span></span> +<span> <span class="va">res_raw</span>,</span> +<span> <span class="va">lod</span>,</span> +<span> loq <span class="op">=</span> <span class="cn">NA</span>,</span> +<span> set_first_sample_nd <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> first_sample_nd_value <span class="op">=</span> <span class="fl">0</span>,</span> +<span> ignore_below_loq_after_first_nd <span class="op">=</span> <span class="cn">TRUE</span></span> +<span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>res_raw</dt> +<dd><p>Character vector of a residue time series, or matrix of +residue values with rows representing depth profiles for a specific sampling +time, and columns representing time series of residues at the same depth. +Values below the limit of detection (lod) have to be coded as "nd", values +between the limit of detection and the limit of quantification, if any, have +to be coded as "nq". Samples not analysed have to be coded as "na". All +values that are not "na", "nd" or "nq" have to be coercible to numeric</p></dd> + + +<dt>lod</dt> +<dd><p>Limit of detection (numeric)</p></dd> + + +<dt>loq</dt> +<dd><p>Limit of quantification(numeric). Must be specified if the FOCUS rule to +stop after the first non-detection is to be applied</p></dd> + + +<dt>time_zero_presence</dt> +<dd><p>Do we assume that residues occur at time zero? +This only affects samples from the first sampling time that have been +reported as "nd" (not detected).</p></dd> + + +<dt>set_first_sample_nd</dt> +<dd><p>Should the first sample be set to "first_sample_nd_value" +in case it is a non-detection?</p></dd> + + +<dt>first_sample_nd_value</dt> +<dd><p>Value to be used for the first sample if it is a non-detection</p></dd> + + +<dt>ignore_below_loq_after_first_nd</dt> +<dd><p>Should we ignore values below the LOQ after the first +non-detection that occurs after the quantified values?</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>A numeric vector, if a vector was supplied, or a numeric matrix otherwise</p> + </div> + <div id="functions"> + <h2>Functions</h2> + +<ul><li><p><code>set_nd_nq_focus()</code>: Set non-detects in residue time series according to FOCUS rules</p></li> +</ul></div> + <div id="references"> + <h2>References</h2> + <p>Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H. +J. and Pol, J. W. (2015). Leaching of plant protection products and their +transformation products; Proposals for improving the assessment of leaching +to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra +Wageningen UR (University & Research centre)</p> +<p>FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># FOCUS (2014) p. 75/76 and 131/132</span></span></span> +<span class="r-in"><span><span class="va">parent_1</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">.12</span>, <span class="fl">.09</span>, <span class="fl">.05</span>, <span class="fl">.03</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">parent_1</span>, <span class="fl">0.02</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.12 0.09 0.05 0.03 0.01 NA NA NA NA NA</span> +<span class="r-in"><span><span class="va">parent_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">.12</span>, <span class="fl">.09</span>, <span class="fl">.05</span>, <span class="fl">.03</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="fl">.03</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">parent_2</span>, <span class="fl">0.02</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.03 0.01 NA NA</span> +<span class="r-in"><span><span class="fu">set_nd_nq_focus</span><span class="op">(</span><span class="va">parent_2</span>, <span class="fl">0.02</span>, loq <span class="op">=</span> <span class="fl">0.05</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.12 0.09 0.05 0.03 0.01 NA NA NA NA NA</span> +<span class="r-in"><span><span class="va">parent_3</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">.12</span>, <span class="fl">.09</span>, <span class="fl">.05</span>, <span class="fl">.03</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="fl">.06</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">parent_3</span>, <span class="fl">0.02</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01 NA NA</span> +<span class="r-in"><span><span class="fu">set_nd_nq_focus</span><span class="op">(</span><span class="va">parent_3</span>, <span class="fl">0.02</span>, loq <span class="op">=</span> <span class="fl">0.05</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01 NA NA</span> +<span class="r-in"><span><span class="va">metabolite</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>, <span class="fl">0.03</span>, <span class="fl">0.06</span>, <span class="fl">0.10</span>, <span class="fl">0.11</span>, <span class="fl">0.10</span>, <span class="fl">0.09</span>, <span class="fl">0.05</span>, <span class="fl">0.03</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">metabolite</span>, <span class="fl">0.02</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] NA NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01 NA</span> +<span class="r-in"><span><span class="fu">set_nd_nq_focus</span><span class="op">(</span><span class="va">metabolite</span>, <span class="fl">0.02</span>, <span class="fl">0.05</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.00 NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01 NA</span> +<span class="r-in"><span><span class="co">#</span></span></span> +<span class="r-in"><span><span class="co"># Boesten et al. (2015), p. 57/58</span></span></span> +<span class="r-in"><span><span class="va">table_8</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">4</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fl">10</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nq"</span>, <span class="fl">2</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">2</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fl">10</span>, <span class="fl">10</span>, <span class="fl">10</span>, <span class="st">"nq"</span>, <span class="st">"nd"</span>, <span class="st">"nd"</span>,</span></span> +<span class="r-in"><span> <span class="st">"nq"</span>, <span class="fl">10</span>, <span class="st">"nq"</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">3</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="st">"nd"</span>, <span class="st">"nq"</span>, <span class="st">"nq"</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">3</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">6</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">6</span><span class="op">)</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> ncol <span class="op">=</span> <span class="fl">6</span>, byrow <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">table_8</span>, <span class="fl">0.5</span>, <span class="fl">1.5</span>, time_zero_presence <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [,1] [,2] [,3] [,4] [,5] [,6]</span> +<span class="r-out co"><span class="r-pr">#></span> [1,] 10.00 10.00 0.25 0.25 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [2,] 10.00 10.00 1.00 1.00 0.25 NA</span> +<span class="r-out co"><span class="r-pr">#></span> [3,] 10.00 10.00 10.00 1.00 0.25 NA</span> +<span class="r-out co"><span class="r-pr">#></span> [4,] 1.00 10.00 1.00 0.25 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [5,] 0.25 1.00 1.00 0.25 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [6,] NA 0.25 0.25 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [7,] NA NA NA NA NA NA</span> +<span class="r-in"><span><span class="va">table_10</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html" class="external-link">matrix</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">10</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">4</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fl">10</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">4</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fl">10</span>, <span class="fl">10</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">3</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="st">"nd"</span>, <span class="fl">10</span>, <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">4</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="st">"nd"</span>, <span class="fl">18</span><span class="op">)</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> ncol <span class="op">=</span> <span class="fl">6</span>, byrow <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">set_nd_nq</span><span class="op">(</span><span class="va">table_10</span>, <span class="fl">0.5</span>, time_zero_presence <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [,1] [,2] [,3] [,4] [,5] [,6]</span> +<span class="r-out co"><span class="r-pr">#></span> [1,] 10.00 10.00 0.25 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [2,] 10.00 10.00 0.25 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [3,] 10.00 10.00 10.00 0.25 NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [4,] 0.25 10.00 0.25 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [5,] NA 0.25 NA NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [6,] NA NA NA NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> [7,] NA NA NA NA NA NA</span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/status.html b/docs/dev/reference/status.html new file mode 100644 index 00000000..778446b3 --- /dev/null +++ b/docs/dev/reference/status.html @@ -0,0 +1,171 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Method to get status information for fit array objects — status • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" 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content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Method to get status information for fit array objects</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/status.R" class="external-link"><code>R/status.R</code></a></small> + <div class="hidden name"><code>status.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Method to get status information for fit array objects</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">status</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">status</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for status.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mhmkin</span></span> +<span><span class="fu">status</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for status.mhmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The object to investigate</p></dd> + + +<dt>...</dt> +<dd><p>For potential future extensions</p></dd> + + +<dt>x</dt> +<dd><p>The object to be printed</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>An object with the same dimensions as the fit array +suitable printing method.</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS B"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">status</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS B</span> +<span class="r-out co"><span class="r-pr">#></span> SFO OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/summary.mkinfit.html b/docs/dev/reference/summary.mkinfit.html index 494731e9..c58fffbb 100644 --- a/docs/dev/reference/summary.mkinfit.html +++ b/docs/dev/reference/summary.mkinfit.html @@ -1,71 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uncertainty statistics, the chi2 error levels calculated according to FOCUS guidance (2006) as defined therein, formation fractions, DT50 values and optionally the data, consisting of observed, predicted and residual -values." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +values."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script 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href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -102,6 +45,9 @@ values." /> <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -116,34 +62,27 @@ values." /> <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Summary method for class "mkinfit"</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/summary.mkinfit.R'><code>R/summary.mkinfit.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/summary.mkinfit.R" class="external-link"><code>R/summary.mkinfit.R</code></a></small> <div class="hidden name"><code>summary.mkinfit.Rd</code></div> </div> @@ -155,187 +94,217 @@ and optionally the data, consisting of observed, predicted and residual values.</p> </div> - <pre class="usage"><span class='co'># S3 method for mkinfit</span> -<span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>object</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span>, distimes <span class='op'>=</span> <span class='cn'>TRUE</span>, alpha <span class='op'>=</span> <span class='fl'>0.05</span>, <span class='va'>...</span><span class='op'>)</span> - -<span class='co'># S3 method for summary.mkinfit</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, digits <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"digits"</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>3</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>object</th> - <td><p>an object of class <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> - </tr> - <tr> - <th>data</th> - <td><p>logical, indicating whether the data should be included in the -summary.</p></td> - </tr> - <tr> - <th>distimes</th> - <td><p>logical, indicating whether DT50 and DT90 values should be -included.</p></td> - </tr> - <tr> - <th>alpha</th> - <td><p>error level for confidence interval estimation from t -distribution</p></td> - </tr> - <tr> - <th>...</th> - <td><p>optional arguments passed to methods like <code>print</code>.</p></td> - </tr> - <tr> - <th>x</th> - <td><p>an object of class <code>summary.mkinfit</code>.</p></td> - </tr> - <tr> - <th>digits</th> - <td><p>Number of digits to use for printing</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>The summary function returns a list with components, among others</p> -<dt>version, Rversion</dt><dd><p>The mkin and R versions used</p></dd> -<dt>date.fit, date.summary</dt><dd><p>The dates where the fit and the summary were + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">TRUE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, alpha <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.mkinfit</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>an object of class <code><a href="mkinfit.html">mkinfit</a></code>.</p></dd> + + +<dt>data</dt> +<dd><p>logical, indicating whether the data should be included in the +summary.</p></dd> + + +<dt>distimes</dt> +<dd><p>logical, indicating whether DT50 and DT90 values should be +included.</p></dd> + + +<dt>alpha</dt> +<dd><p>error level for confidence interval estimation from t +distribution</p></dd> + + +<dt>...</dt> +<dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + +<dt>x</dt> +<dd><p>an object of class <code>summary.mkinfit</code>.</p></dd> + + +<dt>digits</dt> +<dd><p>Number of digits to use for printing</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>The summary function returns a list with components, among others</p> +<dl><dt>version, Rversion</dt> +<dd><p>The mkin and R versions used</p></dd> + +<dt>date.fit, date.summary</dt> +<dd><p>The dates where the fit and the summary were produced</p></dd> -<dt>diffs</dt><dd><p>The differential equations used in the model</p></dd> -<dt>use_of_ff</dt><dd><p>Was maximum or minimum use made of formation fractions</p></dd> -<dt>bpar</dt><dd><p>Optimised and backtransformed + +<dt>diffs</dt> +<dd><p>The differential equations used in the model</p></dd> + +<dt>use_of_ff</dt> +<dd><p>Was maximum or minimum use made of formation fractions</p></dd> + +<dt>bpar</dt> +<dd><p>Optimised and backtransformed parameters</p></dd> -<dt>data</dt><dd><p>The data (see Description above).</p></dd> -<dt>start</dt><dd><p>The starting values and bounds, if applicable, for optimised + +<dt>data</dt> +<dd><p>The data (see Description above).</p></dd> + +<dt>start</dt> +<dd><p>The starting values and bounds, if applicable, for optimised parameters.</p></dd> -<dt>fixed</dt><dd><p>The values of fixed parameters.</p></dd> -<dt>errmin </dt><dd><p>The chi2 error levels for + +<dt>fixed</dt> +<dd><p>The values of fixed parameters.</p></dd> + +<dt>errmin </dt> +<dd><p>The chi2 error levels for each observed variable.</p></dd> -<dt>bparms.ode</dt><dd><p>All backtransformed ODE + +<dt>bparms.ode</dt> +<dd><p>All backtransformed ODE parameters, for use as starting parameters for related models.</p></dd> -<dt>errparms</dt><dd><p>Error model parameters.</p></dd> -<dt>ff</dt><dd><p>The estimated formation fractions derived from the fitted + +<dt>errparms</dt> +<dd><p>Error model parameters.</p></dd> + +<dt>ff</dt> +<dd><p>The estimated formation fractions derived from the fitted model.</p></dd> -<dt>distimes</dt><dd><p>The DT50 and DT90 values for each observed variable.</p></dd> -<dt>SFORB</dt><dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> -The print method is called for its side effect, i.e. printing the summary. - <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2> +<dt>distimes</dt> +<dd><p>The DT50 and DT90 values for each observed variable.</p></dd> + +<dt>SFORB</dt> +<dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> - <p>FOCUS (2006) “Guidance Document on Estimating Persistence +</dl><p>The print method is called for its side effect, i.e. printing the summary.</p> + </div> + <div id="references"> + <h2>References</h2> + <p>FOCUS (2006) “Guidance Document on Estimating Persistence and Degradation Kinetics from Environmental Fate Studies on Pesticides in -EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, +EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, -<a href='http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics'>http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a></p> - <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> - +<a href="http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics" class="external-link">http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a></p> + </div> + <div id="author"> + <h2>Author</h2> <p>Johannes Ranke</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> - <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span>, <span class='va'>FOCUS_2006_A</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> mkin version used for fitting: 1.0.3.9000 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Feb 15 17:13:09 2021 -#> Date of summary: Mon Feb 15 17:13:09 2021 -#> -#> Equations: -#> d_parent/dt = - k_parent * parent -#> -#> Model predictions using solution type analytical -#> -#> Fitted using 131 model solutions performed in 0.027 s -#> -#> Error model: Constant variance -#> -#> Error model algorithm: OLS -#> -#> Starting values for parameters to be optimised: -#> value type -#> parent_0 101.24 state -#> k_parent 0.10 deparm -#> -#> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 101.240000 -Inf Inf -#> log_k_parent -2.302585 -Inf Inf -#> -#> Fixed parameter values: -#> None -#> -#> Results: -#> -#> AIC BIC logLik -#> 55.28197 55.5203 -24.64099 -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> Estimate Std. Error Lower Upper -#> parent_0 109.200 3.70400 99.630 118.700 -#> log_k_parent -3.291 0.09176 -3.527 -3.055 -#> sigma 5.266 1.31600 1.882 8.649 -#> -#> Parameter correlation: -#> parent_0 log_k_parent sigma -#> parent_0 1.000e+00 5.428e-01 1.642e-07 -#> log_k_parent 5.428e-01 1.000e+00 2.507e-07 -#> sigma 1.642e-07 2.507e-07 1.000e+00 -#> -#> Backtransformed parameters: -#> Confidence intervals for internally transformed parameters are asymmetric. -#> t-test (unrealistically) based on the assumption of normal distribution -#> for estimators of untransformed parameters. -#> Estimate t value Pr(>t) Lower Upper -#> parent_0 109.20000 29.47 4.218e-07 99.6300 118.70000 -#> k_parent 0.03722 10.90 5.650e-05 0.0294 0.04712 -#> sigma 5.26600 4.00 5.162e-03 1.8820 8.64900 -#> -#> FOCUS Chi2 error levels in percent: -#> err.min n.optim df -#> All data 8.385 2 6 -#> parent 8.385 2 6 -#> -#> Estimated disappearance times: -#> DT50 DT90 -#> parent 18.62 61.87 -#> -#> Data: -#> time variable observed predicted residual -#> 0 parent 101.24 109.153 -7.9132 -#> 3 parent 99.27 97.622 1.6484 -#> 7 parent 90.11 84.119 5.9913 -#> 14 parent 72.19 64.826 7.3641 -#> 30 parent 29.71 35.738 -6.0283 -#> 62 parent 5.98 10.862 -4.8818 -#> 90 parent 1.54 3.831 -2.2911 -#> 118 parent 0.39 1.351 -0.9613</div><div class='input'> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_A</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:30:48 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:30:48 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - k_parent * parent</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 131 model solutions performed in 0.028 s</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Error model algorithm: OLS </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for parameters to be optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value type</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 101.24 state</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.10 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Starting values for the transformed parameters actually optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 101.240000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -2.302585 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 55.28197 55.5203 -24.64099</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised, transformed parameters with symmetric confidence intervals:</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 109.200 3.70400 99.630 118.700</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -3.291 0.09176 -3.527 -3.055</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 5.266 1.31600 1.882 8.649</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_parent sigma</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 5.428e-01 1.642e-07</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent 5.428e-01 1.000e+00 2.507e-07</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.642e-07 2.507e-07 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> +<span class="r-out co"><span class="r-pr">#></span> t-test (unrealistically) based on the assumption of normal distribution</span> +<span class="r-out co"><span class="r-pr">#></span> for estimators of untransformed parameters.</span> +<span class="r-out co"><span class="r-pr">#></span> Estimate t value Pr(>t) Lower Upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 109.20000 29.47 4.218e-07 99.6300 118.70000</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.03722 10.90 5.650e-05 0.0294 0.04712</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 5.26600 4.00 5.162e-03 1.8820 8.64900</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> FOCUS Chi2 error levels in percent:</span> +<span class="r-out co"><span class="r-pr">#></span> err.min n.optim df</span> +<span class="r-out co"><span class="r-pr">#></span> All data 8.385 2 6</span> +<span class="r-out co"><span class="r-pr">#></span> parent 8.385 2 6</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> +<span class="r-out co"><span class="r-pr">#></span> parent 18.62 61.87</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> time variable observed predicted residual</span> +<span class="r-out co"><span class="r-pr">#></span> 0 parent 101.24 109.153 -7.9132</span> +<span class="r-out co"><span class="r-pr">#></span> 3 parent 99.27 97.622 1.6484</span> +<span class="r-out co"><span class="r-pr">#></span> 7 parent 90.11 84.119 5.9913</span> +<span class="r-out co"><span class="r-pr">#></span> 14 parent 72.19 64.826 7.3641</span> +<span class="r-out co"><span class="r-pr">#></span> 30 parent 29.71 35.738 -6.0283</span> +<span class="r-out co"><span class="r-pr">#></span> 62 parent 5.98 10.862 -4.8818</span> +<span class="r-out co"><span class="r-pr">#></span> 90 parent 1.54 3.831 -2.2911</span> +<span class="r-out co"><span class="r-pr">#></span> 118 parent 0.39 1.351 -0.9613</span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div 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overview of ill-defined parameters calculated by illparms."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/multistart.html">Short demo of the multistart method</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Summary method for class "mmkin"</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/summary.mmkin.R" class="external-link"><code>R/summary.mmkin.R</code></a></small> + <div class="hidden name"><code>summary.mmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Shows status information on the <a href="mkinfit.html">mkinfit</a> objects contained in the object +and gives an overview of ill-defined parameters calculated by <a href="illparms.html">illparms</a>.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>an object of class <a href="mmkin.html">mmkin</a></p></dd> + + +<dt>conf.level</dt> +<dd><p>confidence level for testing parameters</p></dd> + + +<dt>...</dt> +<dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + +<dt>x</dt> +<dd><p>an object of class <code>summary.mmkin</code>.</p></dd> + + +<dt>digits</dt> +<dd><p>number of digits to use for printing</p></dd> + +</dl></div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS C"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 1.032 s</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Status:</span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Ill-defined parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC parent_0, alpha, beta, sigma </span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/dev/reference/summary.nlme.mmkin.html b/docs/dev/reference/summary.nlme.mmkin.html index b2f6624a..067efcfe 100644 --- a/docs/dev/reference/summary.nlme.mmkin.html +++ b/docs/dev/reference/summary.nlme.mmkin.html @@ -1,71 +1,16 @@ -<!-- Generated by pkgdown: do not edit by hand --> <!DOCTYPE html> -<html lang="en"> - <head> - <meta charset="utf-8"> -<meta http-equiv="X-UA-Compatible" content="IE=edge"> -<meta name="viewport" content="width=device-width, initial-scale=1.0"> - -<title>Summary method for class "nlme.mmkin" — summary.nlme.mmkin • mkin</title> - - -<!-- jquery --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script> -<!-- Bootstrap --> - -<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous" /> - -<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" 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href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Summary method for class " nlme.mmkin summary.nlme.mmkin><meta property="og:description" content="Lists model equations, initial parameter values, optimised parameters for fixed effects (population), random effects (deviations from the population mean) and residual error model, as well as the resulting endpoints such as formation fractions and DT50 values. Optionally -(default is FALSE), the data are listed in full." /> - - -<meta name="robots" content="noindex"> - -<!-- mathjax --> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> -<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> - -<!--[if lt IE 9]> +(default is FALSE), the data are listed in full."><meta name="robots" content="noindex"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> -<![endif]--> - +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - - </head> - - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -76,23 +21,21 @@ endpoints such as formation fractions and DT50 values. Optionally </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.0.3.9000</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> + <ul class="nav navbar-nav"><li> <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> </a> - <ul class="dropdown-menu" role="menu"> - <li> + <ul class="dropdown-menu" role="menu"><li> <a href="../articles/mkin.html">Introduction to mkin</a> </li> <li> @@ -102,6 +45,9 @@ endpoints such as formation fractions and DT50 values. Optionally <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -116,34 +62,27 @@ endpoints such as formation fractions and DT50 values. Optionally <li> <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> </li> - </ul> -</li> + </ul></li> <li> <a href="../news/index.html">News</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/mkin/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Summary method for class "nlme.mmkin"</h1> - <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/summary.nlme.mmkin.R'><code>R/summary.nlme.mmkin.R</code></a></small> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/summary.nlme.mmkin.R" class="external-link"><code>R/summary.nlme.mmkin.R</code></a></small> <div class="hidden name"><code>summary.nlme.mmkin.Rd</code></div> </div> @@ -155,295 +94,320 @@ endpoints such as formation fractions and DT50 values. Optionally (default is FALSE), the data are listed in full.</p> </div> - <pre class="usage"><span class='co'># S3 method for nlme.mmkin</span> -<span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span> - <span class='va'>object</span>, - data <span class='op'>=</span> <span class='cn'>FALSE</span>, - verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, - distimes <span class='op'>=</span> <span class='cn'>TRUE</span>, - alpha <span class='op'>=</span> <span class='fl'>0.05</span>, - <span class='va'>...</span> -<span class='op'>)</span> - -<span class='co'># S3 method for summary.nlme.mmkin</span> -<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, digits <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"digits"</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>3</span><span class='op'>)</span>, verbose <span class='op'>=</span> <span class='va'>x</span><span class='op'>$</span><span class='va'>verbose</span>, <span class='va'>...</span><span class='op'>)</span></pre> - - <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> - <table class="ref-arguments"> - <colgroup><col class="name" /><col class="desc" /></colgroup> - <tr> - <th>object</th> - <td><p>an object of class <a href='nlme.mmkin.html'>nlme.mmkin</a></p></td> - </tr> - <tr> - <th>data</th> - <td><p>logical, indicating whether the full data should be included in -the summary.</p></td> - </tr> - <tr> - <th>verbose</th> - <td><p>Should the summary be verbose?</p></td> - </tr> - <tr> - <th>distimes</th> - <td><p>logical, indicating whether DT50 and DT90 values should be -included.</p></td> - </tr> - <tr> - <th>alpha</th> - <td><p>error level for confidence interval estimation from the t -distribution</p></td> - </tr> - <tr> - <th>...</th> - <td><p>optional arguments passed to methods like <code>print</code>.</p></td> - </tr> - <tr> - <th>x</th> - <td><p>an object of class summary.nlme.mmkin</p></td> - </tr> - <tr> - <th>digits</th> - <td><p>Number of digits to use for printing</p></td> - </tr> - </table> - - <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> - - <p>The summary function returns a list based on the <a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a> object + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for nlme.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> data <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> distimes <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> alpha <span class="op">=</span> <span class="fl">0.05</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.nlme.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="va">x</span><span class="op">$</span><span class="va">verbose</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>an object of class <a href="nlme.mmkin.html">nlme.mmkin</a></p></dd> + + +<dt>data</dt> +<dd><p>logical, indicating whether the full data should be included in +the summary.</p></dd> + + +<dt>verbose</dt> +<dd><p>Should the summary be verbose?</p></dd> + + +<dt>distimes</dt> +<dd><p>logical, indicating whether DT50 and DT90 values should be +included.</p></dd> + + +<dt>alpha</dt> +<dd><p>error level for confidence interval estimation from the t +distribution</p></dd> + + +<dt>...</dt> +<dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + +<dt>x</dt> +<dd><p>an object of class summary.nlme.mmkin</p></dd> + + +<dt>digits</dt> +<dd><p>Number of digits to use for printing</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>The summary function returns a list based on the <a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a> object obtained in the fit, with at least the following additional components</p> -<dt>nlmeversion, mkinversion, Rversion</dt><dd><p>The nlme, mkin and R versions used</p></dd> -<dt>date.fit, date.summary</dt><dd><p>The dates where the fit and the summary were +<dl><dt>nlmeversion, mkinversion, Rversion</dt> +<dd><p>The nlme, mkin and R versions used</p></dd> + +<dt>date.fit, date.summary</dt> +<dd><p>The dates where the fit and the summary were produced</p></dd> -<dt>diffs</dt><dd><p>The differential equations used in the degradation model</p></dd> -<dt>use_of_ff</dt><dd><p>Was maximum or minimum use made of formation fractions</p></dd> -<dt>data</dt><dd><p>The data</p></dd> -<dt>confint_trans</dt><dd><p>Transformed parameters as used in the optimisation, with confidence intervals</p></dd> -<dt>confint_back</dt><dd><p>Backtransformed parameters, with confidence intervals if available</p></dd> -<dt>ff</dt><dd><p>The estimated formation fractions derived from the fitted + +<dt>diffs</dt> +<dd><p>The differential equations used in the degradation model</p></dd> + +<dt>use_of_ff</dt> +<dd><p>Was maximum or minimum use made of formation fractions</p></dd> + +<dt>data</dt> +<dd><p>The data</p></dd> + +<dt>confint_trans</dt> +<dd><p>Transformed parameters as used in the optimisation, with confidence intervals</p></dd> + +<dt>confint_back</dt> +<dd><p>Backtransformed parameters, with confidence intervals if available</p></dd> + +<dt>ff</dt> +<dd><p>The estimated formation fractions derived from the fitted model.</p></dd> -<dt>distimes</dt><dd><p>The DT50 and DT90 values for each observed variable.</p></dd> -<dt>SFORB</dt><dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> -The print method is called for its side effect, i.e. printing the summary. - <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> +<dt>distimes</dt> +<dd><p>The DT50 and DT90 values for each observed variable.</p></dd> + +<dt>SFORB</dt> +<dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> +</dl><p>The print method is called for its side effect, i.e. printing the summary.</p> + </div> + <div id="author"> + <h2>Author</h2> <p>Johannes Ranke for the mkin specific parts José Pinheiro and Douglas Bates for the components inherited from nlme</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'> -<span class='co'># Generate five datasets following SFO kinetics</span> -<span class='va'>sampling_times</span> <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span><span class='op'>)</span> -<span class='va'>dt50_sfo_in_pop</span> <span class='op'><-</span> <span class='fl'>50</span> -<span class='va'>k_in_pop</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>2</span><span class='op'>)</span> <span class='op'>/</span> <span class='va'>dt50_sfo_in_pop</span> -<span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span><span class='op'>(</span><span class='fl'>1234</span><span class='op'>)</span> -<span class='va'>k_in</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/Lognormal.html'>rlnorm</a></span><span class='op'>(</span><span class='fl'>5</span>, <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='va'>k_in_pop</span><span class='op'>)</span>, <span class='fl'>0.5</span><span class='op'>)</span> -<span class='va'>SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> - -<span class='va'>pred_sfo</span> <span class='op'><-</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>k</span><span class='op'>)</span> <span class='op'>{</span> - <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>SFO</span>, - <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='va'>k</span><span class='op'>)</span>, - <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span><span class='op'>)</span>, - <span class='va'>sampling_times</span><span class='op'>)</span> -<span class='op'>}</span> - -<span class='va'>ds_sfo_mean</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>k_in</span>, <span class='va'>pred_sfo</span><span class='op'>)</span> -<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds_sfo_mean</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"ds"</span>, <span class='fl'>1</span><span class='op'>:</span><span class='fl'>5</span><span class='op'>)</span> - -<span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span><span class='op'>(</span><span class='fl'>12345</span><span class='op'>)</span> -<span class='va'>ds_sfo_syn</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>ds_sfo_mean</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>{</span> - <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>ds</span>, - sdfunc <span class='op'>=</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>sqrt</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>+</span> <span class='va'>value</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>*</span> <span class='fl'>0.07</span><span class='op'>^</span><span class='fl'>2</span><span class='op'>)</span>, - n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span> -<span class='op'>}</span><span class='op'>)</span> - -<span class='co'># Evaluate using mmkin and nlme</span> -<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://svn.r-project.org/R-packages/trunk/nlme/'>nlme</a></span><span class='op'>)</span> -<span class='va'>f_mmkin</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>ds_sfo_syn</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> -#> <span class='warning'>iteration limit reached without convergence (10)</span></div><div class='input'><span class='va'>f_nlme</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Iteration 4, LME step: nlminb() did not converge (code = 1). PORT message: false convergence (8)</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_nlme</span>, data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> nlme version used for fitting: 3.1.152 -#> mkin version used for pre-fitting: 1.0.3.9000 -#> R version used for fitting: 4.0.3 -#> Date of fit: Mon Feb 15 17:13:12 2021 -#> Date of summary: Mon Feb 15 17:13:12 2021 -#> -#> Equations: -#> d_parent/dt = - k_parent * parent -#> -#> Data: -#> 90 observations of 1 variable(s) grouped in 5 datasets -#> -#> Model predictions using solution type analytical -#> -#> Fitted in 0.544 s using 4 iterations -#> -#> Variance model: Two-component variance function -#> -#> Mean of starting values for individual parameters: -#> parent_0 log_k_parent -#> 101.569 -4.454 -#> -#> Fixed degradation parameter values: -#> None -#> -#> Results: -#> -#> AIC BIC logLik -#> 584.5 599.5 -286.2 -#> -#> Optimised, transformed parameters with symmetric confidence intervals: -#> lower est. upper -#> parent_0 99.371 101.592 103.814 -#> log_k_parent -4.973 -4.449 -3.926 -#> -#> Correlation: -#> prnt_0 -#> log_k_parent 0.051 -#> -#> Random effects: -#> Formula: list(parent_0 ~ 1, log_k_parent ~ 1) -#> Level: ds -#> Structure: Diagonal -#> parent_0 log_k_parent Residual -#> StdDev: 6.924e-05 0.5863 1 -#> -#> Variance function: -#> Structure: Constant plus proportion of variance covariate -#> Formula: ~fitted(.) -#> Parameter estimates: -#> const prop -#> 0.0001208853 0.0789968036 -#> -#> Backtransformed parameters with asymmetric confidence intervals: -#> lower est. upper -#> parent_0 99.370882 101.59243 103.81398 -#> k_parent 0.006923 0.01168 0.01972 -#> -#> Estimated disappearance times: -#> DT50 DT90 -#> parent 59.32 197.1 -#> -#> Data: -#> ds name time observed predicted residual std standardized -#> ds 1 parent 0 104.1 101.592 2.50757 8.0255 0.312451 -#> ds 1 parent 0 105.0 101.592 3.40757 8.0255 0.424594 -#> ds 1 parent 1 98.5 100.796 -2.29571 7.9625 -0.288313 -#> ds 1 parent 1 96.1 100.796 -4.69571 7.9625 -0.589725 -#> ds 1 parent 3 101.9 99.221 2.67904 7.8381 0.341796 -#> ds 1 parent 3 85.2 99.221 -14.02096 7.8381 -1.788812 -#> ds 1 parent 7 99.1 96.145 2.95512 7.5951 0.389081 -#> ds 1 parent 7 93.0 96.145 -3.14488 7.5951 -0.414065 -#> ds 1 parent 14 88.1 90.989 -2.88944 7.1879 -0.401987 -#> ds 1 parent 14 84.1 90.989 -6.88944 7.1879 -0.958480 -#> ds 1 parent 28 80.2 81.493 -1.29305 6.4377 -0.200857 -#> ds 1 parent 28 91.3 81.493 9.80695 6.4377 1.523364 -#> ds 1 parent 60 65.1 63.344 1.75642 5.0039 0.351008 -#> ds 1 parent 60 65.8 63.344 2.45642 5.0039 0.490898 -#> ds 1 parent 90 47.8 50.018 -2.21764 3.9512 -0.561252 -#> ds 1 parent 90 53.5 50.018 3.48236 3.9512 0.881335 -#> ds 1 parent 120 37.6 39.495 -1.89515 3.1200 -0.607423 -#> ds 1 parent 120 39.3 39.495 -0.19515 3.1200 -0.062549 -#> ds 2 parent 0 107.9 101.592 6.30757 8.0255 0.785943 -#> ds 2 parent 0 102.1 101.592 0.50757 8.0255 0.063245 -#> ds 2 parent 1 103.8 100.058 3.74159 7.9043 0.473361 -#> ds 2 parent 1 108.6 100.058 8.54159 7.9043 1.080626 -#> ds 2 parent 3 91.0 97.060 -6.05952 7.6674 -0.790297 -#> ds 2 parent 3 84.9 97.060 -12.15952 7.6674 -1.585874 -#> ds 2 parent 7 79.3 91.329 -12.02867 7.2147 -1.667251 -#> ds 2 parent 7 100.9 91.329 9.57133 7.2147 1.326647 -#> ds 2 parent 14 77.3 82.102 -4.80185 6.4858 -0.740366 -#> ds 2 parent 14 83.5 82.102 1.39815 6.4858 0.215571 -#> ds 2 parent 28 66.8 66.351 0.44945 5.2415 0.085748 -#> ds 2 parent 28 63.3 66.351 -3.05055 5.2415 -0.582002 -#> ds 2 parent 60 40.8 40.775 0.02474 3.2211 0.007679 -#> ds 2 parent 60 44.8 40.775 4.02474 3.2211 1.249485 -#> ds 2 parent 90 27.8 25.832 1.96762 2.0407 0.964198 -#> ds 2 parent 90 27.0 25.832 1.16762 2.0407 0.572171 -#> ds 2 parent 120 15.2 16.366 -1.16561 1.2928 -0.901595 -#> ds 2 parent 120 15.5 16.366 -0.86561 1.2928 -0.669547 -#> ds 3 parent 0 97.7 101.592 -3.89243 8.0255 -0.485009 -#> ds 3 parent 0 88.2 101.592 -13.39243 8.0255 -1.668739 -#> ds 3 parent 1 109.9 99.218 10.68196 7.8379 1.362858 -#> ds 3 parent 1 97.8 99.218 -1.41804 7.8379 -0.180921 -#> ds 3 parent 3 100.5 94.634 5.86555 7.4758 0.784603 -#> ds 3 parent 3 77.4 94.634 -17.23445 7.4758 -2.305360 -#> ds 3 parent 7 78.3 86.093 -7.79273 6.8011 -1.145813 -#> ds 3 parent 7 90.3 86.093 4.20727 6.8011 0.618620 -#> ds 3 parent 14 76.0 72.958 3.04222 5.7634 0.527848 -#> ds 3 parent 14 79.1 72.958 6.14222 5.7634 1.065722 -#> ds 3 parent 28 46.0 52.394 -6.39404 4.1390 -1.544842 -#> ds 3 parent 28 53.4 52.394 1.00596 4.1390 0.243046 -#> ds 3 parent 60 25.1 24.582 0.51786 1.9419 0.266676 -#> ds 3 parent 60 21.4 24.582 -3.18214 1.9419 -1.638664 -#> ds 3 parent 90 11.0 12.092 -1.09202 0.9552 -1.143199 -#> ds 3 parent 90 14.2 12.092 2.10798 0.9552 2.206776 -#> ds 3 parent 120 5.8 5.948 -0.14810 0.4699 -0.315178 -#> ds 3 parent 120 6.1 5.948 0.15190 0.4699 0.323282 -#> ds 4 parent 0 95.3 101.592 -6.29243 8.0255 -0.784057 -#> ds 4 parent 0 102.0 101.592 0.40757 8.0255 0.050784 -#> ds 4 parent 1 104.4 101.125 3.27549 7.9885 0.410025 -#> ds 4 parent 1 105.4 101.125 4.27549 7.9885 0.535205 -#> ds 4 parent 3 113.7 100.195 13.50487 7.9151 1.706218 -#> ds 4 parent 3 82.3 100.195 -17.89513 7.9151 -2.260886 -#> ds 4 parent 7 98.1 98.362 -0.26190 7.7703 -0.033706 -#> ds 4 parent 7 87.8 98.362 -10.56190 7.7703 -1.359270 -#> ds 4 parent 14 97.9 95.234 2.66590 7.5232 0.354357 -#> ds 4 parent 14 104.8 95.234 9.56590 7.5232 1.271521 -#> ds 4 parent 28 85.0 89.274 -4.27372 7.0523 -0.606001 -#> ds 4 parent 28 77.2 89.274 -12.07372 7.0523 -1.712017 -#> ds 4 parent 60 82.2 77.013 5.18661 6.0838 0.852526 -#> ds 4 parent 60 86.1 77.013 9.08661 6.0838 1.493571 -#> ds 4 parent 90 70.5 67.053 3.44692 5.2970 0.650733 -#> ds 4 parent 90 61.7 67.053 -5.35308 5.2970 -1.010591 -#> ds 4 parent 120 60.0 58.381 1.61905 4.6119 0.351058 -#> ds 4 parent 120 56.4 58.381 -1.98095 4.6119 -0.429530 -#> ds 5 parent 0 92.6 101.592 -8.99243 8.0255 -1.120485 -#> ds 5 parent 0 116.5 101.592 14.90757 8.0255 1.857531 -#> ds 5 parent 1 108.0 99.914 8.08560 7.8929 1.024413 -#> ds 5 parent 1 104.9 99.914 4.98560 7.8929 0.631655 -#> ds 5 parent 3 100.5 96.641 3.85898 7.6343 0.505477 -#> ds 5 parent 3 89.5 96.641 -7.14102 7.6343 -0.935382 -#> ds 5 parent 7 91.7 90.412 1.28752 7.1423 0.180267 -#> ds 5 parent 7 95.1 90.412 4.68752 7.1423 0.656304 -#> ds 5 parent 14 82.2 80.463 1.73715 6.3563 0.273295 -#> ds 5 parent 14 84.5 80.463 4.03715 6.3563 0.635141 -#> ds 5 parent 28 60.5 63.728 -3.22788 5.0343 -0.641178 -#> ds 5 parent 28 72.8 63.728 9.07212 5.0343 1.802062 -#> ds 5 parent 60 38.3 37.399 0.90061 2.9544 0.304835 -#> ds 5 parent 60 40.7 37.399 3.30061 2.9544 1.117174 -#> ds 5 parent 90 22.5 22.692 -0.19165 1.7926 -0.106913 -#> ds 5 parent 90 20.8 22.692 -1.89165 1.7926 -1.055273 -#> ds 5 parent 120 13.4 13.768 -0.36790 1.0876 -0.338259 -#> ds 5 parent 120 13.8 13.768 0.03210 1.0876 0.029517</div><div class='input'> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Generate five datasets following SFO kinetics</span></span></span> +<span class="r-in"><span><span class="va">sampling_times</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dt50_sfo_in_pop</span> <span class="op"><-</span> <span class="fl">50</span></span></span> +<span class="r-in"><span><span class="va">k_in_pop</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">2</span><span class="op">)</span> <span class="op">/</span> <span class="va">dt50_sfo_in_pop</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1234</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="va">k_in_pop</span><span class="op">)</span>, <span class="fl">0.5</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">pred_sfo</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">k</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">SFO</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k_parent <span class="op">=</span> <span class="va">k</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">ds_sfo_mean</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">k_in</span>, <span class="va">pred_sfo</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds_sfo_mean</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"ds"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">12345</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">ds_sfo_syn</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ds_sfo_mean</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">ds</span>,</span></span> +<span class="r-in"><span> sdfunc <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="fl">1</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="fl">0.07</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> n <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="co"># Evaluate using mmkin and nlme</span></span></span> +<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://svn.r-project.org/R-packages/trunk/nlme/" class="external-link">nlme</a></span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">ds_sfo_syn</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>Optimisation did not converge:</span> +<span class="r-wrn co"><span class="r-pr">#></span> iteration limit reached without convergence (10)</span> +<span class="r-in"><span><span class="va">f_nlme</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/pkg/nlme/man/nlme.html" class="external-link">nlme</a></span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">)</span></span></span> +<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>Iteration 4, LME step: nlminb() did not converge (code = 1). PORT message: false convergence (8)</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_nlme</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> nlme version used for fitting: 3.1.158 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 15:27:32 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 15:27:32 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - k_parent * parent</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 0.534 s using 4 iterations</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model: Two-component variance function </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Mean of starting values for individual parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_parent </span> +<span class="r-out co"><span class="r-pr">#></span> 101.569 -4.454 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 584.5 599.5 -286.2</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised, transformed parameters with symmetric confidence intervals:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 99.371 101.592 103.814</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -4.973 -4.449 -3.926</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Correlation: </span> +<span class="r-out co"><span class="r-pr">#></span> parnt_0</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent 0.0507 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> Formula: list(parent_0 ~ 1, log_k_parent ~ 1)</span> +<span class="r-out co"><span class="r-pr">#></span> Level: ds</span> +<span class="r-out co"><span class="r-pr">#></span> Structure: Diagonal</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_parent Residual</span> +<span class="r-out co"><span class="r-pr">#></span> StdDev: 6.924e-05 0.5863 1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance function:</span> +<span class="r-out co"><span class="r-pr">#></span> Structure: Constant plus proportion of variance covariate</span> +<span class="r-out co"><span class="r-pr">#></span> Formula: ~fitted(.) </span> +<span class="r-out co"><span class="r-pr">#></span> Parameter estimates:</span> +<span class="r-out co"><span class="r-pr">#></span> const prop </span> +<span class="r-out co"><span class="r-pr">#></span> 0.0001208853 0.0789968036 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters with asymmetric confidence intervals:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 99.370882 101.59243 103.81398</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.006923 0.01168 0.01972</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> +<span class="r-out co"><span class="r-pr">#></span> parent 59.32 197.1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> ds name time observed predicted residual std standardized</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 104.1 101.592 2.50757 8.0255 0.312451</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 105.0 101.592 3.40757 8.0255 0.424594</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 98.5 100.796 -2.29571 7.9625 -0.288313</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 96.1 100.796 -4.69571 7.9625 -0.589725</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 101.9 99.221 2.67904 7.8381 0.341796</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 85.2 99.221 -14.02096 7.8381 -1.788812</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 99.1 96.145 2.95512 7.5951 0.389081</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 93.0 96.145 -3.14488 7.5951 -0.414065</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 88.1 90.989 -2.88944 7.1879 -0.401987</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 84.1 90.989 -6.88944 7.1879 -0.958480</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 80.2 81.493 -1.29305 6.4377 -0.200857</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 91.3 81.493 9.80695 6.4377 1.523364</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 65.1 63.344 1.75642 5.0039 0.351008</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 65.8 63.344 2.45642 5.0039 0.490898</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 47.8 50.018 -2.21764 3.9512 -0.561252</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 53.5 50.018 3.48236 3.9512 0.881335</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 37.6 39.495 -1.89515 3.1200 -0.607423</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 39.3 39.495 -0.19515 3.1200 -0.062549</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 107.9 101.592 6.30757 8.0255 0.785943</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 102.1 101.592 0.50757 8.0255 0.063245</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 103.8 100.058 3.74159 7.9043 0.473361</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 108.6 100.058 8.54159 7.9043 1.080626</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 91.0 97.060 -6.05952 7.6674 -0.790297</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 84.9 97.060 -12.15952 7.6674 -1.585874</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 79.3 91.329 -12.02867 7.2147 -1.667251</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 100.9 91.329 9.57133 7.2147 1.326647</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 77.3 82.102 -4.80185 6.4858 -0.740366</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 83.5 82.102 1.39815 6.4858 0.215571</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 66.8 66.351 0.44945 5.2415 0.085748</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 63.3 66.351 -3.05055 5.2415 -0.582002</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 40.8 40.775 0.02474 3.2211 0.007679</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 44.8 40.775 4.02474 3.2211 1.249485</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 27.8 25.832 1.96762 2.0407 0.964198</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 27.0 25.832 1.16762 2.0407 0.572171</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 15.2 16.366 -1.16561 1.2928 -0.901595</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 15.5 16.366 -0.86561 1.2928 -0.669547</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 97.7 101.592 -3.89243 8.0255 -0.485009</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 88.2 101.592 -13.39243 8.0255 -1.668739</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 109.9 99.218 10.68196 7.8379 1.362858</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 97.8 99.218 -1.41804 7.8379 -0.180921</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 100.5 94.634 5.86555 7.4758 0.784603</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 77.4 94.634 -17.23445 7.4758 -2.305360</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 7 78.3 86.093 -7.79273 6.8011 -1.145813</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 7 90.3 86.093 4.20727 6.8011 0.618620</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 14 76.0 72.958 3.04222 5.7634 0.527848</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 14 79.1 72.958 6.14222 5.7634 1.065722</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 28 46.0 52.394 -6.39404 4.1390 -1.544842</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 28 53.4 52.394 1.00596 4.1390 0.243046</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 60 25.1 24.582 0.51786 1.9419 0.266676</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 60 21.4 24.582 -3.18214 1.9419 -1.638664</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 90 11.0 12.092 -1.09202 0.9552 -1.143199</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 90 14.2 12.092 2.10798 0.9552 2.206776</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 120 5.8 5.948 -0.14810 0.4699 -0.315178</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 120 6.1 5.948 0.15190 0.4699 0.323282</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 95.3 101.592 -6.29243 8.0255 -0.784057</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 102.0 101.592 0.40757 8.0255 0.050784</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 104.4 101.125 3.27549 7.9885 0.410025</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 105.4 101.125 4.27549 7.9885 0.535205</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 113.7 100.195 13.50487 7.9151 1.706218</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 82.3 100.195 -17.89513 7.9151 -2.260886</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 98.1 98.362 -0.26190 7.7703 -0.033706</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 87.8 98.362 -10.56190 7.7703 -1.359270</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 97.9 95.234 2.66590 7.5232 0.354357</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 104.8 95.234 9.56590 7.5232 1.271521</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 85.0 89.274 -4.27372 7.0523 -0.606001</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 77.2 89.274 -12.07372 7.0523 -1.712017</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 82.2 77.013 5.18661 6.0838 0.852526</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 86.1 77.013 9.08661 6.0838 1.493571</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 70.5 67.053 3.44692 5.2970 0.650733</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 61.7 67.053 -5.35308 5.2970 -1.010591</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 60.0 58.381 1.61905 4.6119 0.351058</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 56.4 58.381 -1.98095 4.6119 -0.429530</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 92.6 101.592 -8.99243 8.0255 -1.120485</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 116.5 101.592 14.90757 8.0255 1.857531</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 108.0 99.914 8.08560 7.8929 1.024413</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 104.9 99.914 4.98560 7.8929 0.631655</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 100.5 96.641 3.85898 7.6343 0.505477</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 89.5 96.641 -7.14102 7.6343 -0.935382</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 91.7 90.412 1.28752 7.1423 0.180267</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 95.1 90.412 4.68752 7.1423 0.656304</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 82.2 80.463 1.73715 6.3563 0.273295</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 84.5 80.463 4.03715 6.3563 0.635141</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 60.5 63.728 -3.22788 5.0343 -0.641178</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 72.8 63.728 9.07212 5.0343 1.802062</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 38.3 37.399 0.90061 2.9544 0.304835</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 40.7 37.399 3.30061 2.9544 1.117174</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 22.5 22.692 -0.19165 1.7926 -0.106913</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 20.8 22.692 -1.89165 1.7926 -1.055273</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 13.4 13.768 -0.36790 1.0876 -0.338259</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 13.8 13.768 0.03210 1.0876 0.029517</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html index febf25b4..1a6da753 100644 --- a/docs/dev/reference/summary.saem.mmkin.html +++ b/docs/dev/reference/summary.saem.mmkin.html @@ -21,7 +21,7 @@ endpoints such as formation fractions and DT50 values. Optionally </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.0</span> + <span class="version label label-info" data-toggle="tooltip" data-placement="bottom" title="In-development version">1.1.2</span> </span> </div> @@ -30,7 +30,7 @@ endpoints such as formation fractions and DT50 values. Optionally <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> - <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> Articles <span class="caret"></span> @@ -45,6 +45,9 @@ endpoints such as formation fractions and DT50 values. Optionally <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> </li> <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> </li> <li> @@ -92,59 +95,88 @@ endpoints such as formation fractions and DT50 values. Optionally </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for summary.saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="va">x</span><span class="op">$</span><span class="va">verbose</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="va">x</span><span class="op">$</span><span class="va">verbose</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>object</dt> <dd><p>an object of class <a href="saem.html">saem.mmkin</a></p></dd> + + <dt>data</dt> <dd><p>logical, indicating whether the full data should be included in the summary.</p></dd> + + <dt>verbose</dt> <dd><p>Should the summary be verbose?</p></dd> + + <dt>distimes</dt> <dd><p>logical, indicating whether DT50 and DT90 values should be included.</p></dd> + + <dt>...</dt> <dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + <dt>x</dt> <dd><p>an object of class summary.saem.mmkin</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>The summary function returns a list based on the <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a>obtained in the fit, with at least the following additional components</p> + + +<p>The summary function returns a list based on the <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a></p> + + +<p>obtained in the fit, with at least the following additional components</p> <dl><dt>saemixversion, mkinversion, Rversion</dt> <dd><p>The saemix, mkin and R versions used</p></dd> + <dt>date.fit, date.summary</dt> <dd><p>The dates where the fit and the summary were produced</p></dd> + <dt>diffs</dt> <dd><p>The differential equations used in the degradation model</p></dd> + <dt>use_of_ff</dt> <dd><p>Was maximum or minimum use made of formation fractions</p></dd> + <dt>data</dt> <dd><p>The data</p></dd> + <dt>confint_trans</dt> <dd><p>Transformed parameters as used in the optimisation, with confidence intervals</p></dd> + <dt>confint_back</dt> <dd><p>Backtransformed parameters, with confidence intervals if available</p></dd> + <dt>confint_errmod</dt> <dd><p>Error model parameters with confidence intervals</p></dd> + <dt>ff</dt> <dd><p>The estimated formation fractions derived from the fitted model.</p></dd> + <dt>distimes</dt> <dd><p>The DT50 and DT90 values for each observed variable.</p></dd> + <dt>SFORB</dt> <dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> + </dl><p>The print method is called for its side effect, i.e. printing the summary.</p> </div> <div id="author"> @@ -155,50 +187,366 @@ saemix authors for the parts inherited from saemix.</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># Generate five datasets following DFOP-SFO kinetics</span></span> -<span class="r-in"><span class="va">sampling_times</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span> -<span class="r-in"><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1234</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.1</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k2_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"><span class="va">g_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.5</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_parent_to_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.3</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">pred_dfop_sfo</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">k1</span>, <span class="va">k2</span>, <span class="va">g</span>, <span class="va">f_parent_to_m1</span>, <span class="va">k_m1</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1</span>, k2 <span class="op">=</span> <span class="va">k2</span>, g <span class="op">=</span> <span class="va">g</span>, f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1</span>, k_m1 <span class="op">=</span> <span class="va">k_m1</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">sampling_times</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">ds_mean_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">5</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k2 <span class="op">=</span> <span class="va">k2_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, g <span class="op">=</span> <span class="va">g_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>,</span> -<span class="r-in"> f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k_m1 <span class="op">=</span> <span class="va">k_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">sampling_times</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"ds"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">ds_syn_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">ds</span>,</span> -<span class="r-in"> sdfunc <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="fl">1</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="fl">0.07</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>,</span> -<span class="r-in"> n <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span></span> -<span class="r-in"><span class="op">}</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="co"># Evaluate using mmkin and saem</span></span> -<span class="r-in"><span class="va">f_mmkin_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds_syn_dfop_sfo</span>,</span> -<span class="r-in"> quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin_dfop_sfo</span><span class="op">)</span></span> -<span class="r-msg co"><span class="r-pr">#></span> </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in rxModelVars_(obj):</span> Not compatible with STRSXP: [type=NULL].</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in h(simpleError(msg, call)):</span> error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_saem_dfop_sfo' not found</span> -<span class="r-in"><span class="co"># }</span></span> -<span class="r-in"></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># Generate five datasets following DFOP-SFO kinetics</span></span></span> +<span class="r-in"><span><span class="va">sampling_times</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1234</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.1</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k2_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">g_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.5</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_parent_to_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.3</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">pred_dfop_sfo</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">k1</span>, <span class="va">k2</span>, <span class="va">g</span>, <span class="va">f_parent_to_m1</span>, <span class="va">k_m1</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1</span>, k2 <span class="op">=</span> <span class="va">k2</span>, g <span class="op">=</span> <span class="va">g</span>, f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1</span>, k_m1 <span class="op">=</span> <span class="va">k_m1</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">ds_mean_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">5</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k2 <span class="op">=</span> <span class="va">k2_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, g <span class="op">=</span> <span class="va">g_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k_m1 <span class="op">=</span> <span class="va">k_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"ds"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">ds_syn_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">ds</span>,</span></span> +<span class="r-in"><span> sdfunc <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="fl">1</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="fl">0.07</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> n <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="co"># Evaluate using mmkin and saem</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds_syn_dfop_sfo</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by SAEM</span> +<span class="r-out co"><span class="r-pr">#></span> Structural model:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)</span> +<span class="r-out co"><span class="r-pr">#></span> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time))) * parent - k_m1 * m1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 171 observations of 2 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 828.1 822.7 -400.1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> estimate lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.74378 97.81291 103.67465</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -4.06168 -4.17104 -3.95231</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.92584 -1.31273 -0.53894</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.81914 -3.60206 -2.03623</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.63916 -4.32672 -2.95161</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.02927 -1.15247 1.09394</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.86164 0.67928 1.04400</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.07973 0.06437 0.09509</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 0.73313 -7.46512 8.93137</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_m1 0.06488 -0.06041 0.19017</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.41955 0.15206 0.68705</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 0.81750 0.29140 1.34361</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 0.75265 0.27939 1.22590</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.34411 -1.70964 2.39786</span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "sd(parent_0)" "sd(log_k_m1)" "sd(g_qlogis)"</span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, covariance.model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/diag.html" class="external-link">diag</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> character(0)</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html" class="external-link">intervals</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Approximate 95% confidence intervals</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed effects:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 97.54844979 100.46239264 103.37633550</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 0.01575805 0.01729111 0.01897331</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.21014925 0.28626877 0.37680664</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.02651112 0.05601399 0.11834908</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.01326524 0.02649799 0.05293107</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.31467778 0.51297098 0.70726363</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> sd(f_parent_qlogis) 0.1658367 0.4471180 0.7283993</span> +<span class="r-out co"><span class="r-pr">#></span> sd(log_k1) 0.2768757 0.7929203 1.3089649</span> +<span class="r-out co"><span class="r-pr">#></span> sd(log_k2) 0.2693629 0.7566116 1.2438602</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.70273100 0.88750764 1.07228428</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.06781347 0.08328016 0.09874685</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.1 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Sep 16 10:31:33 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Sep 16 10:31:33 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Equations:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)</span> +<span class="r-out co"><span class="r-pr">#></span> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time))) * parent - k_m1 * m1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 171 observations of 2 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 27.615 s</span> +<span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 10 chains</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model: Two-component variance function </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Mean of starting values for individual parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 </span> +<span class="r-out co"><span class="r-pr">#></span> 101.65645 -4.05368 -0.94311 -2.35943 -4.07006 </span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis </span> +<span class="r-out co"><span class="r-pr">#></span> -0.01132 </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> None</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 825.6 821.3 -401.8</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.4624 97.5484 103.3763</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -4.0576 -4.1504 -3.9647</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.9136 -1.3240 -0.5031</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.8822 -3.6302 -2.1341</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.6307 -4.3226 -2.9388</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis 0.0519 -0.7783 0.8821</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Correlation: </span> +<span class="r-out co"><span class="r-pr">#></span> parnt_0 lg_k_m1 f_prnt_ log_k1 log_k2 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.4102 </span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.2113 0.2439 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 0.1308 -0.1305 -0.0504 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -0.0383 0.0592 0.0151 0.0001 </span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.0029 -0.0118 0.0131 -0.2547 -0.1942</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4471 0.1658 0.7284</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 0.7929 0.2769 1.3090</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 0.7566 0.2694 1.2439</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Variance model:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.88751 0.70273 1.07228</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.08328 0.06781 0.09875</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.46239 97.54845 103.37634</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 0.01729 0.01576 0.01897</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.28627 0.21015 0.37681</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.05601 0.02651 0.11835</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.02650 0.01327 0.05293</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.51297 0.31468 0.70726</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> +<span class="r-out co"><span class="r-pr">#></span> ff</span> +<span class="r-out co"><span class="r-pr">#></span> parent_m1 0.2863</span> +<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.7137</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> +<span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_k1 DT50_k2</span> +<span class="r-out co"><span class="r-pr">#></span> parent 17.44 65.15 19.61 12.37 26.16</span> +<span class="r-out co"><span class="r-pr">#></span> m1 40.09 133.17 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> ds name time observed predicted residual std standardized</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 89.8 1.005e+02 -10.662393 8.4135 -1.267301</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 104.1 1.005e+02 3.637607 8.4135 0.432355</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 88.7 9.576e+01 -7.063498 8.0244 -0.880249</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 95.5 9.576e+01 -0.263498 8.0244 -0.032837</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 81.8 8.717e+01 -5.369491 7.3135 -0.734185</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 94.5 8.717e+01 7.330509 7.3135 1.002320</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 71.5 7.274e+01 -1.238672 6.1224 -0.202319</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 70.3 7.274e+01 -2.438672 6.1224 -0.398322</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 54.2 5.418e+01 0.022691 4.5984 0.004935</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 49.6 5.418e+01 -4.577309 4.5984 -0.995423</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 31.5 3.241e+01 -0.914545 2.8416 -0.321837</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 28.8 3.241e+01 -3.614545 2.8416 -1.271993</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 12.1 1.283e+01 -0.730904 1.3891 -0.526186</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 13.6 1.283e+01 0.769096 1.3891 0.553681</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 6.2 6.128e+00 0.071981 1.0238 0.070309</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 8.3 6.128e+00 2.171981 1.0238 2.121538</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.2 3.022e+00 -0.822164 0.9225 -0.891230</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.4 3.022e+00 -0.622164 0.9225 -0.674429</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.3 1.163e+00 -0.863423 0.8928 -0.967116</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.2 1.163e+00 -0.963423 0.8928 -1.079126</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 2.2 3.233e+00 -1.032930 0.9274 -1.113734</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 3.0 3.233e+00 -0.232930 0.9274 -0.251152</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 6.5 6.495e+00 0.005314 1.0393 0.005113</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 5.0 6.495e+00 -1.494686 1.0393 -1.438116</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 10.2 1.010e+01 0.096372 1.2230 0.078801</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 9.5 1.010e+01 -0.603628 1.2230 -0.493572</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 12.2 1.269e+01 -0.492073 1.3802 -0.356526</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 13.4 1.269e+01 0.707927 1.3802 0.512922</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 11.8 1.086e+01 0.944360 1.2669 0.745420</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 13.2 1.086e+01 2.344360 1.2669 1.850494</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 6.6 7.723e+00 -1.123088 1.0961 -1.024658</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 9.3 7.723e+00 1.576912 1.0961 1.438708</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 3.5 5.184e+00 -1.683936 0.9869 -1.706219</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 5.4 5.184e+00 0.216064 0.9869 0.218923</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 118.0 1.005e+02 17.537607 8.4135 2.084469</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 99.8 1.005e+02 -0.662393 8.4135 -0.078730</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 90.2 9.566e+01 -5.456414 8.0156 -0.680727</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 94.6 9.566e+01 -1.056414 8.0156 -0.131795</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 96.1 8.702e+01 9.082833 7.3009 1.244062</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 78.4 8.702e+01 -8.617167 7.3009 -1.180281</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.9 7.298e+01 4.919834 6.1423 0.800981</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.7 7.298e+01 4.719834 6.1423 0.768420</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 56.0 5.588e+01 0.124003 4.7372 0.026176</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 54.7 5.588e+01 -1.175997 4.7372 -0.248245</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.6 3.719e+01 -0.587869 3.2217 -0.182474</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.8 3.719e+01 -0.387869 3.2217 -0.120394</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 22.1 2.013e+01 1.973728 1.8966 1.040673</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 24.7 2.013e+01 4.573728 1.8966 2.411556</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 12.4 1.259e+01 -0.185933 1.3734 -0.135379</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 10.8 1.259e+01 -1.785933 1.3734 -1.300347</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 6.8 7.981e+00 -1.180542 1.1088 -1.064723</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 7.9 7.981e+00 -0.080542 1.1088 -0.072640</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 1 1.3 1.306e+00 -0.006246 0.8941 -0.006986</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 3.7 3.589e+00 0.110879 0.9365 0.118399</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 4.7 3.589e+00 1.110879 0.9365 1.186217</span> 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0.977610</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 90 7.4 8.014e+00 -0.614393 1.1105 -0.553272</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 6.1 5.736e+00 0.363593 1.0079 0.360737</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 4.5 5.736e+00 -1.236407 1.0079 -1.226697</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.2 1.005e+02 5.737607 8.4135 0.681955</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.9 1.005e+02 6.437607 8.4135 0.765155</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 107.4 9.343e+01 13.972212 7.8311 1.784188</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 96.1 9.343e+01 2.672212 7.8311 0.341229</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 79.4 8.160e+01 -2.196297 6.8531 -0.320484</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 82.6 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class="r-out co"><span class="r-pr">#></span> ds 3 m1 7 6.8 8.124e+00 -1.324338 1.1160 -1.186685</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 7 10.1 8.124e+00 1.975662 1.1160 1.770309</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 11.4 1.104e+01 0.361860 1.2778 0.283196</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 12.8 1.104e+01 1.761860 1.2778 1.378852</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 11.5 1.177e+01 -0.272554 1.3225 -0.206097</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 10.6 1.177e+01 -1.172554 1.3225 -0.886648</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 7.5 9.242e+00 -1.741667 1.1747 -1.482591</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 8.6 9.242e+00 -0.641667 1.1747 -0.546218</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 7.3 6.837e+00 0.463318 1.0544 0.439398</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 8.1 6.837e+00 1.263318 1.0544 1.198095</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 5.3 4.906e+00 0.394322 0.9770 0.403595</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 3.8 4.906e+00 -1.105678 0.9770 -1.131677</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 104.7 1.005e+02 4.237607 8.4135 0.503670</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 88.3 1.005e+02 -12.162393 8.4135 -1.445587</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.2 9.723e+01 -3.029220 8.1458 -0.371877</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.6 9.723e+01 -2.629220 8.1458 -0.322772</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 78.1 9.114e+01 -13.041804 7.6420 -1.706592</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 96.5 9.114e+01 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class="r-pr">#></span> ds 4 parent 90 11.8 1.183e+01 -0.034206 1.3263 -0.025791</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 12.1 1.183e+01 0.265794 1.3263 0.200408</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 7.0 6.985e+00 0.014647 1.0612 0.013803</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 6.2 6.985e+00 -0.785353 1.0612 -0.740078</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 0 1.6 -1.705e-13 1.600000 0.8875 1.802801</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 1 0.9 6.803e-01 0.219655 0.8893 0.246994</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 3.7 1.927e+00 1.773027 0.9019 1.965880</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 2.0 1.927e+00 0.073027 0.9019 0.080970</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.6 4.013e+00 -0.412926 0.9483 -0.435417</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.8 4.013e+00 -0.212926 0.9483 -0.224523</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 14 7.1 6.604e+00 0.495843 1.0441 0.474896</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 14 6.6 6.604e+00 -0.004157 1.0441 -0.003981</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 28 9.5 9.077e+00 0.422700 1.1658 0.362576</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 28 9.3 9.077e+00 0.222700 1.1658 0.191024</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 60 8.3 8.818e+00 -0.518498 1.1520 -0.450099</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 60 9.0 8.818e+00 0.181502 1.1520 0.157559</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 90 6.6 6.738e+00 -0.137785 1.0500 -0.131222</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 90 7.7 6.738e+00 0.962215 1.0500 0.916383</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 120 3.7 4.794e+00 -1.093754 0.9732 -1.123914</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 120 3.5 4.794e+00 -1.293754 0.9732 -1.329429</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 110.4 1.005e+02 9.937607 8.4135 1.181155</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 112.1 1.005e+02 11.637607 8.4135 1.383212</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 93.5 9.372e+01 -0.215694 7.8550 -0.027460</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 91.0 9.372e+01 -2.715694 7.8550 -0.345730</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 71.0 8.226e+01 -11.257156 6.9076 -1.629667</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 89.7 8.226e+01 7.442844 6.9076 1.077480</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 60.4 6.553e+01 -5.128464 5.5289 -0.927571</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 59.1 6.553e+01 -6.428464 5.5289 -1.162699</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 56.5 4.835e+01 8.146351 4.1235 1.975572</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 47.0 4.835e+01 -1.353649 4.1235 -0.328273</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 30.2 3.300e+01 -2.803303 2.8883 -0.970586</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 23.9 3.300e+01 -9.103303 2.8883 -3.151832</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 17.0 1.891e+01 -1.905909 1.8074 -1.054506</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 18.7 1.891e+01 -0.205909 1.8074 -0.113926</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.3 1.172e+01 -0.423434 1.3194 -0.320923</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.9 1.172e+01 0.176566 1.3194 0.133820</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 9.0 7.281e+00 1.719138 1.0749 1.599402</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 8.1 7.281e+00 0.819138 1.0749 0.762086</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 0 0.7 -2.842e-13 0.700000 0.8875 0.788726</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 3.0 3.252e+00 -0.252227 0.9279 -0.271821</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 2.6 3.252e+00 -0.652227 0.9279 -0.702895</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 5.1 8.615e+00 -3.515326 1.1413 -3.080237</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 7.5 8.615e+00 -1.115326 1.1413 -0.977283</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 16.5 1.588e+01 0.619041 1.5928 0.388661</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 19.0 1.588e+01 3.119041 1.5928 1.958272</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 22.9 2.189e+01 1.014705 2.0272 0.500543</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 23.2 2.189e+01 1.314705 2.0272 0.648529</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 22.2 2.369e+01 -1.487604 2.1632 -0.687701</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 24.4 2.369e+01 0.712396 2.1632 0.329332</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 15.5 1.869e+01 -3.193942 1.7920 -1.782295</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 19.8 1.869e+01 1.106058 1.7920 0.617206</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.9 1.380e+01 1.103454 1.4518 0.760041</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.2 1.380e+01 0.403454 1.4518 0.277892</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.9 9.864e+00 1.035963 1.2093 0.856637</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.4 9.864e+00 0.535963 1.2093 0.443187</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> </code></pre></div> </div> </div> @@ -213,7 +561,7 @@ saemix authors for the parts inherited from saemix.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/dev/sitemap.xml b/docs/dev/sitemap.xml index 77355cd5..2e2c4b14 100644 --- a/docs/dev/sitemap.xml +++ b/docs/dev/sitemap.xml @@ -34,6 +34,9 @@ <loc>https://pkgdown.jrwb.de/mkin/articles/web_only/dimethenamid_2018.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/articles/web_only/multistart.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/authors.html</loc> </url> <url> @@ -97,12 +100,18 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/add_err.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/anova.saem.mmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/aw.html</loc> </url> <url> <loc>https://pkgdown.jrwb.de/mkin/reference/confint.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/convergence.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/create_deg_func.html</loc> </url> <url> @@ -124,6 +133,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/get_deg_func.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/illparms.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/ilr.html</loc> </url> <url> @@ -136,12 +148,18 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/intervals.saem.mmkin.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/llhist.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/loftest.html</loc> </url> <url> <loc>https://pkgdown.jrwb.de/mkin/reference/logLik.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/logLik.saem.mmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/logistic.solution.html</loc> </url> <url> @@ -157,6 +175,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/mean_degparms.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/mhmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/mixed.html</loc> </url> <url> @@ -199,6 +220,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/mmkin.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/multistart.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/nafta.html</loc> </url> <url> @@ -214,9 +238,15 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/nobs.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/parhist.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/parms.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/parplot.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/plot.mixed.mmkin.html</loc> </url> <url> @@ -244,12 +274,21 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/schaefer07_complex_case.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/set_nd_nq.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/sigma_twocomp.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/status.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/summary.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/summary.mmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/summary.nlme.mmkin.html</loc> </url> <url> diff --git a/docs/index.html b/docs/index.html index 6e6a90fa..67e1702a 100644 --- a/docs/index.html +++ b/docs/index.html @@ -44,7 +44,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -276,7 +276,7 @@ <div class="pkgdown"> <p></p> -<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> +<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer> diff --git a/docs/news/index.html b/docs/news/index.html index e7a7f571..faaab288 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -82,7 +82,16 @@ </div> <div class="section level2"> -<h2 class="page-header" data-toc-text="1.1.1" id="mkin-111">mkin 1.1.1<a class="anchor" aria-label="anchor" href="#mkin-111"></a></h2> +<h2 class="page-header" data-toc-text="1.1.2" id="mkin-112">mkin 1.1.2<a class="anchor" aria-label="anchor" href="#mkin-112"></a></h2> +<ul><li><p>‘R/mhmkin.R’: New method for performing multiple hierarchical mkin fits in one function call, optionally in parallel.</p></li> +<li><p>‘R/saem.R’: Implement and test saemix transformations for FOMC and HS. Also, error out if saemix transformations are requested but not supported.</p></li> +<li><p>‘R/saem.R’: ‘logLik’ and ‘update’ methods for ‘saem.mmkin’ objects.</p></li> +<li><p>‘R/convergence.R’: New generic to show convergence information with methods for ‘mmkin’ and ‘mhmkin’ objects.</p></li> +<li><p>‘R/illparms.R’: New generic to show ill-defined parameters with methods for ‘mkinfit’, ‘mmkin’, ‘saem.mmkin’ and ‘mhmkin’ objects.</p></li> +<li><p>‘R/summary.mmkin.R’: Summary method for mmkin objects.</p></li> +</ul></div> + <div class="section level2"> +<h2 class="page-header" data-toc-text="1.1.1" id="mkin-111-2022-07-12">mkin 1.1.1 (2022-07-12)<a class="anchor" aria-label="anchor" href="#mkin-111-2022-07-12"></a></h2> <ul><li><p>’R/{mkinmod,mkinpredict}.R: Store DLL information in mkinmod objects and use that information in mkinpredict to avoid a performance regression brought by a bugfix in R 4.2.x. Thanks to Tomas Kalibera for his analysis of the problem on the r-package-devel list and his suggestion on how to fix it.</p></li> <li><p>‘vignettes/FOCUS_L.rmd’: Remove an outdated note referring to a failure to calculate the covariance matrix for DFOP with the L2 dataset. Since 0.9.45.5 the covariance matrix is available</p></li> <li><p>‘vignettes/web_only/benchmarks.rmd’: Add the first benchmark data using my laptop system, therefore add the CPU when showing the benchmark results.</p></li> @@ -594,7 +603,7 @@ </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 87309c06..7db87468 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,5 +1,5 @@ pandoc: 2.9.2.1 -pkgdown: 2.0.5 +pkgdown: 2.0.6 pkgdown_sha: ~ articles: FOCUS_D: FOCUS_D.html @@ -11,7 +11,7 @@ articles: benchmarks: web_only/benchmarks.html compiled_models: web_only/compiled_models.html dimethenamid_2018: web_only/dimethenamid_2018.html -last_built: 2022-07-12T10:10Z +last_built: 2022-08-10T13:56Z urls: reference: 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href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Method to get convergence information</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/convergence.R" class="external-link"><code>R/convergence.R</code></a></small> + <div class="hidden name"><code>convergence.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Method to get convergence information</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">convergence</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">convergence</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for convergence.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The object to investigate</p></dd> + + +<dt>...</dt> +<dd><p>For potential future extensions</p></dd> + + +<dt>x</dt> +<dd><p>The object to be printed</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>For <a href="mkinfit.html">mkinfit</a> objects, a character vector containing +For <a href="mmkin.html">mmkin</a> objects, an object of class 'convergence.mmkin' with a +suitable printing method.</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS B"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">convergence</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS B</span> +<span class="r-out co"><span class="r-pr">#></span> SFO OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/reference/illparms.html b/docs/reference/illparms.html new file mode 100644 index 00000000..cbdbfde2 --- /dev/null +++ b/docs/reference/illparms.html @@ -0,0 +1,207 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Method to get the names of ill-defined parameters — illparms • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link 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t-test) for +significant difference from zero. For this test, the parameterisation +without parameter transformations is used."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Method to get the names of ill-defined parameters</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/illparms.R" class="external-link"><code>R/illparms.R</code></a></small> + <div class="hidden name"><code>illparms.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The method for generalised nonlinear regression fits as obtained +with <a href="mkinfit.html">mkinfit</a> and <a href="mmkin.html">mmkin</a> checks if the degradation parameters +pass the Wald test (in degradation kinetics often simply called t-test) for +significant difference from zero. For this test, the parameterisation +without parameter transformations is used.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for illparms.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, errmod <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mhmkin</span></span> +<span><span class="fu">illparms</span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, random <span class="op">=</span> <span class="cn">TRUE</span>, errmod <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for illparms.mhmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>The object to investigate</p></dd> + + +<dt>...</dt> +<dd><p>For potential future extensions</p></dd> + + +<dt>conf.level</dt> +<dd><p>The confidence level for checking p values</p></dd> + + +<dt>x</dt> +<dd><p>The object to be printed</p></dd> + + +<dt>random</dt> +<dd><p>For hierarchical fits, should random effects be tested?</p></dd> + + +<dt>errmod</dt> +<dd><p>For hierarchical fits, should error model parameters be +tested?</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>For <a href="mkinfit.html">mkinfit</a> or <a href="saem.html">saem</a> objects, a character vector of parameter +names. For <a href="mmkin.html">mmkin</a> or <a href="mhmkin.html">mhmkin</a> objects, a matrix like object of class +'illparms.mmkin' or 'illparms.mhmkin'. The latter objects have a suitable +printing method.</p> + </div> + <div id="details"> + <h2>Details</h2> + <p>The method for hierarchical model fits, also known as nonlinear +mixed-effects model fits as obtained with <a href="saem.html">saem</a> and <a href="mhmkin.html">mhmkin</a> +checks if any of the confidence intervals for the random +effects expressed as standard deviations include zero, and if +the confidence intervals for the error model parameters include +zero.</p> + </div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_A</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">illparms</span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "parent_0" "alpha" "beta" "sigma" </span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS C"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu">illparms</span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC parent_0, alpha, beta, sigma </span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/reference/index.html b/docs/reference/index.html index 63e3de8f..956648d2 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -17,7 +17,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.1</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -98,9 +98,27 @@ <td><p>Fit one or more kinetic models with one or more state variables to one or more datasets</p></td> </tr><tr><td> - <p><code><a href="nafta.html">nafta()</a></code> <code><a href="nafta.html">print(<i><nafta></i>)</a></code> </p> + <p><code><a href="mhmkin.html">mhmkin()</a></code> <code><a href="mhmkin.html">`[`(<i><mhmkin></i>)</a></code> <code><a href="mhmkin.html">print(<i><mhmkin></i>)</a></code> </p> </td> - <td><p>Evaluate parent kinetics using the NAFTA guidance</p></td> + <td><p>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</p></td> + </tr></tbody><tbody><tr><th colspan="2"> + <h2 id="generics">Generics <a href="#generics" class="anchor" aria-hidden="true"></a></h2> + <p class="section-desc"></p><p>Generic functions introduced by the package</p> + </th> + </tr></tbody><tbody><tr><td> + <p><code><a href="convergence.html">convergence()</a></code> <code><a href="convergence.html">print(<i><convergence.mmkin></i>)</a></code> </p> + </td> + <td><p>Method to get convergence information</p></td> + </tr><tr><td> + <p><code><a href="illparms.html">illparms()</a></code> <code><a href="illparms.html">print(<i><illparms.mmkin></i>)</a></code> <code><a href="illparms.html">print(<i><illparms.mhmkin></i>)</a></code> </p> + </td> + <td><p>Method to get the names of ill-defined parameters</p></td> + </tr><tr><td> + <p><code><a href="endpoints.html">endpoints()</a></code> </p> + </td> + <td><p>Function to calculate endpoints for further use from kinetic models fitted +with mkinfit</p></td> </tr></tbody><tbody><tr><th colspan="2"> <h2 id="show-results">Show results <a href="#show-results" class="anchor" aria-hidden="true"></a></h2> <p class="section-desc"></p><p>Functions working with mkinfit objects</p> @@ -138,11 +156,6 @@ more datasets</p></td> </td> <td><p>Calculate the minimum error to assume in order to pass the variance test</p></td> </tr><tr><td> - <p><code><a href="endpoints.html">endpoints()</a></code> </p> - </td> - <td><p>Function to calculate endpoints for further use from kinetic models fitted -with mkinfit</p></td> - </tr><tr><td> <p><code><a href="aw.html">aw()</a></code> </p> </td> <td><p>Calculate Akaike weights for model averaging</p></td> @@ -167,9 +180,13 @@ of an mmkin object</p></td> <p><code><a href="AIC.mmkin.html">AIC(<i><mmkin></i>)</a></code> <code><a href="AIC.mmkin.html">BIC(<i><mmkin></i>)</a></code> </p> </td> <td><p>Calculate the AIC for a column of an mmkin object</p></td> + </tr><tr><td> + <p><code><a href="summary.mmkin.html">summary(<i><mmkin></i>)</a></code> <code><a href="summary.mmkin.html">print(<i><summary.mmkin></i>)</a></code> </p> + </td> + <td><p>Summary method for class "mmkin"</p></td> </tr></tbody><tbody><tr><th colspan="2"> <h2 id="mixed-models">Mixed models <a href="#mixed-models" class="anchor" aria-hidden="true"></a></h2> - <p class="section-desc"></p><p>Create and work with nonlinear mixed effects models</p> + <p class="section-desc"></p><p>Create and work with nonlinear hierarchical models</p> </th> </tr></tbody><tbody><tr><td> <p><code><a href="nlme.mmkin.html">nlme(<i><mmkin></i>)</a></code> <code><a href="nlme.mmkin.html">print(<i><nlme.mmkin></i>)</a></code> <code><a href="nlme.mmkin.html">update(<i><nlme.mmkin></i>)</a></code> </p> @@ -180,6 +197,11 @@ of an mmkin object</p></td> </td> <td><p>Fit nonlinear mixed models with SAEM</p></td> </tr><tr><td> + <p><code><a href="mhmkin.html">mhmkin()</a></code> <code><a href="mhmkin.html">`[`(<i><mhmkin></i>)</a></code> <code><a href="mhmkin.html">print(<i><mhmkin></i>)</a></code> </p> + </td> + <td><p>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</p></td> + </tr><tr><td> <p><code><a href="plot.mixed.mmkin.html">plot(<i><mixed.mmkin></i>)</a></code> </p> </td> <td><p>Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object</p></td> @@ -204,7 +226,7 @@ of an mmkin object</p></td> </td> <td><p>Create a mixed effects model from an mmkin row object</p></td> </tr><tr><td> - <p><code><a href="reexports.html">reexports</a></code> </p> + <p><code><a href="reexports.html">reexports</a></code> <code><a href="reexports.html">intervals</a></code> <code><a href="reexports.html">lrtest</a></code> <code><a href="reexports.html">nlme</a></code> </p> </td> <td><p>Objects exported from other packages</p></td> </tr><tr><td> @@ -429,7 +451,7 @@ kinetic models fitted with mkinfit</p></td> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/reference/mhmkin.html b/docs/reference/mhmkin.html new file mode 100644 index 00000000..25be0af6 --- /dev/null +++ b/docs/reference/mhmkin.html @@ -0,0 +1,213 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models — mhmkin • mkin</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models — mhmkin"><meta property="og:description" content="The name of the methods expresses that (multiple) hierarchichal +(also known as multilevel) multicompartment kinetic models are +fitted. Our kinetic models are nonlinear, so we can use various nonlinear +mixed-effects model fitting functions."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mhmkin.R" class="external-link"><code>R/mhmkin.R</code></a></small> + <div class="hidden name"><code>mhmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The name of the methods expresses that (<strong>m</strong>ultiple) <strong>h</strong>ierarchichal +(also known as multilevel) <strong>m</strong>ulticompartment <strong>kin</strong>etic models are +fitted. Our kinetic models are nonlinear, so we can use various nonlinear +mixed-effects model fitting functions.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre><code>mhmkin(objects, backend = "saemix", algorithm = "saem", ...) + +# S3 method for list +mhmkin( + objects, + backend = "saemix", + ..., + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), + cluster = NULL +) + +# S3 method for mhmkin +[(x, i, j, ..., drop = FALSE) + +# S3 method for mhmkin +print(x, ...)</code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>objects</dt> +<dd><p>A list of <a href="mmkin.html">mmkin</a> objects containing fits of the same +degradation models to the same data, but using different error models.</p></dd> + + +<dt>backend</dt> +<dd><p>The backend to be used for fitting. Currently, only saemix is +supported</p></dd> + + +<dt>algorithm</dt> +<dd><p>The algorithm to be used for fitting (currently not used)</p></dd> + + +<dt>...</dt> +<dd><p>Further arguments that will be passed to the nonlinear mixed-effects +model fitting function.</p></dd> + + +<dt>cores</dt> +<dd><p>The number of cores to be used for multicore processing. This +is only used when the <code>cluster</code> argument is <code>NULL</code>. On Windows +machines, cores > 1 is not supported, you need to use the <code>cluster</code> +argument to use multiple logical processors. Per default, all cores detected +by <code><a href="https://rdrr.io/r/parallel/detectCores.html" class="external-link">parallel::detectCores()</a></code> are used, except on Windows where the default +is 1.</p></dd> + + +<dt>cluster</dt> +<dd><p>A cluster as returned by makeCluster to be used for +parallel execution.</p></dd> + + +<dt>x</dt> +<dd><p>An mhmkin object.</p></dd> + + +<dt>i</dt> +<dd><p>Row index selecting the fits for specific models</p></dd> + + +<dt>j</dt> +<dd><p>Column index selecting the fits to specific datasets</p></dd> + + +<dt>drop</dt> +<dd><p>If FALSE, the method always returns an mhmkin object, otherwise +either a list of fit objects or a single fit object.</p></dd> + +</dl></div> + <div id="value"> + <h2>Value</h2> + + +<p>A two-dimensional <a href="https://rdrr.io/r/base/array.html" class="external-link">array</a> of fit objects and/or try-errors that can +be indexed using the degradation model names for the first index (row index) +and the error model names for the second index (column index), with class +attribute 'mhmkin'.</p> + + +<p>An object of class <code>mhmkin</code>.</p> + </div> + <div id="see-also"> + <h2>See also</h2> + <div class="dont-index"><p><code>[.mhmkin</code> for subsetting mhmkin objects</p></div> + </div> + <div id="author"> + <h2>Author</h2> + <p>Johannes Ranke</p> + </div> + + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index e5bf1203..3b27ac7f 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -25,7 +25,7 @@ likelihood function."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -103,33 +103,33 @@ likelihood function.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">mkinfit</span><span class="op">(</span> - <span class="va">mkinmod</span>, - <span class="va">observed</span>, - parms.ini <span class="op">=</span> <span class="st">"auto"</span>, - state.ini <span class="op">=</span> <span class="st">"auto"</span>, - err.ini <span class="op">=</span> <span class="st">"auto"</span>, - fixed_parms <span class="op">=</span> <span class="cn">NULL</span>, - fixed_initials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">diffs</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>, - from_max_mean <span class="op">=</span> <span class="cn">FALSE</span>, - solution_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"analytical"</span>, <span class="st">"eigen"</span>, <span class="st">"deSolve"</span><span class="op">)</span>, - method.ode <span class="op">=</span> <span class="st">"lsoda"</span>, - use_compiled <span class="op">=</span> <span class="st">"auto"</span>, - control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>eval.max <span class="op">=</span> <span class="fl">300</span>, iter.max <span class="op">=</span> <span class="fl">200</span><span class="op">)</span>, - transform_rates <span class="op">=</span> <span class="cn">TRUE</span>, - transform_fractions <span class="op">=</span> <span class="cn">TRUE</span>, - quiet <span class="op">=</span> <span class="cn">FALSE</span>, - atol <span class="op">=</span> <span class="fl">1e-08</span>, - rtol <span class="op">=</span> <span class="fl">1e-10</span>, - error_model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"obs"</span>, <span class="st">"tc"</span><span class="op">)</span>, - error_model_algorithm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"d_3"</span>, <span class="st">"direct"</span>, <span class="st">"twostep"</span>, <span class="st">"threestep"</span>, - <span class="st">"fourstep"</span>, <span class="st">"IRLS"</span>, <span class="st">"OLS"</span><span class="op">)</span>, - reweight.tol <span class="op">=</span> <span class="fl">1e-08</span>, - reweight.max.iter <span class="op">=</span> <span class="fl">10</span>, - trace_parms <span class="op">=</span> <span class="cn">FALSE</span>, - test_residuals <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mkinfit</span><span class="op">(</span></span> +<span> <span class="va">mkinmod</span>,</span> +<span> <span class="va">observed</span>,</span> +<span> parms.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> state.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> err.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> fixed_parms <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> fixed_initials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">diffs</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>,</span> +<span> from_max_mean <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> solution_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"analytical"</span>, <span class="st">"eigen"</span>, <span class="st">"deSolve"</span><span class="op">)</span>,</span> +<span> method.ode <span class="op">=</span> <span class="st">"lsoda"</span>,</span> +<span> use_compiled <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>eval.max <span class="op">=</span> <span class="fl">300</span>, iter.max <span class="op">=</span> <span class="fl">200</span><span class="op">)</span>,</span> +<span> transform_rates <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> transform_fractions <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> atol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> rtol <span class="op">=</span> <span class="fl">1e-10</span>,</span> +<span> error_model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"obs"</span>, <span class="st">"tc"</span><span class="op">)</span>,</span> +<span> error_model_algorithm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"d_3"</span>, <span class="st">"direct"</span>, <span class="st">"twostep"</span>, <span class="st">"threestep"</span>, <span class="st">"fourstep"</span>,</span> +<span> <span class="st">"IRLS"</span>, <span class="st">"OLS"</span><span class="op">)</span>,</span> +<span> reweight.tol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> reweight.max.iter <span class="op">=</span> <span class="fl">10</span>,</span> +<span> trace_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> test_residuals <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> @@ -140,6 +140,8 @@ model to be fitted to the data, or one of the shorthand names ("SFO", "FOMC", "DFOP", "HS", "SFORB", "IORE"). If a shorthand name is given, a parent only degradation model is generated for the variable with the highest value in <code>observed</code>.</p></dd> + + <dt>observed</dt> <dd><p>A dataframe with the observed data. The first column called "name" must contain the name of the observed variable for each data point. @@ -150,6 +152,8 @@ order to avoid problems with fitting the two-component error model. This is not expected to be a problem, because in general, values of zero are not observed in degradation data, because there is a lower limit of detection.</p></dd> + + <dt>parms.ini</dt> <dd><p>A named vector of initial values for the parameters, including parameters to be optimised and potentially also fixed parameters @@ -161,6 +165,8 @@ needs. You can use the parameter lists "bparms.ode" from a previously fitted model, which contains the differential equation parameters from this model. This works nicely if the models are nested. An example is given below.</p></dd> + + <dt>state.ini</dt> <dd><p>A named vector of initial values for the state variables of the model. In case the observed variables are represented by more than one @@ -170,26 +176,36 @@ is to set the initial value of the first model variable to the mean of the time zero values for the variable with the maximum observed value, and all others to 0. If this variable has no time zero observations, its initial value is set to 100.</p></dd> + + <dt>err.ini</dt> <dd><p>A named vector of initial values for the error model parameters to be optimised. If set to "auto", initial values are set to default values. Otherwise, inital values for all error model parameters must be given.</p></dd> + + <dt>fixed_parms</dt> <dd><p>The names of parameters that should not be optimised but rather kept at the values specified in <code>parms.ini</code>. Alternatively, a named numeric vector of parameters to be fixed, regardless of the values in parms.ini.</p></dd> + + <dt>fixed_initials</dt> <dd><p>The names of model variables for which the initial state at time 0 should be excluded from the optimisation. Defaults to all state variables except for the first one.</p></dd> + + <dt>from_max_mean</dt> <dd><p>If this is set to TRUE, and the model has only one observed variable, then data before the time of the maximum observed value (after averaging for each sampling time) are discarded, and this time is subtracted from all remaining time values, so the time of the maximum observed mean value is the new time zero.</p></dd> + + <dt>solution_type</dt> <dd><p>If set to "eigen", the solution of the system of differential equations is based on the spectral decomposition of the @@ -200,16 +216,24 @@ only implemented for relatively simple degradation models. The default is "auto", which uses "analytical" if possible, otherwise "deSolve" if a compiler is present, and "eigen" if no compiler is present and the model can be expressed using eigenvalues and eigenvectors.</p></dd> + + <dt>method.ode</dt> <dd><p>The solution method passed via <code><a href="mkinpredict.html">mkinpredict()</a></code> to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code> in case the solution type is "deSolve". The default "lsoda" is performant, but sometimes fails to converge.</p></dd> + + <dt>use_compiled</dt> <dd><p>If set to <code>FALSE</code>, no compiled version of the <a href="mkinmod.html">mkinmod</a> model is used in the calls to <code><a href="mkinpredict.html">mkinpredict()</a></code> even if a compiled version is present.</p></dd> + + <dt>control</dt> <dd><p>A list of control arguments passed to <code><a href="https://rdrr.io/r/stats/nlminb.html" class="external-link">stats::nlminb()</a></code>.</p></dd> + + <dt>transform_rates</dt> <dd><p>Boolean specifying if kinetic rate constants should be transformed in the model specification used in the fitting for better @@ -218,6 +242,8 @@ TRUE, also alpha and beta parameters of the FOMC model are log-transformed, as well as k1 and k2 rate constants for the DFOP and HS models and the break point tb of the HS model. If FALSE, zero is used as a lower bound for the rates in the optimisation.</p></dd> + + <dt>transform_fractions</dt> <dd><p>Boolean specifying if formation fractions should be transformed in the model specification used in the fitting for @@ -225,16 +251,24 @@ better compliance with the assumption of normal distribution of the estimator. The default (TRUE) is to do transformations. If TRUE, the g parameter of the DFOP model is also transformed. Transformations are described in <a href="transform_odeparms.html">transform_odeparms</a>.</p></dd> + + <dt>quiet</dt> <dd><p>Suppress printing out the current value of the negative log-likelihood after each improvement?</p></dd> + + <dt>atol</dt> <dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default is 1e-8, which is lower than the default in the <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code> function which is used per default.</p></dd> + + <dt>rtol</dt> <dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default is 1e-10, much lower than in <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>.</p></dd> + + <dt>error_model</dt> <dd><p>If the error model is "const", a constant standard deviation is assumed.</p> @@ -246,6 +280,8 @@ used for setting up the likelihood function. Note that this model deviates from the model by Rocke and Lorenzato, as their model implies that the errors follow a lognormal distribution for large values, not a normal distribution as assumed by this method.</p></dd> + + <dt>error_model_algorithm</dt> <dd><p>If "auto", the selected algorithm depends on the error model. If the error model is "const", unweighted nonlinear @@ -271,22 +307,35 @@ unweighted least squares, and then iterates optimization of the error model parameters and subsequent optimization of the degradation model using those error model parameters, until the error model parameters converge.</p></dd> + + <dt>reweight.tol</dt> <dd><p>Tolerance for the convergence criterion calculated from the error model parameters in IRLS fits.</p></dd> + + <dt>reweight.max.iter</dt> <dd><p>Maximum number of iterations in IRLS fits.</p></dd> + + <dt>trace_parms</dt> <dd><p>Should a trace of the parameter values be listed?</p></dd> + + <dt>test_residuals</dt> <dd><p>Should the residuals be tested for normal distribution?</p></dd> + + <dt>...</dt> <dd><p>Further arguments that will be passed on to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>.</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>A list with "mkinfit" in the class attribute.</p> + + +<p>A list with "mkinfit" in the class attribute.</p> </div> <div id="details"> <h2>Details</h2> @@ -325,21 +374,21 @@ Degradation Data. <em>Environments</em> 6(12) 124 <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span> -<span class="r-in"><span class="co"># Use shorthand notation for parent only degradation</span></span> -<span class="r-in"><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:37:57 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:37:57 2022 </span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Use shorthand notation for parent only degradation</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 13:14:25 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 13:14:25 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted using 222 model solutions performed in 0.041 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 222 model solutions performed in 0.046 s</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> <span class="r-out co"><span class="r-pr">#></span> </span> @@ -374,10 +423,10 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_alpha log_beta sigma</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.770e-08</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha -1.565e-01 1.000e+00 9.564e-01 9.974e-08</span> -<span class="r-out co"><span class="r-pr">#></span> log_beta -3.142e-01 9.564e-01 1.000e+00 8.468e-08</span> -<span class="r-out co"><span class="r-pr">#></span> sigma 4.770e-08 9.974e-08 8.468e-08 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.772e-08</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.005e-07</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta -3.142e-01 9.564e-01 1.000e+00 8.541e-08</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 4.772e-08 1.005e-07 8.541e-08 1.000e+00</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> @@ -409,24 +458,24 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 63 parent 4.0 2.102 1.8977</span> <span class="r-out co"><span class="r-pr">#></span> 91 parent 3.9 1.441 2.4590</span> <span class="r-out co"><span class="r-pr">#></span> 119 parent 0.6 1.092 -0.4919</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># One parent compound, one metabolite, both single first order.</span></span> -<span class="r-in"><span class="co"># We remove zero values from FOCUS dataset D in order to avoid warnings</span></span> -<span class="r-in"><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span></span> -<span class="r-in"><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span> -<span class="r-in"> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># One parent compound, one metabolite, both single first order.</span></span></span> +<span class="r-in"><span><span class="co"># We remove zero values from FOCUS dataset D in order to avoid warnings</span></span></span> +<span class="r-in"><span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span></span></span> +<span class="r-in"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># Fit the model quietly to the FOCUS example dataset D using defaults</span></span> -<span class="r-in"><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="plot.mkinfit.html">plot_sep</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Fit the model quietly to the FOCUS example dataset D using defaults</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="plot.mkinfit.html">plot_sep</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="mkinfit-1.png" alt="" width="700" height="433"></span> -<span class="r-in"><span class="co"># As lower parent values appear to have lower variance, we try an alternative error model</span></span> -<span class="r-in"><span class="va">fit.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># This avoids the warning, and the likelihood ratio test confirms it is preferable</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># As lower parent values appear to have lower variance, we try an alternative error model</span></span></span> +<span class="r-in"><span><span class="va">fit.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This avoids the warning, and the likelihood ratio test confirms it is preferable</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -436,10 +485,10 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 2 5 -97.224 -1 64.483 9.737e-16 ***</span> <span class="r-out co"><span class="r-pr">#></span> ---</span> <span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> -<span class="r-in"><span class="co"># We can also allow for different variances of parent and metabolite as error model</span></span> -<span class="r-in"><span class="va">fit.obs</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># The two-component error model has significantly higher likelihood</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.obs</span>, <span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># We can also allow for different variances of parent and metabolite as error model</span></span></span> +<span class="r-in"><span><span class="va">fit.obs</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># The two-component error model has significantly higher likelihood</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.obs</span>, <span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -449,12 +498,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 2 6 -96.936 0 63.907 < 2.2e-16 ***</span> <span class="r-out co"><span class="r-pr">#></span> ---</span> <span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> -<span class="r-in"><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> parent_0 k_parent k_m1 f_parent_to_m1 sigma_low </span> <span class="r-out co"><span class="r-pr">#></span> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049883e-03 </span> <span class="r-out co"><span class="r-pr">#></span> rsd_high </span> <span class="r-out co"><span class="r-pr">#></span> 7.928118e-02 </span> -<span class="r-in"><span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $ff</span> <span class="r-out co"><span class="r-pr">#></span> parent_m1 parent_sink </span> <span class="r-out co"><span class="r-pr">#></span> 0.5083933 0.4916067 </span> @@ -462,38 +511,41 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> $distimes</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> <span class="r-out co"><span class="r-pr">#></span> parent 6.89313 22.89848</span> -<span class="r-out co"><span class="r-pr">#></span> m1 134.15634 445.65770</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># We can show a quick (only one replication) benchmark for this case, as we</span></span> -<span class="r-in"><span class="co"># have several alternative solution methods for the model. We skip</span></span> -<span class="r-in"><span class="co"># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span></span> -<span class="r-in"><span class="co"># benchmark vignette</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="kw">if</span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu">benchmark</span><span class="op">(</span>replications <span class="op">=</span> <span class="fl">1</span>, order <span class="op">=</span> <span class="st">"relative"</span>, columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"test"</span>, <span class="st">"relative"</span>, <span class="st">"elapsed"</span><span class="op">)</span>,</span> -<span class="r-in"> deSolve_compiled <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, use_compiled <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span> -<span class="r-in"> eigen <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"eigen"</span><span class="op">)</span>,</span> -<span class="r-in"> analytical <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"analytical"</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span></span> +<span class="r-out co"><span class="r-pr">#></span> m1 134.15634 445.65772</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can show a quick (only one replication) benchmark for this case, as we</span></span></span> +<span class="r-in"><span><span class="co"># have several alternative solution methods for the model. We skip</span></span></span> +<span class="r-in"><span><span class="co"># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span></span></span> +<span class="r-in"><span><span class="co"># benchmark vignette</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="kw">if</span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/rbenchmark/man/benchmark.html" class="external-link">benchmark</a></span><span class="op">(</span>replications <span class="op">=</span> <span class="fl">1</span>, order <span class="op">=</span> <span class="st">"relative"</span>, columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"test"</span>, <span class="st">"relative"</span>, <span class="st">"elapsed"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> deSolve_compiled <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, use_compiled <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> eigen <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"eigen"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> analytical <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"analytical"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Loading required package: rbenchmark</span> -<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>there is no package called ‘rbenchmark’</span> -<span class="r-in"><span class="co"># }</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span> -<span class="r-in"> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-out co"><span class="r-pr">#></span> test relative elapsed</span> +<span class="r-out co"><span class="r-pr">#></span> 3 analytical 1.000 0.540</span> +<span class="r-out co"><span class="r-pr">#></span> 1 deSolve_compiled 1.537 0.830</span> +<span class="r-out co"><span class="r-pr">#></span> 2 eigen 2.687 1.451</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># Again, we get a warning and try a more sophisticated error model</span></span> -<span class="r-in"><span class="va">fit.FOMC_SFO.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># This model has a higher likelihood, but not significantly so</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit.FOMC_SFO.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Again, we get a warning and try a more sophisticated error model</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This model has a higher likelihood, but not significantly so</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit.FOMC_SFO.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -501,16 +553,16 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> #Df LogLik Df Chisq Pr(>Chisq)</span> <span class="r-out co"><span class="r-pr">#></span> 1 7 -64.829 </span> <span class="r-out co"><span class="r-pr">#></span> 2 6 -64.983 -1 0.3075 0.5792</span> -<span class="r-in"><span class="co"># Also, the missing standard error for log_beta and the t-tests for alpha</span></span> -<span class="r-in"><span class="co"># and beta indicate overparameterisation</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit.FOMC_SFO.tc</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># Also, the missing standard error for log_beta and the t-tests for alpha</span></span></span> +<span class="r-in"><span><span class="co"># and beta indicate overparameterisation</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit.FOMC_SFO.tc</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span> <span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>NaNs produced</span> <span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>NaNs produced</span> <span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>diag(.) had 0 or NA entries; non-finite result is doubtful</span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:38:07 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:38:07 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 13:14:36 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 13:14:36 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> @@ -519,12 +571,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type deSolve </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted using 3924 model solutions performed in 7.107 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 3729 model solutions performed in 2.488 s</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model: Two-component variance function </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model algorithm: d_3 </span> -<span class="r-out co"><span class="r-pr">#></span> Three-step fitting yielded a higher likelihood than direct fitting </span> +<span class="r-out co"><span class="r-pr">#></span> Direct fitting and three-step fitting yield approximately the same likelihood </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Starting values for parameters to be optimised:</span> <span class="r-out co"><span class="r-pr">#></span> value type</span> @@ -559,7 +611,7 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error Lower Upper</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 101.600000 2.6400000 96.240000 107.000000</span> <span class="r-out co"><span class="r-pr">#></span> log_k_m1 -5.284000 0.0929100 -5.474000 -5.095000</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.001426 0.0766900 -0.155000 0.157800</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.001426 0.0767000 -0.155000 0.157800</span> <span class="r-out co"><span class="r-pr">#></span> log_alpha 5.522000 0.0077320 5.506000 5.538000</span> <span class="r-out co"><span class="r-pr">#></span> log_beta 7.806000 NaN NaN NaN</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low 0.002488 0.0002431 0.001992 0.002984</span> @@ -567,31 +619,31 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000000 -0.095145 -0.76674 0.70541 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.095145 1.000000 0.51428 -0.14381 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.766743 0.514278 1.00000 -0.61392 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.705413 -0.143809 -0.61392 1.00000 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000000 -0.095226 -0.76678 0.70544 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.095226 1.000000 0.51432 -0.14387 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.766780 0.514321 1.00000 -0.61396 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.705444 -0.143872 -0.61396 1.00000 NaN</span> <span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN NaN NaN 1</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.016077 0.001586 0.01548 5.87034 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.006617 -0.011694 -0.05356 0.04848 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.016073 0.001586 0.01548 5.87007 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.006626 -0.011700 -0.05357 0.04849 NaN</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low rsd_high</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 0.016077 0.006617</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 0.001586 -0.011694</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.015476 -0.053560</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.870339 0.048481</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 0.016073 0.006626</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 0.001586 -0.011700</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.015476 -0.053566</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.870075 0.048487</span> <span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low 1.000000 -0.652555</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high -0.652555 1.000000</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 1.000000 -0.652558</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high -0.652558 1.000000</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> <span class="r-out co"><span class="r-pr">#></span> t-test (unrealistically) based on the assumption of normal distribution</span> <span class="r-out co"><span class="r-pr">#></span> for estimators of untransformed parameters.</span> <span class="r-out co"><span class="r-pr">#></span> Estimate t value Pr(>t) Lower Upper</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.016e+02 32.7800 6.312e-26 9.624e+01 1.070e+02</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02</span> <span class="r-out co"><span class="r-pr">#></span> k_m1 5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 5.004e-01 20.8300 4.318e-20 4.613e-01 5.394e-01</span> -<span class="r-out co"><span class="r-pr">#></span> alpha 2.502e+02 0.5624 2.890e-01 2.463e+02 2.542e+02</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02</span> <span class="r-out co"><span class="r-pr">#></span> beta 2.455e+03 0.5549 2.915e-01 NA NA</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03</span> <span class="r-out co"><span class="r-pr">#></span> rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02</span> @@ -611,12 +663,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back</span> <span class="r-out co"><span class="r-pr">#></span> parent 6.812 22.7 6.834</span> <span class="r-out co"><span class="r-pr">#></span> m1 136.661 454.0 NA</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># We can easily use starting parameters from the parent only fit (only for illustration)</span></span> -<span class="r-in"><span class="va">fit.FOMC</span> <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> -<span class="r-in"> parms.ini <span class="op">=</span> <span class="va">fit.FOMC</span><span class="op">$</span><span class="va">bparms.ode</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can easily use starting parameters from the parent only fit (only for illustration)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC</span> <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span></span> +<span class="r-in"><span> parms.ini <span class="op">=</span> <span class="va">fit.FOMC</span><span class="op">$</span><span class="va">bparms.ode</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -631,7 +683,7 @@ Degradation Data. <em>Environments</em> 6(12) 124 </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/reference/saem-3.png b/docs/reference/saem-3.png Binary files differindex 99f2a2d6..08e0f544 100644 --- a/docs/reference/saem-3.png +++ b/docs/reference/saem-3.png diff --git a/docs/reference/saem.html b/docs/reference/saem.html index e9898a73..1bc6308e 100644 --- a/docs/reference/saem.html +++ b/docs/reference/saem.html @@ -19,7 +19,7 @@ Expectation Maximisation algorithm (SAEM)."><!-- mathjax --><script src="https:/ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -91,40 +91,40 @@ Expectation Maximisation algorithm (SAEM).</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">saem</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for mmkin</span> -<span class="fu">saem</span><span class="op">(</span> - <span class="va">object</span>, - transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>, - degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>, - test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>, - conf.level <span class="op">=</span> <span class="fl">0.6</span>, - solution_type <span class="op">=</span> <span class="st">"auto"</span>, - nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">300</span>, <span class="fl">100</span><span class="op">)</span>, - control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>displayProgress <span class="op">=</span> <span class="cn">FALSE</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, nbiter.saemix <span class="op">=</span> <span class="va">nbiter.saemix</span>, - save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>, - fail_with_errors <span class="op">=</span> <span class="cn">TRUE</span>, - verbose <span class="op">=</span> <span class="cn">FALSE</span>, - quiet <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span> - -<span class="co"># S3 method for saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span> - -<span class="fu">saemix_model</span><span class="op">(</span> - <span class="va">object</span>, - solution_type <span class="op">=</span> <span class="st">"auto"</span>, - transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>, - degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>, - test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>, - conf.level <span class="op">=</span> <span class="fl">0.6</span>, - verbose <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span> - -<span class="fu">saemix_data</span><span class="op">(</span><span class="va">object</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">saem</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu">saem</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>,</span> +<span> degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> solution_type <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">300</span>, <span class="fl">100</span><span class="op">)</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>displayProgress <span class="op">=</span> <span class="cn">FALSE</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, nbiter.saemix <span class="op">=</span> <span class="va">nbiter.saemix</span>,</span> +<span> save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> +<span> fail_with_errors <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="fu">saemix_model</span><span class="op">(</span></span> +<span> <span class="va">object</span>,</span> +<span> solution_type <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> transformations <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"mkin"</span>, <span class="st">"saemix"</span><span class="op">)</span>,</span> +<span> degparms_start <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/numeric.html" class="external-link">numeric</a></span><span class="op">(</span><span class="op">)</span>,</span> +<span> test_log_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> conf.level <span class="op">=</span> <span class="fl">0.6</span>,</span> +<span> verbose <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span> +<span></span> +<span><span class="fu">saemix_data</span><span class="op">(</span><span class="va">object</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> @@ -132,54 +132,87 @@ Expectation Maximisation algorithm (SAEM).</p> <dl><dt>object</dt> <dd><p>An <a href="mmkin.html">mmkin</a> row object containing several fits of the same <a href="mkinmod.html">mkinmod</a> model to different datasets</p></dd> + + <dt>...</dt> <dd><p>Further parameters passed to <a href="https://rdrr.io/pkg/saemix/man/saemixModel.html" class="external-link">saemix::saemixModel</a>.</p></dd> + + <dt>transformations</dt> <dd><p>Per default, all parameter transformations are done in mkin. If this argument is set to 'saemix', parameter transformations -are done in 'saemix' for the supported cases. Currently this is only -supported in cases where the initial concentration of the parent is not fixed, -SFO or DFOP is used for the parent and there is either no metabolite or one.</p></dd> +are done in 'saemix' for the supported cases, i.e. (as of version 1.1.2) +SFO, FOMC, DFOP and HS without fixing <code>parent_0</code>, and SFO or DFOP with +one SFO metabolite.</p></dd> + + <dt>degparms_start</dt> <dd><p>Parameter values given as a named numeric vector will be used to override the starting values obtained from the 'mmkin' object.</p></dd> + + <dt>test_log_parms</dt> <dd><p>If TRUE, an attempt is made to use more robust starting values for population parameters fitted as log parameters in mkin (like rate constants) by only considering rate constants that pass the t-test when calculating mean degradation parameters using <a href="mean_degparms.html">mean_degparms</a>.</p></dd> + + <dt>conf.level</dt> <dd><p>Possibility to adjust the required confidence level for parameter that are tested if requested by 'test_log_parms'.</p></dd> + + <dt>solution_type</dt> <dd><p>Possibility to specify the solution type in case the automatic choice is not desired</p></dd> + + <dt>nbiter.saemix</dt> <dd><p>Convenience option to increase the number of iterations</p></dd> + + <dt>control</dt> <dd><p>Passed to <a href="https://rdrr.io/pkg/saemix/man/saemix.html" class="external-link">saemix::saemix</a>.</p></dd> + + <dt>fail_with_errors</dt> <dd><p>Should a failure to compute standard errors from the inverse of the Fisher Information Matrix be a failure?</p></dd> + + <dt>verbose</dt> <dd><p>Should we print information about created objects of type <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> and <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a>?</p></dd> + + <dt>quiet</dt> <dd><p>Should we suppress the messages saemix prints at the beginning and the end of the optimisation process?</p></dd> + + <dt>x</dt> <dd><p>An saem.mmkin object to print</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>An S3 object of class 'saem.mmkin', containing the fitted + + +<p>An S3 object of class 'saem.mmkin', containing the fitted <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a> as a list component named 'so'. The -object also inherits from 'mixed.mmkin'. -An <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> object. -An <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a> object.</p> +object also inherits from 'mixed.mmkin'.</p> + + +<p>An <a href="https://rdrr.io/pkg/saemix/man/SaemixModel-class.html" class="external-link">saemix::SaemixModel</a> object.</p> + + +<p>An <a href="https://rdrr.io/pkg/saemix/man/SaemixData-class.html" class="external-link">saemix::SaemixData</a> object.</p> </div> <div id="details"> <h2>Details</h2> @@ -196,77 +229,105 @@ using <a href="mmkin.html">mmkin</a>.</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span> -<span class="r-in"> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_mmkin_parent_p0_fixed</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">ds</span>,</span> -<span class="r-in"> state.ini <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, fixed_initials <span class="op">=</span> <span class="st">"parent"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_p0_fixed</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_p0_fixed</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_mmkin_parent</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_fomc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_dfop</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span></span> -<span class="r-in"><span class="co"># functions from saemix</span></span> -<span class="r-in"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span></span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">ds</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">experimental_data_for_UBA_2019</span><span class="op">[</span><span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">x</span><span class="op">$</span><span class="va">data</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"name"</span>, <span class="st">"time"</span>, <span class="st">"value"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"Dataset"</span>, <span class="fl">6</span><span class="op">:</span><span class="fl">10</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent_p0_fixed</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">ds</span>,</span></span> +<span class="r-in"><span> state.ini <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, fixed_initials <span class="op">=</span> <span class="st">"parent"</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_p0_fixed</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_p0_fixed</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span>, <span class="st">"DFOP"</span><span class="op">)</span>, <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_fomc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent</span><span class="op">[</span><span class="st">"DFOP"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "sd(g_qlogis)"</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_dfop</span>, covariance.model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/diag.html" class="external-link">diag</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by SAEM</span> +<span class="r-out co"><span class="r-pr">#></span> Structural model:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 90 observations of 1 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 490.6 487.5 -237.3</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> estimate lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 93.902 91.3695 96.4339</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.936 -3.9950 -1.8762</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.091 -4.9290 -1.2523</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.366 -0.6484 -0.0836</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 2.385 2.0033 2.7664</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.476 0.3890 4.5623</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.195 0.4381 1.9517</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.092 0.7906 3.3932</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/stats/AIC.html" class="external-link">AIC</a></span><span class="op">(</span><span class="va">f_saem_dfop</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] 493.9811</span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span></span></span> +<span class="r-in"><span><span class="co"># functions from saemix</span></span></span> +<span class="r-in"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va">saemix</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Loading required package: npde</span> -<span class="r-msg co"><span class="r-pr">#></span> Package saemix, version 3.0</span> +<span class="r-msg co"><span class="r-pr">#></span> Package saemix, version 3.1</span> <span class="r-msg co"><span class="r-pr">#></span> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span> <span class="r-msg co"><span class="r-pr">#></span> </span> <span class="r-msg co"><span class="r-pr">#></span> Attaching package: ‘saemix’</span> <span class="r-msg co"><span class="r-pr">#></span> The following objects are masked from ‘package:npde’:</span> <span class="r-msg co"><span class="r-pr">#></span> </span> <span class="r-msg co"><span class="r-pr">#></span> kurtosis, skewness</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_sfo</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_dfop</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_sfo</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_dfop</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Likelihoods calculated by importance sampling</span> <span class="r-out co"><span class="r-pr">#></span> AIC BIC</span> <span class="r-out co"><span class="r-pr">#></span> 1 624.2598 622.3070</span> <span class="r-out co"><span class="r-pr">#></span> 2 467.8664 465.1324</span> <span class="r-out co"><span class="r-pr">#></span> 3 493.9811 490.4660</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"convergence"</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="saem-1.png" alt="" width="700" height="433"></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"individual.fit"</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"individual.fit"</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="saem-2.png" alt="" width="700" height="433"></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"npde"</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"npde"</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Simulating data using nsim = 1000 simulated datasets</span> <span class="r-out co"><span class="r-pr">#></span> Computing WRES and npde .</span> <span class="r-msg co"><span class="r-pr">#></span> Please use npdeSaemix to obtain VPC and npde</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"vpc"</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, plot.type <span class="op">=</span> <span class="st">"vpc"</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="saem-3.png" alt="" width="700" height="433"></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">f_mmkin_parent_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_mmkin_parent</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_fomc_tc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_tc</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_parent_tc</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_mmkin_parent</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_fomc_tc</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin_parent_tc</span><span class="op">[</span><span class="st">"FOMC"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/compare.saemix.html" class="external-link">compare.saemix</a></span><span class="op">(</span><span class="va">f_saem_fomc</span><span class="op">$</span><span class="va">so</span>, <span class="va">f_saem_fomc_tc</span><span class="op">$</span><span class="va">so</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Likelihoods calculated by importance sampling</span> <span class="r-out co"><span class="r-pr">#></span> AIC BIC</span> <span class="r-out co"><span class="r-pr">#></span> 1 467.8664 465.1324</span> <span class="r-out co"><span class="r-pr">#></span> 2 469.9096 466.7851</span> -<span class="r-in"></span> -<span class="r-in"><span class="va">sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">sfo_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">fomc_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">fomc_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span> -<span class="r-in"> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"A1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> A1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="co"># The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,</span></span> -<span class="r-in"><span class="co"># and compiled ODEs for FOMC that are much slower</span></span> -<span class="r-in"><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span> -<span class="r-in"> <span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">sfo_sfo</span>, <span class="st">"FOMC-SFO"</span> <span class="op">=</span> <span class="va">fomc_sfo</span>, <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds</span></span> -<span class="r-in"><span class="co"># each on this system, as we use analytical solutions written for saemix.</span></span> -<span class="r-in"><span class="co"># When using the analytical solutions written for mkin this took around</span></span> -<span class="r-in"><span class="co"># four minutes</span></span> -<span class="r-in"><span class="va">f_saem_sfo_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># We can use print, plot and summary methods to check the results</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,</span></span></span> +<span class="r-in"><span><span class="co"># and compiled ODEs for FOMC that are much slower</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="st">"SFO-SFO"</span> <span class="op">=</span> <span class="va">sfo_sfo</span>, <span class="st">"FOMC-SFO"</span> <span class="op">=</span> <span class="va">fomc_sfo</span>, <span class="st">"DFOP-SFO"</span> <span class="op">=</span> <span class="va">dfop_sfo</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">ds</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds</span></span></span> +<span class="r-in"><span><span class="co"># each on this system, as we use analytical solutions written for saemix.</span></span></span> +<span class="r-in"><span><span class="co"># When using the analytical solutions written for mkin this took around</span></span></span> +<span class="r-in"><span><span class="co"># four minutes</span></span></span> +<span class="r-in"><span><span class="va">f_saem_sfo_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"SFO-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu">saem</span><span class="op">(</span><span class="va">f_mmkin</span><span class="op">[</span><span class="st">"DFOP-SFO"</span>, <span class="op">]</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># We can use print, plot and summary methods to check the results</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by SAEM</span> <span class="r-out co"><span class="r-pr">#></span> Structural model:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> @@ -291,21 +352,21 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-out co"><span class="r-pr">#></span> log_k1 -2.5841 -3.6876 -1.4805</span> <span class="r-out co"><span class="r-pr">#></span> log_k2 -3.5228 -5.3254 -1.7203</span> <span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.1027 -0.8719 0.6665</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 1.8856 1.6770 2.0943</span> -<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7669 4.7695</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 1.8856 1.6676 2.1037</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7668 4.7695</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k_A1 1.7447 0.4047 3.0848</span> <span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4525 0.1620 0.7431</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.2423 0.4560 2.0285</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.0390 0.7601 3.3180</span> -<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3068 1.1946</span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/plot-SaemixObject-ANY-method.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3069 1.1947</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/plot.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="saem-4.png" alt="" width="700" height="433"></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.0 </span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.0 </span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.1 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> <span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Thu Jun 30 10:23:53 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Thu Jun 30 10:23:53 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 13:15:20 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 13:15:20 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> @@ -320,7 +381,7 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted in 8.85 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 9.258 s</span> <span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 10 chains</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Variance model: Constant variance </span> @@ -359,16 +420,16 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Random effects:</span> <span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7669 4.7695</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 2.7682 0.7668 4.7695</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k_A1 1.7447 0.4047 3.0848</span> <span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4525 0.1620 0.7431</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k1 1.2423 0.4560 2.0285</span> <span class="r-out co"><span class="r-pr">#></span> SD.log_k2 2.0390 0.7601 3.3180</span> -<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3068 1.1946</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.4439 -0.3069 1.1947</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Variance model:</span> <span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 1.886 1.677 2.094</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 1.886 1.668 2.104</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> @@ -554,27 +615,27 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 21 6.4 7.59693 -1.19693 1.886 -0.634761</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 21 7.2 7.59693 -0.39693 1.886 -0.210502</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 41 9.1 9.86436 -0.76436 1.886 -0.405361</span> -<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 41 8.5 9.86436 -1.36436 1.886 -0.723556</span> +<span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 41 8.5 9.86436 -1.36436 1.886 -0.723555</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 63 11.7 10.99397 0.70603 1.886 0.374425</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 63 12.0 10.99397 1.00603 1.886 0.533522</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 91 13.3 11.91274 1.38726 1.886 0.735696</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 91 13.2 11.91274 1.28726 1.886 0.682663</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 120 14.3 12.66519 1.63481 1.886 0.866981</span> <span class="r-out co"><span class="r-pr">#></span> Dataset 10 A1 120 12.1 12.66519 -0.56519 1.886 -0.299733</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># The following takes about 6 minutes</span></span> -<span class="r-in"><span class="co">#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span></span> -<span class="r-in"><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co">#saemix::compare.saemix(list(</span></span> -<span class="r-in"><span class="co"># f_saem_dfop_sfo$so,</span></span> -<span class="r-in"><span class="co"># f_saem_dfop_sfo_deSolve$so))</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># If the model supports it, we can also use eigenvalue based solutions, which</span></span> -<span class="r-in"><span class="co"># take a similar amount of time</span></span> -<span class="r-in"><span class="co">#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",</span></span> -<span class="r-in"><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># The following takes about 6 minutes</span></span></span> +<span class="r-in"><span><span class="co">#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",</span></span></span> +<span class="r-in"><span><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co">#saemix::compare.saemix(list(</span></span></span> +<span class="r-in"><span><span class="co"># f_saem_dfop_sfo$so,</span></span></span> +<span class="r-in"><span><span class="co"># f_saem_dfop_sfo_deSolve$so))</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># If the model supports it, we can also use eigenvalue based solutions, which</span></span></span> +<span class="r-in"><span><span class="co"># take a similar amount of time</span></span></span> +<span class="r-in"><span><span class="co">#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",</span></span></span> +<span class="r-in"><span><span class="co"># control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -589,7 +650,7 @@ using <a href="mmkin.html">mmkin</a>.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html index 6d816366..17ecdfe4 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -21,7 +21,7 @@ values."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mat </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -95,70 +95,99 @@ values.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for mkinfit</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">TRUE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, alpha <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for summary.mkinfit</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mkinfit</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">TRUE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, alpha <span class="op">=</span> <span class="fl">0.05</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.mkinfit</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>object</dt> <dd><p>an object of class <code><a href="mkinfit.html">mkinfit</a></code>.</p></dd> + + <dt>data</dt> <dd><p>logical, indicating whether the data should be included in the summary.</p></dd> + + <dt>distimes</dt> <dd><p>logical, indicating whether DT50 and DT90 values should be included.</p></dd> + + <dt>alpha</dt> <dd><p>error level for confidence interval estimation from t distribution</p></dd> + + <dt>...</dt> <dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + <dt>x</dt> <dd><p>an object of class <code>summary.mkinfit</code>.</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>The summary function returns a list with components, among others</p> + + +<p>The summary function returns a list with components, among others</p> <dl><dt>version, Rversion</dt> <dd><p>The mkin and R versions used</p></dd> + <dt>date.fit, date.summary</dt> <dd><p>The dates where the fit and the summary were produced</p></dd> + <dt>diffs</dt> <dd><p>The differential equations used in the model</p></dd> + <dt>use_of_ff</dt> <dd><p>Was maximum or minimum use made of formation fractions</p></dd> + <dt>bpar</dt> <dd><p>Optimised and backtransformed parameters</p></dd> + <dt>data</dt> <dd><p>The data (see Description above).</p></dd> + <dt>start</dt> <dd><p>The starting values and bounds, if applicable, for optimised parameters.</p></dd> + <dt>fixed</dt> <dd><p>The values of fixed parameters.</p></dd> + <dt>errmin </dt> <dd><p>The chi2 error levels for each observed variable.</p></dd> + <dt>bparms.ode</dt> <dd><p>All backtransformed ODE parameters, for use as starting parameters for related models.</p></dd> + <dt>errparms</dt> <dd><p>Error model parameters.</p></dd> + <dt>ff</dt> <dd><p>The estimated formation fractions derived from the fitted model.</p></dd> + <dt>distimes</dt> <dd><p>The DT50 and DT90 values for each observed variable.</p></dd> + <dt>SFORB</dt> <dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> + </dl><p>The print method is called for its side effect, i.e. printing the summary.</p> </div> <div id="references"> @@ -176,19 +205,19 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span><span class="op">)</span>, <span class="va">FOCUS_2006_A</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:42:00 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:42:00 2022 </span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">FOCUS_2006_A</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Jul 22 11:39:29 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Jul 22 11:39:29 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - k_parent * parent</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted using 131 model solutions performed in 0.027 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 131 model solutions performed in 0.028 s</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> <span class="r-out co"><span class="r-pr">#></span> </span> @@ -220,9 +249,9 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_parent sigma</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 5.428e-01 1.648e-07</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_parent 5.428e-01 1.000e+00 2.514e-07</span> -<span class="r-out co"><span class="r-pr">#></span> sigma 1.648e-07 2.514e-07 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 5.428e-01 1.642e-07</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent 5.428e-01 1.000e+00 2.507e-07</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 1.642e-07 2.507e-07 1.000e+00</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> @@ -252,7 +281,7 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, <span class="r-out co"><span class="r-pr">#></span> 62 parent 5.98 10.862 -4.8818</span> <span class="r-out co"><span class="r-pr">#></span> 90 parent 1.54 3.831 -2.2911</span> <span class="r-out co"><span class="r-pr">#></span> 118 parent 0.39 1.351 -0.9613</span> -<span class="r-in"></span> +<span class="r-in"><span></span></span> </code></pre></div> </div> </div> @@ -267,7 +296,7 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> </div> </footer></div> diff --git a/docs/reference/summary.mmkin.html b/docs/reference/summary.mmkin.html new file mode 100644 index 00000000..dfbd766e --- /dev/null +++ b/docs/reference/summary.mmkin.html @@ -0,0 +1,173 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta 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property="og:title" content="Summary method for class " mmkin summary.mmkin><meta property="og:description" content="Shows convergence information on the mkinfit objects contained in the object +and gives an overview of ill-defined parameters calculated by illparms."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + + + <div class="container template-reference-topic"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"><li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"><li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/dimethenamid_2018.html">Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul></li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/mkin/" class="external-link"> + <span class="fab fa-github fa-lg"></span> + + </a> +</li> + </ul></div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header><div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Summary method for class "mmkin"</h1> + <small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/summary.mmkin.R" class="external-link"><code>R/summary.mmkin.R</code></a></small> + <div class="hidden name"><code>summary.mmkin.Rd</code></div> + </div> + + <div class="ref-description"> + <p>Shows convergence information on the <a href="mkinfit.html">mkinfit</a> objects contained in the object +and gives an overview of ill-defined parameters calculated by <a href="illparms.html">illparms</a>.</p> + </div> + + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, conf.level <span class="op">=</span> <span class="fl">0.95</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> + </div> + + <div id="arguments"> + <h2>Arguments</h2> + <dl><dt>object</dt> +<dd><p>an object of class <a href="mmkin.html">mmkin</a></p></dd> + + +<dt>conf.level</dt> +<dd><p>confidence level for testing parameters</p></dd> + + +<dt>...</dt> +<dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + +<dt>x</dt> +<dd><p>an object of class <code>summary.mmkin</code>.</p></dd> + + +<dt>digits</dt> +<dd><p>number of digits to use for printing</p></dd> + +</dl></div> + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">fits</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="st">"FOMC"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"FOCUS A"</span> <span class="op">=</span> <span class="va">FOCUS_2006_A</span>,</span></span> +<span class="r-in"><span> <span class="st">"FOCUS C"</span> <span class="op">=</span> <span class="va">FOCUS_2006_C</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span>, cores <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fits</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 0.607 s</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Convergence:</span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC OK OK </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> OK: No warnings</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Ill-defined parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> dataset</span> +<span class="r-out co"><span class="r-pr">#></span> model FOCUS A FOCUS C</span> +<span class="r-out co"><span class="r-pr">#></span> SFO </span> +<span class="r-out co"><span class="r-pr">#></span> FOMC parent_0, alpha, beta, sigma </span> +<span class="r-in"><span></span></span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.5.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/reference/summary.saem.mmkin.html b/docs/reference/summary.saem.mmkin.html index c2f9490e..0ab239cb 100644 --- a/docs/reference/summary.saem.mmkin.html +++ b/docs/reference/summary.saem.mmkin.html @@ -21,7 +21,7 @@ endpoints such as formation fractions and DT50 values. Optionally </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -95,59 +95,88 @@ endpoints such as formation fractions and DT50 values. Optionally </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># S3 method for saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span> - -<span class="co"># S3 method for summary.saem.mmkin</span> -<span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="va">x</span><span class="op">$</span><span class="va">verbose</span>, <span class="va">...</span><span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># S3 method for saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">object</span>, data <span class="op">=</span> <span class="cn">FALSE</span>, verbose <span class="op">=</span> <span class="cn">FALSE</span>, distimes <span class="op">=</span> <span class="cn">TRUE</span>, <span class="va">...</span><span class="op">)</span></span> +<span></span> +<span><span class="co"># S3 method for summary.saem.mmkin</span></span> +<span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">x</span>, digits <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/Extremes.html" class="external-link">max</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fu"><a href="https://rdrr.io/r/base/options.html" class="external-link">getOption</a></span><span class="op">(</span><span class="st">"digits"</span><span class="op">)</span> <span class="op">-</span> <span class="fl">3</span><span class="op">)</span>, verbose <span class="op">=</span> <span class="va">x</span><span class="op">$</span><span class="va">verbose</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> <h2>Arguments</h2> <dl><dt>object</dt> <dd><p>an object of class <a href="saem.html">saem.mmkin</a></p></dd> + + <dt>data</dt> <dd><p>logical, indicating whether the full data should be included in the summary.</p></dd> + + <dt>verbose</dt> <dd><p>Should the summary be verbose?</p></dd> + + <dt>distimes</dt> <dd><p>logical, indicating whether DT50 and DT90 values should be included.</p></dd> + + <dt>...</dt> <dd><p>optional arguments passed to methods like <code>print</code>.</p></dd> + + <dt>x</dt> <dd><p>an object of class summary.saem.mmkin</p></dd> + + <dt>digits</dt> <dd><p>Number of digits to use for printing</p></dd> + </dl></div> <div id="value"> <h2>Value</h2> - <p>The summary function returns a list based on the <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a>obtained in the fit, with at least the following additional components</p> + + +<p>The summary function returns a list based on the <a href="https://rdrr.io/pkg/saemix/man/SaemixObject-class.html" class="external-link">saemix::SaemixObject</a></p> + + +<p>obtained in the fit, with at least the following additional components</p> <dl><dt>saemixversion, mkinversion, Rversion</dt> <dd><p>The saemix, mkin and R versions used</p></dd> + <dt>date.fit, date.summary</dt> <dd><p>The dates where the fit and the summary were produced</p></dd> + <dt>diffs</dt> <dd><p>The differential equations used in the degradation model</p></dd> + <dt>use_of_ff</dt> <dd><p>Was maximum or minimum use made of formation fractions</p></dd> + <dt>data</dt> <dd><p>The data</p></dd> + <dt>confint_trans</dt> <dd><p>Transformed parameters as used in the optimisation, with confidence intervals</p></dd> + <dt>confint_back</dt> <dd><p>Backtransformed parameters, with confidence intervals if available</p></dd> + <dt>confint_errmod</dt> <dd><p>Error model parameters with confidence intervals</p></dd> + <dt>ff</dt> <dd><p>The estimated formation fractions derived from the fitted model.</p></dd> + <dt>distimes</dt> <dd><p>The DT50 and DT90 values for each observed variable.</p></dd> + <dt>SFORB</dt> <dd><p>If applicable, eigenvalues of SFORB components of the model.</p></dd> + </dl><p>The print method is called for its side effect, i.e. printing the summary.</p> </div> <div id="author"> @@ -158,50 +187,110 @@ saemix authors for the parts inherited from saemix.</p> <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># Generate five datasets following DFOP-SFO kinetics</span></span> -<span class="r-in"><span class="va">sampling_times</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span> -<span class="r-in"><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1234</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.1</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k2_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"><span class="va">g_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.5</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_parent_to_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.3</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="va">k_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">pred_dfop_sfo</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">k1</span>, <span class="va">k2</span>, <span class="va">g</span>, <span class="va">f_parent_to_m1</span>, <span class="va">k_m1</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1</span>, k2 <span class="op">=</span> <span class="va">k2</span>, g <span class="op">=</span> <span class="va">g</span>, f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1</span>, k_m1 <span class="op">=</span> <span class="va">k_m1</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">sampling_times</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">ds_mean_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">5</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k2 <span class="op">=</span> <span class="va">k2_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, g <span class="op">=</span> <span class="va">g_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>,</span> -<span class="r-in"> f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k_m1 <span class="op">=</span> <span class="va">k_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span> -<span class="r-in"> <span class="va">sampling_times</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"ds"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="va">ds_syn_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">ds</span>,</span> -<span class="r-in"> sdfunc <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="fl">1</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="fl">0.07</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>,</span> -<span class="r-in"> n <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span></span> -<span class="r-in"><span class="op">}</span><span class="op">)</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="co"># Evaluate using mmkin and saem</span></span> -<span class="r-in"><span class="va">f_mmkin_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds_syn_dfop_sfo</span>,</span> -<span class="r-in"> quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span> -<span class="r-in"><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin_dfop_sfo</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.0 </span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:42:18 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:42:18 2022 </span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># Generate five datasets following DFOP-SFO kinetics</span></span></span> +<span class="r-in"><span><span class="va">sampling_times</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"DFOP"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"SFO"</span><span class="op">)</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">1234</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.1</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k2_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">g_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.5</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_parent_to_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">plogis</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/stats/Logistic.html" class="external-link">qlogis</a></span><span class="op">(</span><span class="fl">0.3</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">k_m1_in</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/Lognormal.html" class="external-link">rlnorm</a></span><span class="op">(</span><span class="fl">5</span>, <span class="fu"><a href="https://rdrr.io/r/base/Log.html" class="external-link">log</a></span><span class="op">(</span><span class="fl">0.02</span><span class="op">)</span>, <span class="fl">0.3</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">pred_dfop_sfo</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">k1</span>, <span class="va">k2</span>, <span class="va">g</span>, <span class="va">f_parent_to_m1</span>, <span class="va">k_m1</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1</span>, k2 <span class="op">=</span> <span class="va">k2</span>, g <span class="op">=</span> <span class="va">g</span>, f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1</span>, k_m1 <span class="op">=</span> <span class="va">k_m1</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">ds_mean_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">5</span>, <span class="kw">function</span><span class="op">(</span><span class="va">i</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">dfop_sfo</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="va">k1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k2 <span class="op">=</span> <span class="va">k2_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, g <span class="op">=</span> <span class="va">g_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>,</span></span> +<span class="r-in"><span> f_parent_to_m1 <span class="op">=</span> <span class="va">f_parent_to_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span>, k_m1 <span class="op">=</span> <span class="va">k_m1_in</span><span class="op">[</span><span class="va">i</span><span class="op">]</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, m1 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span><span class="op">)</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="st">"ds"</span>, <span class="fl">1</span><span class="op">:</span><span class="fl">5</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">ds_syn_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">lapply</a></span><span class="op">(</span><span class="va">ds_mean_dfop_sfo</span>, <span class="kw">function</span><span class="op">(</span><span class="va">ds</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">ds</span>,</span></span> +<span class="r-in"><span> sdfunc <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="fl">1</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="fl">0.07</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> n <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span></span></span> +<span class="r-in"><span><span class="op">}</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="co"># Evaluate using mmkin and saem</span></span></span> +<span class="r-in"><span><span class="va">f_mmkin_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="va">dfop_sfo</span><span class="op">)</span>, <span class="va">ds_syn_dfop_sfo</span>,</span></span> +<span class="r-in"><span> quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">5</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">f_mmkin_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Kinetic nonlinear mixed-effects model fit by SAEM</span> +<span class="r-out co"><span class="r-pr">#></span> Structural model:</span> +<span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> +<span class="r-out co"><span class="r-pr">#></span> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))</span> +<span class="r-out co"><span class="r-pr">#></span> * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)</span> +<span class="r-out co"><span class="r-pr">#></span> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *</span> +<span class="r-out co"><span class="r-pr">#></span> exp(-k2 * time))) * parent - k_m1 * m1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> 171 observations of 2 variable(s) grouped in 5 datasets</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 828.1 822.7 -400.1</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fitted parameters:</span> +<span class="r-out co"><span class="r-pr">#></span> estimate lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.74378 97.81291 103.67465</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -4.06168 -4.17104 -3.95231</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.92584 -1.31273 -0.53894</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.81914 -3.60206 -2.03623</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.63916 -4.32672 -2.95161</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.02927 -1.15247 1.09394</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.86164 0.67928 1.04400</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.07973 0.06437 0.09509</span> +<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 0.73313 -7.46512 8.93137</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k_m1 0.06488 -0.06041 0.19017</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.41955 0.15206 0.68705</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 0.81750 0.29140 1.34361</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 0.75265 0.27939 1.22590</span> +<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.34411 -1.70964 2.39786</span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> [1] "sd(parent_0)" "sd(log_k_m1)" "sd(g_qlogis)"</span> +<span class="r-in"><span><span class="va">f_saem_dfop_sfo_2</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/update.html" class="external-link">update</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, covariance.model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/diag.html" class="external-link">diag</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">0</span>, <span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">1</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="fu"><a href="illparms.html">illparms</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> character(0)</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/nlme/man/intervals.html" class="external-link">intervals</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> Approximate 95% confidence intervals</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed effects:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 97.54844979 100.46239264 103.37633550</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 0.01575805 0.01729111 0.01897331</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.21014925 0.28626877 0.37680664</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.02651112 0.05601399 0.11834908</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.01326524 0.02649799 0.05293107</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.31467778 0.51297098 0.70726363</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Random effects:</span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> sd(f_parent_qlogis) 0.1658367 0.4471180 0.7283993</span> +<span class="r-out co"><span class="r-pr">#></span> sd(log_k1) 0.2768757 0.7929203 1.3089649</span> +<span class="r-out co"><span class="r-pr">#></span> sd(log_k2) 0.2693629 0.7566116 1.2438602</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> lower est. upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.70273100 0.88750764 1.07228428</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.06781347 0.08328016 0.09874685</span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo_2</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.1 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 14:31:01 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 14:31:01 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> @@ -216,7 +305,7 @@ saemix authors for the parts inherited from saemix.</p> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted in 12.833 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 26.786 s</span> <span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 10 chains</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Variance model: Two-component variance function </span> @@ -225,7 +314,7 @@ saemix authors for the parts inherited from saemix.</p> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 </span> <span class="r-out co"><span class="r-pr">#></span> 101.65645 -4.05368 -0.94311 -2.35943 -4.07006 </span> <span class="r-out co"><span class="r-pr">#></span> g_qlogis </span> -<span class="r-out co"><span class="r-pr">#></span> -0.01133 </span> +<span class="r-out co"><span class="r-pr">#></span> -0.01132 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Fixed degradation parameter values:</span> <span class="r-out co"><span class="r-pr">#></span> None</span> @@ -234,233 +323,230 @@ saemix authors for the parts inherited from saemix.</p> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Likelihood computed by importance sampling</span> <span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> -<span class="r-out co"><span class="r-pr">#></span> 829.3 823.8 -400.6</span> +<span class="r-out co"><span class="r-pr">#></span> 825.6 821.3 -401.8</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Optimised parameters:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 101.26516 98.412 104.1188</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -4.07510 -4.168 -3.9819</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.94320 -1.350 -0.5364</span> -<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.87697 -3.703 -2.0510</span> -<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.58133 -4.313 -2.8492</span> -<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.03174 -1.564 1.5008</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.4624 97.5484 103.3763</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -4.0576 -4.1504 -3.9647</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.9136 -1.3240 -0.5031</span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 -2.8822 -3.6302 -2.1341</span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -3.6307 -4.3226 -2.9388</span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis 0.0519 -0.7783 0.8821</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Correlation: </span> <span class="r-out co"><span class="r-pr">#></span> parnt_0 lg_k_m1 f_prnt_ log_k1 log_k2 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.4167 </span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.2084 0.2383 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k1 0.1324 -0.1242 -0.0500 </span> -<span class="r-out co"><span class="r-pr">#></span> log_k2 0.0173 0.0001 -0.0067 0.1137 </span> -<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.0849 0.0691 0.0399 -0.3916 -0.3012</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.4102 </span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.2113 0.2439 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k1 0.1308 -0.1305 -0.0504 </span> +<span class="r-out co"><span class="r-pr">#></span> log_k2 -0.0383 0.0592 0.0151 0.0001 </span> +<span class="r-out co"><span class="r-pr">#></span> g_qlogis -0.0029 -0.0118 0.0131 -0.2547 -0.1942</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Random effects:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> SD.parent_0 0.16032 -34.0484 34.3690</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k_m1 0.01463 -0.3605 0.3898</span> -<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.44391 0.1646 0.7232</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 0.84861 0.3044 1.3928</span> -<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 0.79185 0.2944 1.2893</span> -<span class="r-out co"><span class="r-pr">#></span> SD.g_qlogis 0.34997 -3.0572 3.7572</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> SD.f_parent_qlogis 0.4471 0.1658 0.7284</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k1 0.7929 0.2769 1.3090</span> +<span class="r-out co"><span class="r-pr">#></span> SD.log_k2 0.7566 0.2694 1.2439</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Variance model:</span> -<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> a.1 0.87200 0.69118 1.0528</span> -<span class="r-out co"><span class="r-pr">#></span> b.1 0.07963 0.06435 0.0949</span> +<span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> a.1 0.88751 0.70273 1.07228</span> +<span class="r-out co"><span class="r-pr">#></span> b.1 0.08328 0.06781 0.09875</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> est. lower upper</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 101.26516 98.41151 104.11881</span> -<span class="r-out co"><span class="r-pr">#></span> k_m1 0.01699 0.01548 0.01865</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.28025 0.20588 0.36902</span> -<span class="r-out co"><span class="r-pr">#></span> k1 0.05630 0.02465 0.12861</span> -<span class="r-out co"><span class="r-pr">#></span> k2 0.02784 0.01339 0.05789</span> -<span class="r-out co"><span class="r-pr">#></span> g 0.49207 0.17303 0.81770</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 100.46239 97.54845 103.37634</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 0.01729 0.01576 0.01897</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 0.28627 0.21015 0.37681</span> +<span class="r-out co"><span class="r-pr">#></span> k1 0.05601 0.02651 0.11835</span> +<span class="r-out co"><span class="r-pr">#></span> k2 0.02650 0.01327 0.05293</span> +<span class="r-out co"><span class="r-pr">#></span> g 0.51297 0.31468 0.70726</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</span> <span class="r-out co"><span class="r-pr">#></span> ff</span> -<span class="r-out co"><span class="r-pr">#></span> parent_m1 0.2803</span> -<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.7197</span> +<span class="r-out co"><span class="r-pr">#></span> parent_m1 0.2863</span> +<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.7137</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back DT50_k1 DT50_k2</span> -<span class="r-out co"><span class="r-pr">#></span> parent 17.28 63.65 19.16 12.31 24.9</span> -<span class="r-out co"><span class="r-pr">#></span> m1 40.80 135.52 NA NA NA</span> +<span class="r-out co"><span class="r-pr">#></span> parent 17.44 65.15 19.61 12.37 26.16</span> +<span class="r-out co"><span class="r-pr">#></span> m1 40.09 133.17 NA NA NA</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Data:</span> -<span class="r-out co"><span class="r-pr">#></span> ds name time observed predicted residual std standardized</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 89.8 1.012e+02 -11.441861 8.1085 -1.411097</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 104.1 1.012e+02 2.858139 8.1085 0.352487</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 88.7 9.642e+01 -7.717294 7.7267 -0.998787</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 95.5 9.642e+01 -0.917294 7.7267 -0.118718</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 81.8 8.761e+01 -5.811045 7.0304 -0.826561</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 94.5 8.761e+01 6.888955 7.0304 0.979883</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 71.5 7.288e+01 -1.380912 5.8683 -0.235315</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 70.3 7.288e+01 -2.580912 5.8683 -0.439802</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 54.2 5.406e+01 0.139892 4.3920 0.031851</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 49.6 5.406e+01 -4.460108 4.3920 -1.015504</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 31.5 3.222e+01 -0.722286 2.7099 -0.266540</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 28.8 3.222e+01 -3.422286 2.7099 -1.262902</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 12.1 1.280e+01 -0.696320 1.3411 -0.519211</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 13.6 1.280e+01 0.803680 1.3411 0.599263</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 6.2 6.147e+00 0.052772 1.0000 0.052772</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 8.3 6.147e+00 2.152772 1.0000 2.152793</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.2 3.047e+00 -0.847292 0.9051 -0.936096</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.4 3.047e+00 -0.647292 0.9051 -0.715134</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.3 1.172e+00 -0.871912 0.8770 -0.994217</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.2 1.172e+00 -0.971912 0.8770 -1.108244</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 2.2 3.253e+00 -1.053335 0.9097 -1.157932</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 3.0 3.253e+00 -0.253335 0.9097 -0.278492</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 6.5 6.524e+00 -0.024120 1.0150 -0.023763</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 5.0 6.524e+00 -1.524120 1.0150 -1.501571</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 10.2 1.012e+01 0.076122 1.1875 0.064101</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 9.5 1.012e+01 -0.623878 1.1875 -0.525359</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 12.2 1.268e+01 -0.478789 1.3340 -0.358908</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 13.4 1.268e+01 0.721211 1.3340 0.540631</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 11.8 1.085e+01 0.954822 1.2272 0.778023</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 13.2 1.085e+01 2.354822 1.2272 1.918794</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 6.6 7.751e+00 -1.151363 1.0683 -1.077718</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 9.3 7.751e+00 1.548637 1.0683 1.449581</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 3.5 5.236e+00 -1.735804 0.9665 -1.795893</span> -<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 5.4 5.236e+00 0.164196 0.9665 0.169880</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 118.0 1.013e+02 16.726081 8.1110 2.062142</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 99.8 1.013e+02 -1.473919 8.1110 -0.181718</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 90.2 9.591e+01 -5.708953 7.6864 -0.742730</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 94.6 9.591e+01 -1.308953 7.6864 -0.170294</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 96.1 8.654e+01 9.564450 6.9454 1.377088</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 78.4 8.654e+01 -8.135550 6.9454 -1.171355</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.9 7.206e+01 5.840823 5.8037 1.006405</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.7 7.206e+01 5.640823 5.8037 0.971944</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 56.0 5.562e+01 0.376382 4.5141 0.083379</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 54.7 5.562e+01 -0.923618 4.5141 -0.204607</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.6 3.849e+01 -1.891356 3.1865 -0.593546</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.8 3.849e+01 -1.691356 3.1865 -0.530782</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 22.1 2.105e+01 1.052796 1.8892 0.557274</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 24.7 2.105e+01 3.652796 1.8892 1.933527</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 12.4 1.249e+01 -0.085726 1.3224 -0.064825</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 10.8 1.249e+01 -1.685726 1.3224 -1.274728</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 6.8 7.425e+00 -0.625179 1.0535 -0.593407</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 7.9 7.425e+00 0.474821 1.0535 0.450690</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 1 1.3 1.420e+00 -0.119671 0.8793 -0.136098</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 3.7 3.831e+00 -0.130721 0.9238 -0.141501</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 4.7 3.831e+00 0.869279 0.9238 0.940968</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 7 8.1 7.307e+00 0.793062 1.0483 0.756531</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 7 7.9 7.307e+00 0.593062 1.0483 0.565743</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 14 10.1 1.060e+01 -0.500946 1.2136 -0.412765</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 14 10.3 1.060e+01 -0.300946 1.2136 -0.247970</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 28 10.7 1.236e+01 -1.663249 1.3151 -1.264727</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 28 12.2 1.236e+01 -0.163249 1.3151 -0.124134</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 60 10.7 1.063e+01 0.065269 1.2155 0.053697</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 60 12.5 1.063e+01 1.865269 1.2155 1.534560</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 90 9.1 8.134e+00 0.965918 1.0862 0.889243</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 90 7.4 8.134e+00 -0.734082 1.0862 -0.675811</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 6.1 5.918e+00 0.181998 0.9912 0.183617</span> -<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 4.5 5.918e+00 -1.418002 0.9912 -1.430615</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.2 1.013e+02 4.927395 8.1109 0.607501</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.9 1.013e+02 5.627395 8.1109 0.693805</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 107.4 9.362e+01 13.778324 7.5055 1.835758</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 96.1 9.362e+01 2.478324 7.5055 0.330200</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 79.4 8.111e+01 -1.714426 6.5174 -0.263054</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 82.6 8.111e+01 1.485574 6.5174 0.227940</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 7 63.9 6.406e+01 -0.160919 5.1749 -0.031096</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 7 62.4 6.406e+01 -1.660919 5.1749 -0.320957</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 14 51.0 4.811e+01 2.894697 3.9284 0.736859</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 14 47.1 4.811e+01 -1.005303 3.9284 -0.255905</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 28 36.1 3.433e+01 1.766324 2.8695 0.615541</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 28 36.6 3.433e+01 2.266324 2.8695 0.789785</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 60 20.1 1.973e+01 0.371727 1.7967 0.206897</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 60 19.8 1.973e+01 0.071727 1.7967 0.039922</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 90 11.3 1.194e+01 -0.639567 1.2900 -0.495771</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 90 10.7 1.194e+01 -1.239567 1.2900 -0.960871</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 120 8.2 7.228e+00 0.972496 1.0448 0.930805</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 120 7.3 7.228e+00 0.072496 1.0448 0.069388</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 0 0.8 2.046e-12 0.800000 0.8720 0.917426</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 1 1.8 1.802e+00 -0.002337 0.8837 -0.002644</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 1 2.3 1.802e+00 0.497663 0.8837 0.563136</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 3 4.2 4.662e+00 -0.461759 0.9477 -0.487230</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 3 4.1 4.662e+00 -0.561759 0.9477 -0.592746</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 7 6.8 8.261e+00 -1.460846 1.0923 -1.337436</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 7 10.1 8.261e+00 1.839154 1.0923 1.683785</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 11.4 1.088e+01 0.520066 1.2292 0.423096</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 12.8 1.088e+01 1.920066 1.2292 1.562058</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 11.5 1.143e+01 0.066711 1.2606 0.052919</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 10.6 1.143e+01 -0.833289 1.2606 -0.661009</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 7.5 9.224e+00 -1.723819 1.1401 -1.511997</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 8.6 9.224e+00 -0.623819 1.1401 -0.547165</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 7.3 6.951e+00 0.348894 1.0328 0.337804</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 8.1 6.951e+00 1.148894 1.0328 1.112374</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 5.3 5.028e+00 0.272355 0.9595 0.283849</span> -<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 3.8 5.028e+00 -1.227645 0.9595 -1.279452</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 104.7 1.012e+02 3.450870 8.1091 0.425557</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 88.3 1.012e+02 -12.949130 8.1091 -1.596872</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.2 9.787e+01 -3.670543 7.8417 -0.468083</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.6 9.787e+01 -3.270543 7.8417 -0.417073</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 78.1 9.154e+01 -13.439273 7.3409 -1.830749</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 96.5 9.154e+01 4.960727 7.3409 0.675769</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 76.2 8.040e+01 -4.195825 6.4607 -0.649438</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 77.8 8.040e+01 -2.595825 6.4607 -0.401787</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 70.8 6.485e+01 5.950631 5.2368 1.136312</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 67.3 6.485e+01 2.450631 5.2368 0.467964</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 43.1 4.403e+01 -0.927716 3.6126 -0.256803</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 45.1 4.403e+01 1.072284 3.6126 0.296821</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 21.3 2.121e+01 0.085295 1.9010 0.044868</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 23.5 2.121e+01 2.285295 1.9010 1.202136</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 11.8 1.187e+01 -0.069302 1.2859 -0.053892</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 12.1 1.187e+01 0.230698 1.2859 0.179402</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 7.0 6.896e+00 0.104203 1.0305 0.101121</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 6.2 6.896e+00 -0.695797 1.0305 -0.675218</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 0 1.6 4.661e-12 1.600000 0.8720 1.834853</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 1 0.9 6.932e-01 0.206778 0.8737 0.236656</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 3.7 1.958e+00 1.742149 0.8858 1.966684</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 2.0 1.958e+00 0.042149 0.8858 0.047581</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.6 4.056e+00 -0.456030 0.9299 -0.490412</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.8 4.056e+00 -0.256030 0.9299 -0.275333</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 14 7.1 6.624e+00 0.475608 1.0191 0.466682</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 14 6.6 6.624e+00 -0.024392 1.0191 -0.023934</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 28 9.5 9.013e+00 0.487100 1.1293 0.431311</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 28 9.3 9.013e+00 0.287100 1.1293 0.254218</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 60 8.3 8.710e+00 -0.409941 1.1142 -0.367933</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 60 9.0 8.710e+00 0.290059 1.1142 0.260335</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 90 6.6 6.696e+00 -0.095953 1.0221 -0.093880</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 90 7.7 6.696e+00 1.004047 1.0221 0.982349</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 120 3.7 4.803e+00 -1.102994 0.9522 -1.158384</span> -<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 120 3.5 4.803e+00 -1.302994 0.9522 -1.368427</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 110.4 1.013e+02 9.136362 8.1102 1.126526</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 112.1 1.013e+02 10.836362 8.1102 1.336138</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 93.5 9.462e+01 -1.119415 7.5844 -0.147594</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 91.0 9.462e+01 -3.619415 7.5844 -0.477216</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 71.0 8.313e+01 -12.125525 6.6761 -1.816251</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 89.7 8.313e+01 6.574475 6.6761 0.984774</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 60.4 6.580e+01 -5.399792 5.3114 -1.016637</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 59.1 6.580e+01 -6.699792 5.3114 -1.261392</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 56.5 4.728e+01 9.217968 3.8645 2.385273</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 47.0 4.728e+01 -0.282032 3.8645 -0.072979</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 30.2 3.077e+01 -0.574817 2.6010 -0.220999</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 23.9 3.077e+01 -6.874817 2.6010 -2.643147</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 17.0 1.796e+01 -0.957722 1.6748 -0.571838</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 18.7 1.796e+01 0.742278 1.6748 0.443201</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.3 1.186e+01 -0.560382 1.2854 -0.435957</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.9 1.186e+01 0.039618 1.2854 0.030821</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 9.0 7.875e+00 1.125373 1.0740 1.047800</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 8.1 7.875e+00 0.225373 1.0740 0.209838</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 0 0.7 7.105e-15 0.700000 0.8720 0.802748</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 3.0 3.133e+00 -0.132776 0.9070 -0.146393</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 2.6 3.133e+00 -0.532776 0.9070 -0.587416</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 5.1 8.401e+00 -3.300544 1.0990 -3.003203</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 7.5 8.401e+00 -0.900544 1.0990 -0.819415</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 16.5 1.580e+01 0.697935 1.5309 0.455905</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 19.0 1.580e+01 3.197935 1.5309 2.088955</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 22.9 2.230e+01 0.604922 1.9779 0.305846</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 23.2 2.230e+01 0.904922 1.9779 0.457525</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 22.2 2.446e+01 -2.255019 2.1336 -1.056917</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 24.4 2.446e+01 -0.055019 2.1336 -0.025787</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 15.5 1.874e+01 -3.242459 1.7285 -1.875916</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 19.8 1.874e+01 1.057541 1.7285 0.611838</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.9 1.352e+01 1.376176 1.3856 0.993173</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.2 1.352e+01 0.676176 1.3856 0.487989</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.9 9.609e+00 1.291013 1.1601 1.112858</span> -<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.4 9.609e+00 0.791013 1.1601 0.681856</span> -<span class="r-in"><span class="co"># }</span></span> -<span class="r-in"></span> +<span class="r-out co"><span class="r-pr">#></span> ds name time observed predicted residual std standardized</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 89.8 1.005e+02 -10.662393 8.4135 -1.267301</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 0 104.1 1.005e+02 3.637607 8.4135 0.432355</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 88.7 9.576e+01 -7.063498 8.0244 -0.880249</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 1 95.5 9.576e+01 -0.263498 8.0244 -0.032837</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 81.8 8.717e+01 -5.369491 7.3135 -0.734185</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 3 94.5 8.717e+01 7.330509 7.3135 1.002320</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 71.5 7.274e+01 -1.238672 6.1224 -0.202319</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 7 70.3 7.274e+01 -2.438672 6.1224 -0.398322</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 54.2 5.418e+01 0.022691 4.5984 0.004935</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 14 49.6 5.418e+01 -4.577309 4.5984 -0.995423</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 31.5 3.241e+01 -0.914545 2.8416 -0.321837</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 28 28.8 3.241e+01 -3.614545 2.8416 -1.271993</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 12.1 1.283e+01 -0.730904 1.3891 -0.526186</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 60 13.6 1.283e+01 0.769096 1.3891 0.553681</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 6.2 6.128e+00 0.071981 1.0238 0.070309</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 90 8.3 6.128e+00 2.171981 1.0238 2.121538</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.2 3.022e+00 -0.822164 0.9225 -0.891230</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 parent 120 2.4 3.022e+00 -0.622164 0.9225 -0.674429</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.3 1.163e+00 -0.863423 0.8928 -0.967116</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 1 0.2 1.163e+00 -0.963423 0.8928 -1.079126</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 2.2 3.233e+00 -1.032930 0.9274 -1.113734</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 3 3.0 3.233e+00 -0.232930 0.9274 -0.251152</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 6.5 6.495e+00 0.005314 1.0393 0.005113</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 7 5.0 6.495e+00 -1.494686 1.0393 -1.438116</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 10.2 1.010e+01 0.096372 1.2230 0.078801</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 14 9.5 1.010e+01 -0.603628 1.2230 -0.493572</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 12.2 1.269e+01 -0.492073 1.3802 -0.356526</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 28 13.4 1.269e+01 0.707927 1.3802 0.512922</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 11.8 1.086e+01 0.944360 1.2669 0.745420</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 60 13.2 1.086e+01 2.344360 1.2669 1.850494</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 6.6 7.723e+00 -1.123088 1.0961 -1.024658</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 90 9.3 7.723e+00 1.576912 1.0961 1.438708</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 3.5 5.184e+00 -1.683936 0.9869 -1.706219</span> +<span class="r-out co"><span class="r-pr">#></span> ds 1 m1 120 5.4 5.184e+00 0.216064 0.9869 0.218923</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 118.0 1.005e+02 17.537607 8.4135 2.084469</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 0 99.8 1.005e+02 -0.662393 8.4135 -0.078730</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 90.2 9.566e+01 -5.456414 8.0156 -0.680727</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 1 94.6 9.566e+01 -1.056414 8.0156 -0.131795</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 96.1 8.702e+01 9.082833 7.3009 1.244062</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 3 78.4 8.702e+01 -8.617167 7.3009 -1.180281</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.9 7.298e+01 4.919834 6.1423 0.800981</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 7 77.7 7.298e+01 4.719834 6.1423 0.768420</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 56.0 5.588e+01 0.124003 4.7372 0.026176</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 14 54.7 5.588e+01 -1.175997 4.7372 -0.248245</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.6 3.719e+01 -0.587869 3.2217 -0.182474</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 28 36.8 3.719e+01 -0.387869 3.2217 -0.120394</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 22.1 2.013e+01 1.973728 1.8966 1.040673</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 60 24.7 2.013e+01 4.573728 1.8966 2.411556</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 12.4 1.259e+01 -0.185933 1.3734 -0.135379</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 90 10.8 1.259e+01 -1.785933 1.3734 -1.300347</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 6.8 7.981e+00 -1.180542 1.1088 -1.064723</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 parent 120 7.9 7.981e+00 -0.080542 1.1088 -0.072640</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 1 1.3 1.306e+00 -0.006246 0.8941 -0.006986</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 3.7 3.589e+00 0.110879 0.9365 0.118399</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 3 4.7 3.589e+00 1.110879 0.9365 1.186217</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 7 8.1 7.062e+00 1.038045 1.0647 0.974978</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 7 7.9 7.062e+00 0.838045 1.0647 0.787129</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 14 10.1 1.065e+01 -0.553713 1.2549 -0.441227</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 14 10.3 1.065e+01 -0.353713 1.2549 -0.281857</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 28 10.7 1.284e+01 -2.144854 1.3900 -1.543111</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 28 12.2 1.284e+01 -0.644854 1.3900 -0.463939</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 60 10.7 1.082e+01 -0.115278 1.2645 -0.091165</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 60 12.5 1.082e+01 1.684722 1.2645 1.332337</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 90 9.1 8.014e+00 1.085607 1.1105 0.977610</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 90 7.4 8.014e+00 -0.614393 1.1105 -0.553272</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 6.1 5.736e+00 0.363593 1.0079 0.360737</span> +<span class="r-out co"><span class="r-pr">#></span> ds 2 m1 120 4.5 5.736e+00 -1.236407 1.0079 -1.226697</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.2 1.005e+02 5.737607 8.4135 0.681955</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 0 106.9 1.005e+02 6.437607 8.4135 0.765155</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 107.4 9.343e+01 13.972212 7.8311 1.784188</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 1 96.1 9.343e+01 2.672212 7.8311 0.341229</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 79.4 8.160e+01 -2.196297 6.8531 -0.320484</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 parent 3 82.6 8.160e+01 1.003703 6.8531 0.146460</span> +<span class="r-out co"><span 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-1.324338 1.1160 -1.186685</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 7 10.1 8.124e+00 1.975662 1.1160 1.770309</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 11.4 1.104e+01 0.361860 1.2778 0.283196</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 14 12.8 1.104e+01 1.761860 1.2778 1.378852</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 11.5 1.177e+01 -0.272554 1.3225 -0.206097</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 28 10.6 1.177e+01 -1.172554 1.3225 -0.886648</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 7.5 9.242e+00 -1.741667 1.1747 -1.482591</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 60 8.6 9.242e+00 -0.641667 1.1747 -0.546218</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 7.3 6.837e+00 0.463318 1.0544 0.439398</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 90 8.1 6.837e+00 1.263318 1.0544 1.198095</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 5.3 4.906e+00 0.394322 0.9770 0.403595</span> +<span class="r-out co"><span class="r-pr">#></span> ds 3 m1 120 3.8 4.906e+00 -1.105678 0.9770 -1.131677</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 104.7 1.005e+02 4.237607 8.4135 0.503670</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 0 88.3 1.005e+02 -12.162393 8.4135 -1.445587</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.2 9.723e+01 -3.029220 8.1458 -0.371877</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 1 94.6 9.723e+01 -2.629220 8.1458 -0.322772</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 78.1 9.114e+01 -13.041804 7.6420 -1.706592</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 3 96.5 9.114e+01 5.358196 7.6420 0.701150</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 76.2 8.033e+01 -4.133084 6.7488 -0.612421</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 7 77.8 8.033e+01 -2.533084 6.7488 -0.375340</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 70.8 6.504e+01 5.757987 5.4889 1.049017</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 14 67.3 6.504e+01 2.257987 5.4889 0.411371</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 43.1 4.418e+01 -1.080806 3.7849 -0.285557</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 28 45.1 4.418e+01 0.919194 3.7849 0.242858</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 21.3 2.110e+01 0.200596 1.9686 0.101899</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 60 23.5 2.110e+01 2.400596 1.9686 1.219459</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 11.8 1.183e+01 -0.034206 1.3263 -0.025791</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 90 12.1 1.183e+01 0.265794 1.3263 0.200408</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 7.0 6.985e+00 0.014647 1.0612 0.013803</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 parent 120 6.2 6.985e+00 -0.785353 1.0612 -0.740078</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 0 1.6 -1.705e-13 1.600000 0.8875 1.802801</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 1 0.9 6.803e-01 0.219655 0.8893 0.246994</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 3.7 1.927e+00 1.773027 0.9019 1.965880</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 3 2.0 1.927e+00 0.073027 0.9019 0.080970</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.6 4.013e+00 -0.412926 0.9483 -0.435417</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 7 3.8 4.013e+00 -0.212926 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0.9732 -1.123914</span> +<span class="r-out co"><span class="r-pr">#></span> ds 4 m1 120 3.5 4.794e+00 -1.293754 0.9732 -1.329429</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 110.4 1.005e+02 9.937607 8.4135 1.181155</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 0 112.1 1.005e+02 11.637607 8.4135 1.383212</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 93.5 9.372e+01 -0.215694 7.8550 -0.027460</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 1 91.0 9.372e+01 -2.715694 7.8550 -0.345730</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 71.0 8.226e+01 -11.257156 6.9076 -1.629667</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 3 89.7 8.226e+01 7.442844 6.9076 1.077480</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 60.4 6.553e+01 -5.128464 5.5289 -0.927571</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 7 59.1 6.553e+01 -6.428464 5.5289 -1.162699</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 56.5 4.835e+01 8.146351 4.1235 1.975572</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 14 47.0 4.835e+01 -1.353649 4.1235 -0.328273</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 30.2 3.300e+01 -2.803303 2.8883 -0.970586</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 28 23.9 3.300e+01 -9.103303 2.8883 -3.151832</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 17.0 1.891e+01 -1.905909 1.8074 -1.054506</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 60 18.7 1.891e+01 -0.205909 1.8074 -0.113926</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.3 1.172e+01 -0.423434 1.3194 -0.320923</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 90 11.9 1.172e+01 0.176566 1.3194 0.133820</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 9.0 7.281e+00 1.719138 1.0749 1.599402</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 parent 120 8.1 7.281e+00 0.819138 1.0749 0.762086</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 0 0.7 -2.842e-13 0.700000 0.8875 0.788726</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 3.0 3.252e+00 -0.252227 0.9279 -0.271821</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 1 2.6 3.252e+00 -0.652227 0.9279 -0.702895</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 5.1 8.615e+00 -3.515326 1.1413 -3.080237</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 3 7.5 8.615e+00 -1.115326 1.1413 -0.977283</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 16.5 1.588e+01 0.619041 1.5928 0.388661</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 7 19.0 1.588e+01 3.119041 1.5928 1.958272</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 22.9 2.189e+01 1.014705 2.0272 0.500543</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 14 23.2 2.189e+01 1.314705 2.0272 0.648529</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 22.2 2.369e+01 -1.487604 2.1632 -0.687701</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 28 24.4 2.369e+01 0.712396 2.1632 0.329332</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 15.5 1.869e+01 -3.193942 1.7920 -1.782295</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 60 19.8 1.869e+01 1.106058 1.7920 0.617206</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.9 1.380e+01 1.103454 1.4518 0.760041</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 90 14.2 1.380e+01 0.403454 1.4518 0.277892</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.9 9.864e+00 1.035963 1.2093 0.856637</span> +<span class="r-out co"><span class="r-pr">#></span> ds 5 m1 120 10.4 9.864e+00 0.535963 1.2093 0.443187</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> </code></pre></div> </div> </div> @@ -475,7 +561,7 @@ saemix authors for the parts inherited from saemix.</p> </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> diff --git a/docs/sitemap.xml b/docs/sitemap.xml index f39832fb..b30d21a1 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -103,6 +103,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/confint.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/convergence.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/create_deg_func.html</loc> </url> <url> @@ -124,6 +127,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/get_deg_func.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/illparms.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/ilr.html</loc> </url> <url> @@ -157,6 +163,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/mean_degparms.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/mhmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/mixed.html</loc> </url> <url> @@ -262,6 +271,9 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/summary.mkinfit.html</loc> </url> <url> + <loc>https://pkgdown.jrwb.de/mkin/reference/summary.mmkin.html</loc> + </url> + <url> <loc>https://pkgdown.jrwb.de/mkin/reference/summary.nlme.mmkin.html</loc> </url> <url> diff --git a/build.log b/log/build.log index 237294e7..5ac21b0d 100644 --- a/build.log +++ b/log/build.log @@ -5,5 +5,5 @@ * creating vignettes ... OK * checking for LF line-endings in source and make files and shell scripts * checking for empty or unneeded directories -* building ‘mkin_1.1.1.tar.gz’ +* building ‘mkin_1.1.2.tar.gz’ diff --git a/check.log b/log/check.log index 807e2f33..c2b4aa50 100644 --- a/check.log +++ b/log/check.log @@ -1,14 +1,16 @@ * using log directory ‘/home/jranke/git/mkin/mkin.Rcheck’ -* using R version 4.1.3 (2022-03-10) +* using R version 4.2.1 (2022-06-23) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using options ‘--no-tests --as-cran’ * checking for file ‘mkin/DESCRIPTION’ ... OK * checking extension type ... Package -* this is package ‘mkin’ version ‘1.1.0’ +* this is package ‘mkin’ version ‘1.1.2’ * package encoding: UTF-8 -* checking CRAN incoming feasibility ... Note_to_CRAN_maintainers +* checking CRAN incoming feasibility ... NOTE Maintainer: ‘Johannes Ranke <johannes.ranke@jrwb.de>’ + +The Date field is over a month old. * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK @@ -64,9 +66,14 @@ Maintainer: ‘Johannes Ranke <johannes.ranke@jrwb.de>’ * checking package vignettes in ‘inst/doc’ ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... OK +* checking HTML version of manual ... OK * checking for non-standard things in the check directory ... OK * checking for detritus in the temp directory ... OK * DONE -Status: OK +Status: 1 NOTE +See + ‘/home/jranke/git/mkin/mkin.Rcheck/00check.log’ +for details. + diff --git a/check_dev.log b/log/check_dev.log index bd2f319f..bd2f319f 100644 --- a/check_dev.log +++ b/log/check_dev.log @@ -1,68 +1,57 @@ -ℹ Loading mkin -Loading required package: parallel ℹ Testing mkin ✔ | F W S OK | Context ✔ | 5 | AIC calculation -✔ | 5 | Analytical solutions for coupled models [3.2s] +✔ | 5 | Analytical solutions for coupled models [3.4s] ✔ | 5 | Calculation of Akaike weights ✔ | 3 | Export dataset for reading into CAKE ✔ | 12 | Confidence intervals and p-values [1.0s] -✔ | 1 12 | Dimethenamid data from 2018 [32.1s] +✔ | 1 12 | Dimethenamid data from 2018 [63.1s] ──────────────────────────────────────────────────────────────────────────────── Skip (test_dmta.R:98:3): Different backends get consistent results for SFO-SFO3+, dimethenamid data Reason: Fitting this ODE model with saemix takes about 15 minutes on my system ──────────────────────────────────────────────────────────────────────────────── -✔ | 14 | Error model fitting [4.8s] +✔ | 14 | Error model fitting [5.5s] ✔ | 5 | Time step normalisation ✔ | 4 | Calculation of FOCUS chi2 error levels [0.6s] ✔ | 14 | Results for FOCUS D established in expertise for UBA (Ranke 2014) [0.8s] -✔ | 4 | Test fitting the decline of metabolites from their maximum [0.3s] +✔ | 4 | Test fitting the decline of metabolites from their maximum [0.4s] ✔ | 1 | Fitting the logistic model [0.2s] -✔ | 1 12 | Nonlinear mixed-effects models [0.2s] +✔ | 7 | Batch fitting and diagnosing hierarchical kinetic models [28.6s] +✔ | 1 12 | Nonlinear mixed-effects models [0.6s] ──────────────────────────────────────────────────────────────────────────────── -Skip (test_mixed.R:68:3): saemix results are reproducible for biphasic fits +Skip (test_mixed.R:74:3): saemix results are reproducible for biphasic fits Reason: Fitting with saemix takes around 10 minutes when using deSolve ──────────────────────────────────────────────────────────────────────────────── ✔ | 3 | Test dataset classes mkinds and mkindsg -✔ | 10 | Special cases of mkinfit calls [0.4s] -✔ | 3 | mkinfit features [0.7s] -✔ | 8 | mkinmod model generation and printing [0.2s] -✔ | 3 | Model predictions with mkinpredict [0.4s] -✔ | 16 | Evaluations according to 2015 NAFTA guidance [1.5s] -✔ | 9 | Nonlinear mixed-effects models with nlme [8.1s] -✖ | 2 14 | Plotting [10.5s] +✔ | 10 | Special cases of mkinfit calls [1.1s] +✔ | 3 | mkinfit features [1.7s] +✔ | 8 | mkinmod model generation and printing [0.4s] +✔ | 3 | Model predictions with mkinpredict [0.6s] +✔ | 7 | Multistart method for saem.mmkin models [93.9s] +✔ | 16 | Evaluations according to 2015 NAFTA guidance [7.0s] +✔ | 9 | Nonlinear mixed-effects models with nlme [13.0s] +✔ | 16 | Plotting [11.3s] +✔ | 4 | Residuals extracted from mkinfit models +✔ | 1 36 | saemix parent models [72.6s] ──────────────────────────────────────────────────────────────────────────────── -Failure (test_plot.R:56:3): Plotting mkinfit, mmkin and mixed model objects is reproducible -Snapshot of `testcase` to 'plot/mixed-model-fit-for-nlme-object.svg' has changed -Run `testthat::snapshot_review('plot/')` to review changes -Backtrace: - 1. vdiffr::expect_doppelganger(...) - at test_plot.R:56:2 - 3. testthat::expect_snapshot_file(...) - -Failure (test_plot.R:64:3): Plotting mkinfit, mmkin and mixed model objects is reproducible -Snapshot of `testcase` to 'plot/mixed-model-fit-for-saem-object-with-mkin-transformations.svg' has changed -Run `testthat::snapshot_review('plot/')` to review changes -Backtrace: - 1. vdiffr::expect_doppelganger(...) - at test_plot.R:64:2 - 3. testthat::expect_snapshot_file(...) +Skip (test_saemix_parent.R:152:3): We can also use mkin solution methods for saem +Reason: This still takes almost 2.5 minutes although we do not solve ODEs ──────────────────────────────────────────────────────────────────────────────── -✔ | 4 | Residuals extracted from mkinfit models -✔ | 25 | saemix parent models [171.7s] -✔ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper [1.3s] -✔ | 7 | Fitting the SFORB model [3.6s] +✔ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper [1.4s] +✔ | 11 | Processing of residue series +✔ | 7 | Fitting the SFORB model [3.7s] ✔ | 1 | Summaries of old mkinfit objects -✔ | 4 | Summary [0.1s] -✔ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014) [2.1s] -✔ | 9 | Hypothesis tests [7.7s] -✔ | 4 | Calculation of maximum time weighted average concentrations (TWAs) [2.3s] +✔ | 5 | Summary [0.2s] +✔ | 4 | Results for synthetic data established in expertise for UBA (Ranke 2014) [2.2s] +✔ | 9 | Hypothesis tests [8.1s] +✔ | 4 | Calculation of maximum time weighted average concentrations (TWAs) [2.2s] ══ Results ═════════════════════════════════════════════════════════════════════ -Duration: 254.3 s +Duration: 324.3 s ── Skipped tests ────────────────────────────────────────────────────────────── • Fitting this ODE model with saemix takes about 15 minutes on my system (1) • Fitting with saemix takes around 10 minutes when using deSolve (1) +• This still takes almost 2.5 minutes although we do not solve ODEs (1) -[ FAIL 2 | WARN 0 | SKIP 2 | PASS 222 ] +[ FAIL 0 | WARN 0 | SKIP 3 | PASS 261 ] diff --git a/test_dev.log b/log/test_dev.log index 24905a1a..24905a1a 100644 --- a/test_dev.log +++ b/log/test_dev.log diff --git a/tests_slow.log b/log/tests_slow.log index b5b646b6..b5b646b6 100644 --- a/tests_slow.log +++ b/log/tests_slow.log diff --git a/man/anova.saem.mmkin.Rd b/man/anova.saem.mmkin.Rd new file mode 100644 index 00000000..ab6022bc --- /dev/null +++ b/man/anova.saem.mmkin.Rd @@ -0,0 +1,36 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/anova.saem.mmkin.R +\name{anova.saem.mmkin} +\alias{anova.saem.mmkin} +\title{Anova method for saem.mmkin objects} +\usage{ +\method{anova}{saem.mmkin}( + object, + ..., + method = c("is", "lin", "gq"), + test = FALSE, + model.names = NULL +) +} +\arguments{ +\item{object}{An \link{saem.mmkin} object} + +\item{...}{further such objects} + +\item{method}{Method for likelihood calculation: "is" (importance sampling), +"lin" (linear approximation), or "gq" (Gaussian quadrature). Passed +to \link[saemix:logLik]{saemix::logLik.SaemixObject}} + +\item{test}{Should a likelihood ratio test be performed? If TRUE, +the alternative models are tested against the first model. Should +only be done for nested models.} + +\item{model.names}{Optional character vector of model names} +} +\value{ +an "anova" data frame; the traditional (S3) result of anova() +} +\description{ +Generate an anova object. The method to calculate the BIC is that from +the saemix package. As in other prominent anova methods, models are sorted +} @@ -4,6 +4,8 @@ \alias{aw} \alias{aw.mkinfit} \alias{aw.mmkin} +\alias{aw.mixed.mmkin} +\alias{aw.multistart} \title{Calculate Akaike weights for model averaging} \usage{ aw(object, ...) @@ -11,6 +13,10 @@ aw(object, ...) \method{aw}{mkinfit}(object, ...) \method{aw}{mmkin}(object, ...) + +\method{aw}{mixed.mmkin}(object, ...) + +\method{aw}{multistart}(object, ...) } \arguments{ \item{object}{An \link{mmkin} column object, containing two or more diff --git a/man/illparms.Rd b/man/illparms.Rd new file mode 100644 index 00000000..90adf2bb --- /dev/null +++ b/man/illparms.Rd @@ -0,0 +1,73 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/illparms.R +\name{illparms} +\alias{illparms} +\alias{illparms.mkinfit} +\alias{illparms.mmkin} +\alias{print.illparms.mmkin} +\alias{illparms.saem.mmkin} +\alias{illparms.mhmkin} +\alias{print.illparms.mhmkin} +\title{Method to get the names of ill-defined parameters} +\usage{ +illparms(object, ...) + +\method{illparms}{mkinfit}(object, conf.level = 0.95, ...) + +\method{illparms}{mmkin}(object, conf.level = 0.95, ...) + +\method{print}{illparms.mmkin}(x, ...) + +\method{illparms}{saem.mmkin}(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) + +\method{illparms}{mhmkin}(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) + +\method{print}{illparms.mhmkin}(x, ...) +} +\arguments{ +\item{object}{The object to investigate} + +\item{\dots}{For potential future extensions} + +\item{conf.level}{The confidence level for checking p values} + +\item{x}{The object to be printed} + +\item{random}{For hierarchical fits, should random effects be tested?} + +\item{errmod}{For hierarchical fits, should error model parameters be +tested?} +} +\value{ +For \link{mkinfit} or \link{saem} objects, a character vector of parameter +names. For \link{mmkin} or \link{mhmkin} objects, a matrix like object of class +'illparms.mmkin' or 'illparms.mhmkin'. The latter objects have a suitable +printing method. +} +\description{ +The method for generalised nonlinear regression fits as obtained +with \link{mkinfit} and \link{mmkin} checks if the degradation parameters +pass the Wald test (in degradation kinetics often simply called t-test) for +significant difference from zero. For this test, the parameterisation +without parameter transformations is used. +} +\details{ +The method for hierarchical model fits, also known as nonlinear +mixed-effects model fits as obtained with \link{saem} and \link{mhmkin} +checks if any of the confidence intervals for the random +effects expressed as standard deviations include zero, and if +the confidence intervals for the error model parameters include +zero. +} +\examples{ +fit <- mkinfit("FOMC", FOCUS_2006_A, quiet = TRUE) +illparms(fit) +\dontrun{ +fits <- mmkin( + c("SFO", "FOMC"), + list("FOCUS A" = FOCUS_2006_A, + "FOCUS C" = FOCUS_2006_C), + quiet = TRUE) +illparms(fits) +} +} diff --git a/man/llhist.Rd b/man/llhist.Rd new file mode 100644 index 00000000..bec30ecf --- /dev/null +++ b/man/llhist.Rd @@ -0,0 +1,26 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/llhist.R +\name{llhist} +\alias{llhist} +\title{Plot the distribution of log likelihoods from multistart objects} +\usage{ +llhist(object, breaks = "Sturges", lpos = "topleft", main = "", ...) +} +\arguments{ +\item{object}{The \link{multistart} object} + +\item{breaks}{Passed to \link{hist}} + +\item{lpos}{Positioning of the legend.} + +\item{main}{Title of the plot} + +\item{\dots}{Passed to \link{hist}} +} +\description{ +Produces a histogram of log-likelihoods. In addition, the likelihood of the +original fit is shown as a red vertical line. +} +\seealso{ +\link{multistart} +} diff --git a/man/logLik.saem.mmkin.Rd b/man/logLik.saem.mmkin.Rd new file mode 100644 index 00000000..bd0bb72e --- /dev/null +++ b/man/logLik.saem.mmkin.Rd @@ -0,0 +1,18 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/saem.R +\name{logLik.saem.mmkin} +\alias{logLik.saem.mmkin} +\title{logLik method for saem.mmkin objects} +\usage{ +\method{logLik}{saem.mmkin}(object, ..., method = c("is", "lin", "gq")) +} +\arguments{ +\item{object}{The fitted \link{saem.mmkin} object} + +\item{\dots}{Passed to \link[saemix:logLik]{saemix::logLik.SaemixObject}} + +\item{method}{Passed to \link[saemix:logLik]{saemix::logLik.SaemixObject}} +} +\description{ +logLik method for saem.mmkin objects +} diff --git a/man/mhmkin.Rd b/man/mhmkin.Rd new file mode 100644 index 00000000..0ef1599e --- /dev/null +++ b/man/mhmkin.Rd @@ -0,0 +1,75 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mhmkin.R +\name{mhmkin} +\alias{mhmkin} +\alias{mhmkin.list} +\alias{[.mhmkin} +\alias{print.mhmkin} +\title{Fit nonlinear mixed-effects models built from one or more kinetic +degradation models and one or more error models} +\usage{ +mhmkin(objects, backend = "saemix", algorithm = "saem", ...) + +\method{mhmkin}{list}( + objects, + backend = "saemix", + ..., + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), + cluster = NULL +) + +\method{[}{mhmkin}(x, i, j, ..., drop = FALSE) + +\method{print}{mhmkin}(x, ...) +} +\arguments{ +\item{objects}{A list of \link{mmkin} objects containing fits of the same +degradation models to the same data, but using different error models.} + +\item{backend}{The backend to be used for fitting. Currently, only saemix is +supported} + +\item{algorithm}{The algorithm to be used for fitting (currently not used)} + +\item{\dots}{Further arguments that will be passed to the nonlinear mixed-effects +model fitting function.} + +\item{cores}{The number of cores to be used for multicore processing. This +is only used when the \code{cluster} argument is \code{NULL}. On Windows +machines, cores > 1 is not supported, you need to use the \code{cluster} +argument to use multiple logical processors. Per default, all cores detected +by \code{\link[parallel:detectCores]{parallel::detectCores()}} are used, except on Windows where the default +is 1.} + +\item{cluster}{A cluster as returned by \link{makeCluster} to be used for +parallel execution.} + +\item{x}{An \link{mhmkin} object.} + +\item{i}{Row index selecting the fits for specific models} + +\item{j}{Column index selecting the fits to specific datasets} + +\item{drop}{If FALSE, the method always returns an mhmkin object, otherwise +either a list of fit objects or a single fit object.} +} +\value{ +A two-dimensional \link{array} of fit objects and/or try-errors that can +be indexed using the degradation model names for the first index (row index) +and the error model names for the second index (column index), with class +attribute 'mhmkin'. + +An object of class \code{\link{mhmkin}}. +} +\description{ +The name of the methods expresses that (\strong{m}ultiple) \strong{h}ierarchichal +(also known as multilevel) \strong{m}ulticompartment \strong{kin}etic models are +fitted. Our kinetic models are nonlinear, so we can use various nonlinear +mixed-effects model fitting functions. +} +\seealso{ +\code{\link{[.mhmkin}} for subsetting \link{mhmkin} objects +} +\author{ +Johannes Ranke +} diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd index b5b24449..f96b4d22 100644 --- a/man/mkinfit.Rd +++ b/man/mkinfit.Rd @@ -23,8 +23,8 @@ mkinfit( atol = 1e-08, rtol = 1e-10, error_model = c("const", "obs", "tc"), - error_model_algorithm = c("auto", "d_3", "direct", "twostep", "threestep", - "fourstep", "IRLS", "OLS"), + error_model_algorithm = c("auto", "d_3", "direct", "twostep", "threestep", "fourstep", + "IRLS", "OLS"), reweight.tol = 1e-08, reweight.max.iter = 10, trace_parms = FALSE, diff --git a/man/multistart.Rd b/man/multistart.Rd new file mode 100644 index 00000000..5a5f7b44 --- /dev/null +++ b/man/multistart.Rd @@ -0,0 +1,103 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/multistart.R +\name{multistart} +\alias{multistart} +\alias{multistart.saem.mmkin} +\alias{print.multistart} +\alias{best} +\alias{best.default} +\alias{which.best} +\alias{which.best.default} +\title{Perform a hierarchical model fit with multiple starting values} +\usage{ +multistart( + object, + n = 50, + cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), + cluster = NULL, + ... +) + +\method{multistart}{saem.mmkin}(object, n = 50, cores = 1, cluster = NULL, ...) + +\method{print}{multistart}(x, ...) + +best(object, ...) + +\method{best}{default}(object, ...) + +which.best(object, ...) + +\method{which.best}{default}(object, ...) +} +\arguments{ +\item{object}{The fit object to work with} + +\item{n}{How many different combinations of starting parameters should be +used?} + +\item{cores}{How many fits should be run in parallel (only on posix platforms)?} + +\item{cluster}{A cluster as returned by \link[parallel:makeCluster]{parallel::makeCluster} to be used +for parallel execution.} + +\item{\dots}{Passed to the update function.} + +\item{x}{The multistart object to print} +} +\value{ +A list of \link{saem.mmkin} objects, with class attributes +'multistart.saem.mmkin' and 'multistart'. + +The object with the highest likelihood + +The index of the object with the highest likelihood +} +\description{ +The purpose of this method is to check if a certain algorithm for fitting +nonlinear hierarchical models (also known as nonlinear mixed-effects models) +will reliably yield results that are sufficiently similar to each other, if +started with a certain range of reasonable starting parameters. It is +inspired by the article on practical identifiabiliy in the frame of nonlinear +mixed-effects models by Duchesne et al (2021). +} +\examples{ +\dontrun{ +library(mkin) +dmta_ds <- lapply(1:7, function(i) { + ds_i <- dimethenamid_2018$ds[[i]]$data + ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" + ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] + ds_i +}) +names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) +dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) +dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL + +f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE) +f_saem_full <- saem(f_mmkin) +f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16) +parplot(f_saem_full_multi, lpos = "topleft") +illparms(f_saem_full) + +f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") +illparms(f_saem_reduced) +# On Windows, we need to create a cluster first. When working with +# such a cluster, we need to export the mmkin object to the cluster +# nodes, as it is referred to when updating the saem object on the nodes. +library(parallel) +cl <- makePSOCKcluster(12) +f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl) +parplot(f_saem_reduced_multi, lpos = "topright") +stopCluster(cl) +} +} +\references{ +Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +identifiability in the frame of nonlinear mixed effects models: the example +of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +doi: 10.1186/s12859-021-04373-4. +} +\seealso{ +\link{parplot}, \link{llhist} +} diff --git a/man/parms.Rd b/man/parms.Rd index af92bd2a..5c0e8895 100644 --- a/man/parms.Rd +++ b/man/parms.Rd @@ -1,36 +1,43 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/parms.mkinfit.R +% Please edit documentation in R/parms.R \name{parms} \alias{parms} \alias{parms.mkinfit} \alias{parms.mmkin} -\title{Extract model parameters from mkinfit models} +\alias{parms.multistart} +\title{Extract model parameters} \usage{ parms(object, ...) -\method{parms}{mkinfit}(object, transformed = FALSE, ...) +\method{parms}{mkinfit}(object, transformed = FALSE, errparms = TRUE, ...) -\method{parms}{mmkin}(object, transformed = FALSE, ...) +\method{parms}{mmkin}(object, transformed = FALSE, errparms = TRUE, ...) + +\method{parms}{multistart}(object, exclude_failed = TRUE, ...) } \arguments{ -\item{object}{A fitted model object. Methods are implemented for -\code{\link[=mkinfit]{mkinfit()}} objects and for \code{\link[=mmkin]{mmkin()}} objects.} +\item{object}{A fitted model object.} \item{\dots}{Not used} -\item{transformed}{Should the parameters be returned -as used internally during the optimisation?} +\item{transformed}{Should the parameters be returned as used internally +during the optimisation?} + +\item{errparms}{Should the error model parameters be returned +in addition to the degradation parameters?} + +\item{exclude_failed}{For \link{multistart} objects, should rows for failed fits +be removed from the returned parameter matrix?} } \value{ -For mkinfit objects, a numeric vector of fitted model parameters. -For mmkin row objects, a matrix with the parameters with a -row for each dataset. If the mmkin object has more than one row, a list of -such matrices is returned. +Depending on the object, a numeric vector of fitted model parameters, +a matrix (e.g. for mmkin row objects), or a list of matrices (e.g. for +mmkin objects with more than one row). } \description{ -This function always returns degradation model parameters as well as error -model parameters, in order to avoid working with a fitted model without -considering the error structure that was assumed for the fit. +This function returns degradation model parameters as well as error +model parameters per default, in order to avoid working with a fitted model +without considering the error structure that was assumed for the fit. } \examples{ # mkinfit objects @@ -50,3 +57,6 @@ parms(fits) parms(fits, transformed = TRUE) } } +\seealso{ +\link{saem}, \link{multistart} +} diff --git a/man/parplot.Rd b/man/parplot.Rd new file mode 100644 index 00000000..37c5841d --- /dev/null +++ b/man/parplot.Rd @@ -0,0 +1,46 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/parplot.R +\name{parplot} +\alias{parplot} +\alias{parplot.multistart.saem.mmkin} +\title{Plot parameter variability of multistart objects} +\usage{ +parplot(object, ...) + +\method{parplot}{multistart.saem.mmkin}( + object, + llmin = -Inf, + scale = c("best", "median"), + lpos = "bottomleft", + main = "", + ... +) +} +\arguments{ +\item{object}{The \link{multistart} object} + +\item{\dots}{Passed to \link{boxplot}} + +\item{llmin}{The minimum likelihood of objects to be shown} + +\item{scale}{By default, scale parameters using the best available fit. +If 'median', parameters are scaled using the median parameters from all fits.} + +\item{lpos}{Positioning of the legend.} + +\item{main}{Title of the plot} +} +\description{ +Produces a boxplot with all parameters from the multiple runs, scaled +either by the parameters of the run with the highest likelihood, +or by their medians as proposed in the paper by Duchesne et al. (2021). +} +\references{ +Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical +identifiability in the frame of nonlinear mixed effects models: the example +of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478. +doi: 10.1186/s12859-021-04373-4. +} +\seealso{ +\link{multistart} +} diff --git a/man/saem.Rd b/man/saem.Rd index 0c066dd2..d7b04691 100644 --- a/man/saem.Rd +++ b/man/saem.Rd @@ -6,6 +6,7 @@ \alias{print.saem.mmkin} \alias{saemix_model} \alias{saemix_data} +\alias{parms.saem.mmkin} \title{Fit nonlinear mixed models with SAEM} \usage{ saem(object, ...) @@ -17,6 +18,10 @@ saem(object, ...) test_log_parms = TRUE, conf.level = 0.6, solution_type = "auto", + covariance.model = "auto", + covariates = NULL, + covariate_models = NULL, + no_random_effect = NULL, nbiter.saemix = c(300, 100), control = list(displayProgress = FALSE, print = FALSE, nbiter.saemix = nbiter.saemix, save = FALSE, save.graphs = FALSE), @@ -33,13 +38,19 @@ saemix_model( solution_type = "auto", transformations = c("mkin", "saemix"), degparms_start = numeric(), + covariance.model = "auto", + no_random_effect = NULL, + covariates = NULL, + covariate_models = NULL, test_log_parms = FALSE, conf.level = 0.6, verbose = FALSE, ... ) -saemix_data(object, verbose = FALSE, ...) +saemix_data(object, covariates = NULL, verbose = FALSE, ...) + +\method{parms}{saem.mmkin}(object, ci = FALSE, ...) } \arguments{ \item{object}{An \link{mmkin} row object containing several fits of the same @@ -49,9 +60,9 @@ saemix_data(object, verbose = FALSE, ...) \item{transformations}{Per default, all parameter transformations are done in mkin. If this argument is set to 'saemix', parameter transformations -are done in 'saemix' for the supported cases. Currently this is only -supported in cases where the initial concentration of the parent is not fixed, -SFO or DFOP is used for the parent and there is either no metabolite or one.} +are done in 'saemix' for the supported cases, i.e. (as of version 1.1.2) +SFO, FOMC, DFOP and HS without fixing \code{parent_0}, and SFO or DFOP with +one SFO metabolite.} \item{degparms_start}{Parameter values given as a named numeric vector will be used to override the starting values obtained from the 'mmkin' object.} @@ -67,6 +78,21 @@ for parameter that are tested if requested by 'test_log_parms'.} \item{solution_type}{Possibility to specify the solution type in case the automatic choice is not desired} +\item{covariance.model}{Will be passed to \code{\link[saemix:SaemixModel-class]{saemix::SaemixModel()}}. Per +default, uncorrelated random effects are specified for all degradation +parameters.} + +\item{covariates}{A data frame with covariate data for use in +'covariate_models', with dataset names as row names.} + +\item{covariate_models}{A list containing linear model formulas with one explanatory +variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available +in the 'covariates' data frame.} + +\item{no_random_effect}{Character vector of degradation parameters for +which there should be no variability over the groups. Only used +if the covariance model is not explicitly specified.} + \item{nbiter.saemix}{Convenience option to increase the number of iterations} @@ -84,6 +110,9 @@ and the end of the optimisation process?} \item{x}{An saem.mmkin object to print} \item{digits}{Number of digits to use for printing} + +\item{ci}{Should a matrix with estimates and confidence interval boundaries +be returned? If FALSE (default), a vector of estimates is returned.} } \value{ An S3 object of class 'saem.mmkin', containing the fitted @@ -120,7 +149,13 @@ f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) f_saem_sfo <- saem(f_mmkin_parent["SFO", ]) f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +anova(f_saem_sfo, f_saem_fomc, f_saem_dfop) +anova(f_saem_sfo, f_saem_dfop, test = TRUE) +illparms(f_saem_dfop) +f_saem_dfop_red <- update(f_saem_dfop, no_random_effect = "g_qlogis") +anova(f_saem_dfop, f_saem_dfop_red, test = TRUE) +anova(f_saem_sfo, f_saem_fomc, f_saem_dfop) # The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -132,7 +167,7 @@ plot(f_saem_fomc$so, plot.type = "vpc") f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ]) -compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so) +anova(f_saem_fomc, f_saem_fomc_tc, test = TRUE) sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), A1 = mkinsub("SFO")) diff --git a/man/set_nd_nq.Rd b/man/set_nd_nq.Rd new file mode 100644 index 00000000..87a3fae1 --- /dev/null +++ b/man/set_nd_nq.Rd @@ -0,0 +1,103 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/set_nd_nq.R +\name{set_nd_nq} +\alias{set_nd_nq} +\alias{set_nd_nq_focus} +\title{Set non-detects and unquantified values in residue series without replicates} +\usage{ +set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE) + +set_nd_nq_focus( + res_raw, + lod, + loq = NA, + set_first_sample_nd = TRUE, + first_sample_nd_value = 0, + ignore_below_loq_after_first_nd = TRUE +) +} +\arguments{ +\item{res_raw}{Character vector of a residue time series, or matrix of +residue values with rows representing depth profiles for a specific sampling +time, and columns representing time series of residues at the same depth. +Values below the limit of detection (lod) have to be coded as "nd", values +between the limit of detection and the limit of quantification, if any, have +to be coded as "nq". Samples not analysed have to be coded as "na". All +values that are not "na", "nd" or "nq" have to be coercible to numeric} + +\item{lod}{Limit of detection (numeric)} + +\item{loq}{Limit of quantification(numeric). Must be specified if the FOCUS rule to +stop after the first non-detection is to be applied} + +\item{time_zero_presence}{Do we assume that residues occur at time zero? +This only affects samples from the first sampling time that have been +reported as "nd" (not detected).} + +\item{set_first_sample_nd}{Should the first sample be set to "first_sample_nd_value" +in case it is a non-detection?} + +\item{first_sample_nd_value}{Value to be used for the first sample if it is a non-detection} + +\item{ignore_below_loq_after_first_nd}{Should we ignore values below the LOQ after the first +non-detection that occurs after the quantified values?} +} +\value{ +A numeric vector, if a vector was supplied, or a numeric matrix otherwise +} +\description{ +This function automates replacing unquantified values in residue time and +depth series. For time series, the function performs part of the residue +processing proposed in the FOCUS kinetics guidance for parent compounds +and metabolites. For two-dimensional residue series over time and depth, +it automates the proposal of Boesten et al (2015). +} +\section{Functions}{ +\itemize{ +\item \code{set_nd_nq_focus()}: Set non-detects in residue time series according to FOCUS rules + +}} +\examples{ +# FOCUS (2014) p. 75/76 and 131/132 +parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd") +set_nd_nq(parent_1, 0.02) +parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd") +set_nd_nq(parent_2, 0.02) +set_nd_nq_focus(parent_2, 0.02, loq = 0.05) +parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd") +set_nd_nq(parent_3, 0.02) +set_nd_nq_focus(parent_3, 0.02, loq = 0.05) +metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd") +set_nd_nq(metabolite, 0.02) +set_nd_nq_focus(metabolite, 0.02, 0.05) +# +# Boesten et al. (2015), p. 57/58 +table_8 <- matrix( + c(10, 10, rep("nd", 4), + 10, 10, rep("nq", 2), rep("nd", 2), + 10, 10, 10, "nq", "nd", "nd", + "nq", 10, "nq", rep("nd", 3), + "nd", "nq", "nq", rep("nd", 3), + rep("nd", 6), rep("nd", 6)), + ncol = 6, byrow = TRUE) +set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE) +table_10 <- matrix( + c(10, 10, rep("nd", 4), + 10, 10, rep("nd", 4), + 10, 10, 10, rep("nd", 3), + "nd", 10, rep("nd", 4), + rep("nd", 18)), + ncol = 6, byrow = TRUE) +set_nd_nq(table_10, 0.5, time_zero_presence = TRUE) +} +\references{ +Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H. +J. and Pol, J. W. (2015). Leaching of plant protection products and their +transformation products; Proposals for improving the assessment of leaching +to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra +Wageningen UR (University & Research centre) + +FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251 +} diff --git a/man/status.Rd b/man/status.Rd new file mode 100644 index 00000000..1cadbfcc --- /dev/null +++ b/man/status.Rd @@ -0,0 +1,44 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/status.R +\name{status} +\alias{status} +\alias{status.mmkin} +\alias{print.status.mmkin} +\alias{status.mhmkin} +\alias{print.status.mhmkin} +\title{Method to get status information for fit array objects} +\usage{ +status(object, ...) + +\method{status}{mmkin}(object, ...) + +\method{print}{status.mmkin}(x, ...) + +\method{status}{mhmkin}(object, ...) + +\method{print}{status.mhmkin}(x, ...) +} +\arguments{ +\item{object}{The object to investigate} + +\item{\dots}{For potential future extensions} + +\item{x}{The object to be printed} +} +\value{ +An object with the same dimensions as the fit array +suitable printing method. +} +\description{ +Method to get status information for fit array objects +} +\examples{ +\dontrun{ +fits <- mmkin( + c("SFO", "FOMC"), + list("FOCUS A" = FOCUS_2006_A, + "FOCUS B" = FOCUS_2006_C), + quiet = TRUE) +status(fits) +} +} diff --git a/man/summary.mkinfit.Rd b/man/summary.mkinfit.Rd index 24991d71..b6c1fb87 100644 --- a/man/summary.mkinfit.Rd +++ b/man/summary.mkinfit.Rd @@ -60,7 +60,7 @@ values. } \examples{ - summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE)) + summary(mkinfit("SFO", FOCUS_2006_A, quiet = TRUE)) } \references{ diff --git a/man/summary.mmkin.Rd b/man/summary.mmkin.Rd new file mode 100644 index 00000000..32e5824f --- /dev/null +++ b/man/summary.mmkin.Rd @@ -0,0 +1,36 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/summary.mmkin.R +\name{summary.mmkin} +\alias{summary.mmkin} +\alias{print.summary.mmkin} +\title{Summary method for class "mmkin"} +\usage{ +\method{summary}{mmkin}(object, conf.level = 0.95, ...) + +\method{print}{summary.mmkin}(x, digits = max(3, getOption("digits") - 3), ...) +} +\arguments{ +\item{object}{an object of class \link{mmkin}} + +\item{conf.level}{confidence level for testing parameters} + +\item{\dots}{optional arguments passed to methods like \code{print}.} + +\item{x}{an object of class \code{summary.mmkin}.} + +\item{digits}{number of digits to use for printing} +} +\description{ +Shows status information on the \link{mkinfit} objects contained in the object +and gives an overview of ill-defined parameters calculated by \link{illparms}. +} +\examples{ + +fits <- mmkin( + c("SFO", "FOMC"), + list("FOCUS A" = FOCUS_2006_A, + "FOCUS C" = FOCUS_2006_C), + quiet = TRUE, cores = 1) + summary(fits) + +} diff --git a/man/summary.saem.mmkin.Rd b/man/summary.saem.mmkin.Rd index 67cb3cbb..fb099899 100644 --- 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b/tests/testthat/illparms_hfits_synth.txt @@ -0,0 +1,8 @@ + error +degradation const + SFO + FOMC sd(log_alpha), sd(log_beta) + error +degradation tc + SFO sd(parent_0) + FOMC sd(parent_0), sd(log_alpha), sd(log_beta) diff --git a/tests/testthat/print_dfop_nlme_1.txt b/tests/testthat/print_dfop_nlme_1.txt index 1092821d..ccb43b86 100644 --- a/tests/testthat/print_dfop_nlme_1.txt +++ b/tests/testthat/print_dfop_nlme_1.txt @@ -8,17 +8,23 @@ d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * Data: 270 observations of 1 variable(s) grouped in 15 datasets -Log-likelihood: -612 +Log-likelihood: -695 Fixed effects: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) parent_0 log_k1 log_k2 g_qlogis - 100.1 -2.7 -4.1 -0.5 + 100.1 -2.7 -4.1 -0.4 Random effects: Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) Level: ds Structure: Diagonal parent_0 log_k1 log_k2 g_qlogis Residual -StdDev: 0.4 0.3 0.2 0.2 2 +StdDev: 2 0.3 0.2 0.2 1 +Variance function: + Structure: Constant plus proportion of variance covariate + Formula: ~fitted(.) + Parameter estimates: + const prop + 0.9227472 -0.0480500 diff --git a/tests/testthat/print_fits_synth_const.txt b/tests/testthat/print_fits_synth_const.txt new file mode 100644 index 00000000..2ea1f133 --- /dev/null +++ b/tests/testthat/print_fits_synth_const.txt @@ -0,0 +1,11 @@ +<mmkin> object +Status of individual fits: + + dataset +model 1 2 3 4 5 6 + SFO OK OK OK OK OK OK + FOMC C C OK OK OK OK + +C: Optimisation did not converge: +false convergence (8) +OK: No warnings diff --git a/tests/testthat/print_hfits_synth.txt b/tests/testthat/print_hfits_synth.txt new file mode 100644 index 00000000..9af1cbcd --- /dev/null +++ b/tests/testthat/print_hfits_synth.txt @@ -0,0 +1,9 @@ +<mhmkin> object +Status of individual fits: + + error +degradation const tc + SFO OK OK + FOMC OK OK + +OK: Fit terminated successfully diff --git a/tests/testthat/print_multistart_biphasic.txt b/tests/testthat/print_multistart_biphasic.txt new file mode 100644 index 00000000..b4344f22 --- /dev/null +++ b/tests/testthat/print_multistart_biphasic.txt @@ -0,0 +1,4 @@ +<multistart> object with 8 fits: +OK + 8 +OK: Fit terminated successfully diff --git a/tests/testthat/print_sfo_saem_1.txt b/tests/testthat/print_sfo_saem_1.txt index a11e1e96..34eea058 100644 --- a/tests/testthat/print_sfo_saem_1.txt +++ b/tests/testthat/print_sfo_saem_1.txt @@ -7,13 +7,13 @@ Data: Likelihood computed by importance sampling AIC BIC logLik - 1311 1315 -649 + 1312 1316 -650 Fitted parameters: estimate lower upper -parent_0 1e+02 99.13 1e+02 +parent_0 1e+02 99.28 1e+02 k_parent 4e-02 0.03 4e-02 a.1 9e-01 0.75 1e+00 b.1 5e-02 0.04 5e-02 -SD.parent_0 7e-01 -1.09 3e+00 +SD.parent_0 2e-01 -6.33 7e+00 SD.k_parent 3e-01 0.20 4e-01 diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R index 62cdf78e..777c998a 100644 --- a/tests/testthat/setup_script.R +++ b/tests/testthat/setup_script.R @@ -8,31 +8,18 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) { n_cores <- 1 } -# We are only allowed one core on travis, but they also set NOT_CRAN=true -if (Sys.getenv("TRAVIS") != "") n_cores = 1 +# Use the two available cores on travis +if (Sys.getenv("TRAVIS") != "") n_cores = 2 # On Windows we would need to make a cluster first if (Sys.info()["sysname"] == "Windows") n_cores = 1 -# We set up some models and fits with nls for comparisons -SFO_trans <- function(t, parent_0, log_k_parent_sink) { - parent_0 * exp(- exp(log_k_parent_sink) * t) -} -SFO_notrans <- function(t, parent_0, k_parent_sink) { - parent_0 * exp(- k_parent_sink * t) -} -f_1_nls_trans <- nls(value ~ SFO_trans(time, parent_0, log_k_parent_sink), - data = FOCUS_2006_A, - start = list(parent_0 = 100, log_k_parent_sink = log(0.1))) -f_1_nls_notrans <- nls(value ~ SFO_notrans(time, parent_0, k_parent_sink), - data = FOCUS_2006_A, - start = list(parent_0 = 100, k_parent_sink = 0.1)) - +# Very simple example fits f_1_mkin_trans <- mkinfit("SFO", FOCUS_2006_A, quiet = TRUE) f_1_mkin_notrans <- mkinfit("SFO", FOCUS_2006_A, quiet = TRUE, transform_rates = FALSE) -# mmkin object of parent fits for tests +# mmkin object of parent fits models <- c("SFO", "FOMC", "DFOP", "HS") fits <- suppressWarnings( # FOCUS A FOMC was, it seems, in testthat output mmkin(models, @@ -72,9 +59,8 @@ DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data f_2_mkin <- mkinfit("DFOP", DFOP_par_c, quiet = TRUE) f_2_nls <- nls(value ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = subset(DFOP_par_c, name == "parent")) -f_2_anova <- lm(value ~ as.factor(time), data = subset(DFOP_par_c, name == "parent")) -# Two metabolites +# mkinfit with two metabolites m_synth_SFO_lin <- mkinmod( parent = mkinsub("SFO", "M1"), M1 = mkinsub("SFO", "M2"), @@ -137,7 +123,7 @@ set.seed(123456) ds_dfop <- lapply(1:n, function(i) { ds_mean <- mkinpredict(DFOP, dfop_parms[i, ], c(parent = dfop_pop$parent_0), sampling_times) - add_err(ds_mean, const, n = 1)[[1]] + add_err(ds_mean, tc, n = 1)[[1]] }) set.seed(123456) @@ -184,20 +170,22 @@ ds_biphasic <- lapply(ds_biphasic_mean, function(ds) { # Mixed model fits mmkin_sfo_1 <- mmkin("SFO", ds_sfo, quiet = TRUE, error_model = "tc", cores = n_cores) -mmkin_dfop_1 <- mmkin("DFOP", ds_dfop, quiet = TRUE, cores = n_cores) +mmkin_dfop_1 <- mmkin("DFOP", ds_dfop, quiet = TRUE, cores = n_cores, + error_model = "tc") + mmkin_biphasic <- mmkin(list("DFOP-SFO" = DFOP_SFO), ds_biphasic, quiet = TRUE, cores = n_cores, control = list(eval.max = 500, iter.max = 400), error_model = "tc") # nlme -dfop_nlme_1 <- nlme(mmkin_dfop_1) +dfop_nlme_1 <- suppressWarnings(nlme(mmkin_dfop_1)) nlme_biphasic <- suppressWarnings(nlme(mmkin_biphasic)) # saemix sfo_saem_1 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "saemix") - -dfop_saemix_1 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin") -dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix") +sfo_saem_1_reduced <- update(sfo_saem_1, no_random_effect = "parent_0") +dfop_saemix_1 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin", + no_random_effect = "parent_0") saem_biphasic_m <- saem(mmkin_biphasic, transformations = "mkin", quiet = TRUE) saem_biphasic_s <- saem(mmkin_biphasic, transformations = "saemix", quiet = TRUE) diff --git a/tests/testthat/summary_dfop_nlme_1.txt b/tests/testthat/summary_dfop_nlme_1.txt index 9da3fb1b..cfee552a 100644 --- a/tests/testthat/summary_dfop_nlme_1.txt +++ b/tests/testthat/summary_dfop_nlme_1.txt @@ -14,13 +14,13 @@ Data: Model predictions using solution type analytical -Fitted in test time 0 s using 3 iterations +Fitted in test time 0 s using 5 iterations -Variance model: Constant variance +Variance model: Two-component variance function Mean of starting values for individual parameters: parent_0 log_k1 log_k2 g_qlogis - 100.06 -2.68 -4.16 0.01 + 100.2 -2.6 -4.2 0.1 Fixed degradation parameter values: None @@ -28,36 +28,42 @@ None Results: AIC BIC logLik - 1242 1274 -612 + 1410 1446 -695 Optimised, transformed parameters with symmetric confidence intervals: lower est. upper -parent_0 99.6 100.1 100.6 -log_k1 -2.9 -2.7 -2.4 +parent_0 98.7 100.1 101.5 +log_k1 -2.9 -2.7 -2.5 log_k2 -4.2 -4.1 -4.0 -g_qlogis -0.7 -0.5 -0.2 +g_qlogis -0.7 -0.4 -0.2 Correlation: pr_0 lg_1 lg_2 -log_k1 0.2 +log_k1 0.3 log_k2 0.1 0.2 -g_qlogis -0.2 -0.5 -0.4 +g_qlogis -0.1 -0.5 -0.4 Random effects: Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) Level: ds Structure: Diagonal parent_0 log_k1 log_k2 g_qlogis Residual -StdDev: 0.4 0.3 0.2 0.2 2 +StdDev: 2 0.3 0.2 0.2 1 +Variance function: + Structure: Constant plus proportion of variance covariate + Formula: ~fitted(.) + Parameter estimates: + const prop + 0.9227472 -0.0480500 Backtransformed parameters with asymmetric confidence intervals: lower est. upper -parent_0 1e+02 1e+02 1e+02 -k1 6e-02 7e-02 9e-02 -k2 1e-02 2e-02 2e-02 -g 3e-01 4e-01 5e-01 +parent_0 98.69 1e+02 1e+02 +k1 0.06 7e-02 9e-02 +k2 0.01 2e-02 2e-02 +g 0.34 4e-01 5e-01 Estimated disappearance times: DT50 DT90 DT50back DT50_k1 DT50_k2 -parent 23 111 33 10 42 +parent 23 111 33 10 43 diff --git a/tests/testthat/summary_hfit_sfo_tc.txt b/tests/testthat/summary_hfit_sfo_tc.txt new file mode 100644 index 00000000..49765187 --- /dev/null +++ b/tests/testthat/summary_hfit_sfo_tc.txt @@ -0,0 +1,61 @@ +saemix version used for fitting: Dummy 0.0 for testing +mkin version used for pre-fitting: Dummy 0.0 for testing +R version used for fitting: Dummy R version for testing +Date of fit: Dummy date for testing +Date of summary: Dummy date for testing + +Equations: +d_parent/dt = - k_parent * parent + +Data: +106 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in test time 0 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Mean of starting values for individual parameters: + parent_0 log_k_parent + 101 -3 + +Fixed degradation parameter values: +None + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 533 531 -261 + +Optimised parameters: + est. lower upper +parent_0 101.01 99.57 102.45 +log_k_parent -3.32 -3.53 -3.11 +a.1 0.90 0.64 1.17 +b.1 0.05 0.04 0.06 +SD.log_k_parent 0.27 0.11 0.42 + +Correlation: + pr_0 +log_k_parent 0.1 + +Random effects: + est. lower upper +SD.log_k_parent 0.3 0.1 0.4 + +Variance model: + est. lower upper +a.1 0.90 0.64 1.17 +b.1 0.05 0.04 0.06 + +Backtransformed parameters: + est. lower upper +parent_0 1e+02 1e+02 1e+02 +k_parent 4e-02 3e-02 4e-02 + +Estimated disappearance times: + DT50 DT90 +parent 19 64 diff --git a/tests/testthat/summary_parent_FOCUS_2006.txt b/tests/testthat/summary_parent_FOCUS_2006.txt new file mode 100644 index 00000000..418476c0 --- /dev/null +++ b/tests/testthat/summary_parent_FOCUS_2006.txt @@ -0,0 +1,20 @@ +Error model: Constant variance +Fitted in test time 0 s + +Status: + dataset +model FOCUS_C FOCUS_D + SFO OK OK + FOMC OK OK + DFOP OK OK + HS OK OK + +OK: No warnings + +Ill-defined parameters: + dataset +model FOCUS_C FOCUS_D + SFO + FOMC alpha, beta + DFOP g + HS k2 diff --git a/tests/testthat/summary_saem_biphasic_s.txt b/tests/testthat/summary_saem_biphasic_s.txt index 6b203991..7c337843 100644 --- a/tests/testthat/summary_saem_biphasic_s.txt +++ b/tests/testthat/summary_saem_biphasic_s.txt @@ -38,13 +38,21 @@ Likelihood computed by importance sampling 2334 2344 -1153 Optimised parameters: - est. lower upper -parent_0 1e+02 1e+02 1e+02 -k_m1 7e-03 6e-03 7e-03 -f_parent_to_m1 5e-01 4e-01 5e-01 -k1 1e-01 9e-02 1e-01 -k2 2e-02 2e-02 3e-02 -g 5e-01 5e-01 5e-01 + est. lower upper +parent_0 1e+02 1e+02 1e+02 +k_m1 7e-03 6e-03 7e-03 +f_parent_to_m1 5e-01 4e-01 5e-01 +k1 1e-01 9e-02 1e-01 +k2 2e-02 2e-02 3e-02 +g 5e-01 5e-01 5e-01 +a.1 9e-01 8e-01 1e+00 +b.1 5e-02 5e-02 6e-02 +SD.parent_0 3e-02 -5e+01 5e+01 +SD.k_m1 2e-01 1e-01 3e-01 +SD.f_parent_to_m1 3e-01 2e-01 4e-01 +SD.k1 4e-01 2e-01 5e-01 +SD.k2 3e-01 2e-01 5e-01 +SD.g 2e-01 6e-02 4e-01 Correlation: pr_0 k_m1 f___ k1 k2 diff --git a/tests/testthat/test_confidence.R b/tests/testthat/test_confidence.R index 36e9738d..6c645ca4 100644 --- a/tests/testthat/test_confidence.R +++ b/tests/testthat/test_confidence.R @@ -1,5 +1,19 @@ context("Confidence intervals and p-values") +# We set up some models and fits with nls for comparisons +SFO_trans <- function(t, parent_0, log_k_parent_sink) { + parent_0 * exp(- exp(log_k_parent_sink) * t) +} +SFO_notrans <- function(t, parent_0, k_parent_sink) { + parent_0 * exp(- k_parent_sink * t) +} +f_1_nls_trans <- nls(value ~ SFO_trans(time, parent_0, log_k_parent_sink), + data = FOCUS_2006_A, + start = list(parent_0 = 100, log_k_parent_sink = log(0.1))) +f_1_nls_notrans <- nls(value ~ SFO_notrans(time, parent_0, k_parent_sink), + data = FOCUS_2006_A, + start = list(parent_0 = 100, k_parent_sink = 0.1)) + test_that("The confint method 'quadratic' is consistent with the summary", { expect_equivalent( confint(fit_nw_1, parm = "parent_0", method = "quadratic"), diff --git a/tests/testthat/test_mhmkin.R b/tests/testthat/test_mhmkin.R new file mode 100644 index 00000000..fc588473 --- /dev/null +++ b/tests/testthat/test_mhmkin.R @@ -0,0 +1,48 @@ +context("Batch fitting and diagnosing hierarchical kinetic models") + +test_that("Multiple hierarchical kinetic models can be fitted and diagnosed", { + + skip_on_cran() + fits_synth_const <- suppressWarnings( + mmkin(c("SFO", "FOMC"), ds_sfo[1:6], cores = n_cores, quiet = TRUE)) + + fits_synth_tc <- suppressWarnings( + update(fits_synth_const, error_model = "tc")) + + hfits <- mhmkin(list(fits_synth_const, fits_synth_tc)) + + expect_known_output( + print(hfits), + "print_hfits_synth.txt") + + expect_known_output( + print(illparms(hfits)), + "illparms_hfits_synth.txt") + + expect_equal(which.min(AIC(hfits)), 3) + expect_equal(which.min(BIC(hfits)), 3) + + hfit_sfo_tc <- update(hfits[["SFO", "tc"]], + covariance.model = diag(c(0, 1))) + expect_equal(illparms(hfit_sfo_tc), character(0)) + + test_summary <- summary(hfit_sfo_tc) + test_summary$saemixversion <- "Dummy 0.0 for testing" + test_summary$mkinversion <- "Dummy 0.0 for testing" + test_summary$Rversion <- "Dummy R version for testing" + test_summary$date.fit <- "Dummy date for testing" + test_summary$date.summary <- "Dummy date for testing" + test_summary$time <- c(elapsed = "test time 0") + + expect_known_output(print(test_summary, digits = 1), + "summary_hfit_sfo_tc.txt") + + # It depends on the platform exactly which of the + # SFO datasets fail to converge with FOMC + skip_on_travis() + + expect_known_output( + print(fits_synth_const), + "print_fits_synth_const.txt") + +}) diff --git a/tests/testthat/test_mixed.R b/tests/testthat/test_mixed.R index 6fb06656..e005c982 100644 --- a/tests/testthat/test_mixed.R +++ b/tests/testthat/test_mixed.R @@ -1,5 +1,11 @@ context("Nonlinear mixed-effects models") +# Round error model parameters as they are not rounded in print methods +dfop_nlme_1$modelStruct$varStruct$const <- + signif(dfop_nlme_1$modelStruct$varStruct$const, 3) +dfop_nlme_1$modelStruct$varStruct$prop <- + signif(dfop_nlme_1$modelStruct$varStruct$prop, 4) + test_that("Print methods work", { expect_known_output(print(fits[, 2:3], digits = 2), "print_mmkin_parent.txt") expect_known_output(print(mixed(mmkin_sfo_1), digits = 2), "print_mmkin_sfo_1_mixed.txt") diff --git a/tests/testthat/test_multistart.R b/tests/testthat/test_multistart.R new file mode 100644 index 00000000..56eb140c --- /dev/null +++ b/tests/testthat/test_multistart.R @@ -0,0 +1,38 @@ +context("Multistart method for saem.mmkin models") + +test_that("multistart works for saem.mmkin models", { + set.seed(123456) + saem_sfo_s_multi <- multistart(sfo_saem_1_reduced, n = 8, cores = n_cores, + no_random_effect = "parent_0") + anova_sfo <- anova(sfo_saem_1, + sfo_saem_1_reduced, + best(saem_sfo_s_multi), + test = TRUE + ) + expect_true(anova_sfo[3, "Pr(>Chisq)"] > 0.5) + + skip_on_cran() # Save CRAN time + set.seed(123456) + saem_biphasic_m_multi <- multistart(saem_biphasic_m, n = 8, + cores = n_cores) + expect_known_output(print(saem_biphasic_m_multi), + file = "print_multistart_biphasic.txt") + + anova_biphasic <- anova(saem_biphasic_m, + best(saem_biphasic_m_multi)) + + expect_true(anova_biphasic[2, "AIC"] < anova_biphasic[1, "AIC"]) + skip_on_travis() # Plots are platform dependent + + llhist_sfo <- function() llhist(saem_sfo_s_multi) + parplot_sfo <- function() parplot(saem_sfo_s_multi, ylim = c(0.5, 2)) + vdiffr::expect_doppelganger("llhist for sfo fit", llhist_sfo) + vdiffr::expect_doppelganger("parplot for sfo fit", parplot_sfo) + + llhist_biphasic <- function() llhist(saem_biphasic_m_multi) + parplot_biphasic <- function() parplot(saem_biphasic_m_multi, + ylim = c(0.5, 2)) + + vdiffr::expect_doppelganger("llhist for biphasic saemix fit", llhist_biphasic) + vdiffr::expect_doppelganger("parplot for biphasic saemix fit", parplot_biphasic) +}) diff --git a/tests/testthat/test_saemix_parent.R b/tests/testthat/test_saemix_parent.R index 731228d9..39efa18f 100644 --- a/tests/testthat/test_saemix_parent.R +++ b/tests/testthat/test_saemix_parent.R @@ -4,37 +4,81 @@ test_that("Parent fits using saemix are correctly implemented", { skip_on_cran() expect_error(saem(fits), "Only row objects") - # Some fits were done in the setup script + + # SFO + # mmkin_sfo_1 was generated in the setup script + # We did not introduce variance of parent_0 in the data generation + # This is correctly detected + expect_equal(illparms(sfo_saem_1), "sd(parent_0)") + # So we have also done a fit without this variance + expect_equal(illparms(sfo_saem_1_reduced), character(0)) + + # We cannot currently do the fit with completely fixed initial values mmkin_sfo_2 <- update(mmkin_sfo_1, fixed_initials = c(parent = 100)) + sfo_saem_3 <- expect_error(saem(mmkin_sfo_2, quiet = TRUE), "at least two parameters") + + # We get an error if we do not supply a suitable model specification expect_error(update(mmkin_sfo_1, models = c("SFOOO")), "Please supply models.*") - sfo_saem_2 <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "mkin") - sfo_saem_3 <- expect_error(saem(mmkin_sfo_2, quiet = TRUE), "at least two parameters") - s_sfo_s1 <- summary(sfo_saem_1) - s_sfo_s2 <- summary(sfo_saem_2) + sfo_saem_1_mkin <- saem(mmkin_sfo_1, quiet = TRUE, transformations = "mkin") + expect_equal(illparms(sfo_saem_1_mkin), "sd(parent_0)") + sfo_saem_1_reduced_mkin <- update(sfo_saem_1_mkin, no_random_effect = "parent_0") + + # The endpoints obtained do not depend on the transformation + expect_equal(endpoints(sfo_saem_1), endpoints(sfo_saem_1_mkin), tol = 0.01) + expect_equal(endpoints(sfo_saem_1_reduced), endpoints(sfo_saem_1_reduced_mkin), tol = 0.01) + + s_sfo_saem_1 <- summary(sfo_saem_1) + s_sfo_saem_1_reduced <- summary(sfo_saem_1_reduced) + s_sfo_saem_1_mkin <- summary(sfo_saem_1_mkin) + s_sfo_saem_1_reduced_mkin <- summary(sfo_saem_1_reduced_mkin) sfo_nlme_1 <- expect_warning(nlme(mmkin_sfo_1), "not converge") - s_sfo_n <- summary(sfo_nlme_1) + s_sfo_nlme_1 <- summary(sfo_nlme_1) # Compare with input - expect_equal(round(s_sfo_s2$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) + expect_equal(round(s_sfo_saem_1$confint_ranef["SD.k_parent", "est."], 1), 0.3) + expect_equal(round(s_sfo_saem_1_mkin$confint_ranef["SD.log_k_parent", "est."], 1), 0.3) # k_parent is a bit different from input 0.03 here - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), 0.035) - expect_equal(round(s_sfo_s2$confint_back["k_parent", "est."], 3), 0.035) + expect_equal(round(s_sfo_saem_1$confint_back["k_parent", "est."], 3), 0.035) + expect_equal(round(s_sfo_saem_1_mkin$confint_back["k_parent", "est."], 3), 0.035) # But the result is pretty unanimous between methods - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), - round(s_sfo_s2$confint_back["k_parent", "est."], 3)) - expect_equal(round(s_sfo_s1$confint_back["k_parent", "est."], 3), - round(s_sfo_n$confint_back["k_parent", "est."], 3)) - + expect_equal(round(s_sfo_saem_1_reduced$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_saem_1_mkin$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_saem_1_reduced_mkin$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + expect_equal(round(s_sfo_nlme_1$confint_back["k_parent", "est."], 3), + round(s_sfo_saem_1$confint_back["k_parent", "est."], 3)) + + # Compare fits with heavy rounding to avoid platform dependent results + anova_sfo <- anova( + sfo_saem_1, sfo_saem_1_reduced, + sfo_saem_1_mkin, sfo_saem_1_reduced_mkin, + test = TRUE) + anova_sfo_rounded <- round(anova_sfo, 0) + expect_known_output(print(anova_sfo_rounded), file = "anova_sfo_saem.txt") + + # Check the influence of an invented covariate + set.seed(123456) # In my first attempt I hit a false positive by chance... + pH <- data.frame(pH = runif(15, 5, 8), row.names = as.character(1:15)) + sfo_saem_pH <- update(sfo_saem_1_reduced_mkin, covariates = pH, + covariate_models = list(log_k_parent ~ pH)) + # We expect that this is not significantly better, as the covariate values were completely random + expect_true(anova(sfo_saem_1_reduced_mkin, sfo_saem_pH, test = TRUE)[2, "Pr(>Chisq)"] > 0.05) + + # FOMC mmkin_fomc_1 <- mmkin("FOMC", ds_fomc, quiet = TRUE, error_model = "tc", cores = n_cores) - fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE) + fomc_saem_1 <- saem(mmkin_fomc_1, quiet = TRUE, transformations = "saemix", no_random_effect = "parent_0") + fomc_saem_2 <- update(fomc_saem_1, transformations = "mkin") ci_fomc_s1 <- summary(fomc_saem_1)$confint_back fomc_pop <- as.numeric(fomc_pop) expect_true(all(ci_fomc_s1[, "lower"] < fomc_pop)) expect_true(all(ci_fomc_s1[, "upper"] > fomc_pop)) + expect_equal(endpoints(fomc_saem_1), endpoints(fomc_saem_2), tol = 0.01) mmkin_fomc_2 <- update(mmkin_fomc_1, state.ini = 100, fixed_initials = "parent") fomc_saem_2 <- saem(mmkin_fomc_2, quiet = TRUE, transformations = "mkin") @@ -43,62 +87,71 @@ test_that("Parent fits using saemix are correctly implemented", { expect_true(all(ci_fomc_s2[, "lower"] < fomc_pop[2:3])) expect_true(all(ci_fomc_s2[, "upper"] > fomc_pop[2:3])) + # DFOP + dfop_saemix_2 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix", + no_random_effect = "parent_0") + s_dfop_s1 <- summary(dfop_saemix_1) s_dfop_s2 <- summary(dfop_saemix_2) s_dfop_n <- summary(dfop_nlme_1) dfop_pop <- as.numeric(dfop_pop) - expect_true(all(s_dfop_s1$confint_back[, "lower"] < dfop_pop)) - expect_true(all(s_dfop_s1$confint_back[, "upper"] > dfop_pop)) + + # When using DFOP with mkin transformations, k1 and k2 are sometimes swapped + swap_k1_k2 <- function(p) c(p[1], p[3], p[2], 1 - p[4]) + expect_true(all(s_dfop_s1$confint_back[, "lower"] < swap_k1_k2(dfop_pop))) + expect_true(all(s_dfop_s1$confint_back[, "upper"] > swap_k1_k2(dfop_pop))) expect_true(all(s_dfop_s2$confint_back[, "lower"] < dfop_pop)) expect_true(all(s_dfop_s2$confint_back[, "upper"] > dfop_pop)) - dfop_mmkin_means_trans_tested <- mean_degparms(mmkin_dfop_1, test_log_parms = TRUE) - dfop_mmkin_means_trans <- apply(parms(mmkin_dfop_1, transformed = TRUE), 1, mean) - - dfop_mmkin_means_tested <- backtransform_odeparms(dfop_mmkin_means_trans_tested, mmkin_dfop_1$mkinmod) - dfop_mmkin_means <- backtransform_odeparms(dfop_mmkin_means_trans, mmkin_dfop_1$mkinmod) - - # We get < 20% deviations for parent_0 and k1 by averaging the transformed parameters - # If we average only parameters passing the t-test, the deviation for k2 is also < 20% - rel_diff_mmkin <- (dfop_mmkin_means - dfop_pop) / dfop_pop - rel_diff_mmkin_tested <- (dfop_mmkin_means_tested - dfop_pop) / dfop_pop - expect_true(all(rel_diff_mmkin[c("parent_0", "k1")] < 0.20)) - expect_true(all(rel_diff_mmkin_tested[c("parent_0", "k1", "k2")] < 0.20)) - - # We get < 20% deviations with transformations made in mkin - rel_diff_1 <- (s_dfop_s1$confint_back[, "est."] - dfop_pop) / dfop_pop + # We get < 20% deviations with transformations made in mkin (need to swap k1 and k2) + rel_diff_1 <- (swap_k1_k2(s_dfop_s1$confint_back[, "est."]) - dfop_pop) / dfop_pop expect_true(all(rel_diff_1 < 0.20)) # We get < 20% deviations with transformations made in saemix rel_diff_2 <- (s_dfop_s2$confint_back[, "est."] - dfop_pop) / dfop_pop expect_true(all(rel_diff_2 < 0.2)) + # SFORB + mmkin_sforb_1 <- mmkin("SFORB", ds_dfop, quiet = TRUE, cores = n_cores) + sforb_saemix_1 <- saem(mmkin_sforb_1, quiet = TRUE, + no_random_effect = c("parent_free_0"), + transformations = "mkin") + sforb_saemix_2 <- saem(mmkin_sforb_1, quiet = TRUE, + no_random_effect = c("parent_free_0"), + transformations = "saemix") + expect_equal( + log(endpoints(dfop_saemix_1)$distimes[1:2]), + log(endpoints(sforb_saemix_1)$distimes[1:2]), tolerance = 0.03) + expect_equal( + log(endpoints(sforb_saemix_1)$distimes[1:2]), + log(endpoints(sforb_saemix_2)$distimes[1:2]), tolerance = 0.01) + mmkin_hs_1 <- mmkin("HS", ds_hs, quiet = TRUE, error_model = "const", cores = n_cores) hs_saem_1 <- saem(mmkin_hs_1, quiet = TRUE) + hs_saem_2 <- saem(mmkin_hs_1, quiet = TRUE, transformations = "mkin") + expect_equal(endpoints(hs_saem_1), endpoints(hs_saem_2), tol = 0.01) ci_hs_s1 <- summary(hs_saem_1)$confint_back hs_pop <- as.numeric(hs_pop) - # expect_true(all(ci_hs_s1[, "lower"] < hs_pop)) # k1 is overestimated + #expect_true(all(ci_hs_s1[, "lower"] < hs_pop)) # k1 is overestimated expect_true(all(ci_hs_s1[, "upper"] > hs_pop)) mmkin_hs_2 <- update(mmkin_hs_1, state.ini = 100, fixed_initials = "parent") - hs_saem_2 <- saem(mmkin_hs_2, quiet = TRUE) - ci_hs_s2 <- summary(hs_saem_2)$confint_back - - #expect_true(all(ci_hs_s2[, "lower"] < hs_pop[2:4])) # k1 again overestimated - expect_true(all(ci_hs_s2[, "upper"] > hs_pop[2:4])) + hs_saem_3 <- saem(mmkin_hs_2, quiet = TRUE) + ci_hs_s3 <- summary(hs_saem_3)$confint_back - # HS would likely benefit from implemenation of transformations = "saemix" + #expect_true(all(ci_hs_s3[, "lower"] < hs_pop[2:4])) # k1 again overestimated + expect_true(all(ci_hs_s3[, "upper"] > hs_pop[2:4])) }) test_that("We can also use mkin solution methods for saem", { expect_error(saem(mmkin_dfop_1, quiet = TRUE, transformations = "saemix", solution_type = "analytical"), "saemix transformations is only supported if an analytical solution is implemented" ) - skip_on_cran() # This still takes almost 2.5 minutes although we do not solve ODEs + skip("This still takes almost 2.5 minutes although we do not solve ODEs") dfop_saemix_3 <- saem(mmkin_dfop_1, quiet = TRUE, transformations = "mkin", - solution_type = "analytical") + solution_type = "analytical", no_random_effect = "parent_0") distimes_dfop <- endpoints(dfop_saemix_1)$distimes distimes_dfop_analytical <- endpoints(dfop_saemix_3)$distimes rel_diff <- abs(distimes_dfop_analytical - distimes_dfop) / distimes_dfop diff --git a/tests/testthat/test_set_nd.R b/tests/testthat/test_set_nd.R new file mode 100644 index 00000000..232e7c62 --- /dev/null +++ b/tests/testthat/test_set_nd.R @@ -0,0 +1,86 @@ +context("Processing of residue series") + +# FOCUS (2014) page 76 (parent) and page 132 (metabolite) + +parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd") +parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd") +parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd") +metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd") + +test_that("Simple residue series are processed as intended", { + + expect_equal(set_nd_nq(parent_1, 0.02), + c(.12, .09, .05, .03, .01, rep(NA, 5))) + + expect_equal(set_nd_nq(parent_2, 0.02, loq = 0.05), + c(.12, .09, .05, .03, .01, .01, .03, .01, NA, NA)) + + expect_equal(set_nd_nq(metabolite, 0.02, loq = 0.05), + c(NA, NA, .01, .03, .06, .1, .11, .1, .09, .05, .03, .01, NA)) + + expect_equal(set_nd_nq(c("nd", 1, 0.2, "nd"), 0.1), + c(NA, 1, 0.2, 0.05)) + +}) + +test_that("Simple residue series are processed as in the FOCUS guidance", { + + # Parent 1 + expect_error(set_nd_nq_focus(parent_1, 0.02), + "You need to specify an LOQ") + expect_equal(set_nd_nq_focus(parent_1, 0.02, 0.05), + c(.12, .09, .05, .03, .01, rep(NA, 5))) + + # Parent 2 + expect_equal(set_nd_nq_focus(parent_2, 0.02, loq = 0.05), + c(.12, .09, .05, .03, .01, rep(NA, 5))) + + # Parent 3 + expect_equal(set_nd_nq_focus(parent_3, 0.02, loq = 0.05), + c(.12, .09, .05, .03, .01, .01, .06, .01, NA, NA)) + + # Metabolite + expect_equal(set_nd_nq_focus(metabolite, 0.02, loq = 0.05), + c(0, NA, .01, .03, .06, .1, .11, .1, .09, .05, .03, .01, NA)) + +}) + +test_that("Examples Boesten et al. (2015, p. 57/58) are correctly processed", { + table_8 <- matrix( + c(10, 10, rep("nd", 4), + 10, 10, rep("nq", 2), rep("nd", 2), + 10, 10, 10, "nq", "nd", "nd", + "nq", 10, "nq", rep("nd", 3), + "nd", "nq", "nq", rep("nd", 3), + rep("nd", 6), rep("nd", 6)), + ncol = 6, byrow = TRUE) + table_8_processed <- set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE) + table_9 <- matrix( + c(10, 10, 0.25, 0.25, NA, NA, + 10, 10, 1, 1, 0.25, NA, + 10, 10, 10, 1, 0.25, NA, + 1, 10, 1, 0.25, NA, NA, + 0.25, 1, 1, 0.25, NA, NA, + NA, 0.25, 0.25, NA, NA, NA, + rep(NA, 6)), + ncol = 6, byrow = TRUE) + expect_equal(table_8_processed, table_9) + + table_10 <- matrix( + c(10, 10, rep("nd", 4), + 10, 10, rep("nd", 4), + 10, 10, 10, rep("nd", 3), + "nd", 10, rep("nd", 4), + rep("nd", 18)), + ncol = 6, byrow = TRUE) + table_10_processed <- set_nd_nq(table_10, 0.5, time_zero_presence = TRUE) + table_11 <- matrix( + c(10, 10, 0.25, rep(NA, 3), + 10, 10, 0.25, rep(NA, 3), + 10, 10, 10, 0.25, NA, NA, + 0.25, 10, 0.25, rep(NA, 3), + NA, 0.25, rep(NA, 4), + rep(NA, 12)), + ncol = 6, byrow = TRUE) + expect_equal(table_10_processed, table_11) +}) diff --git a/tests/testthat/test_summary.R b/tests/testthat/test_summary.R index 5cf6ac6b..87dc7de2 100644 --- a/tests/testthat/test_summary.R +++ b/tests/testthat/test_summary.R @@ -46,6 +46,12 @@ test_that("Summaries are reproducible", { expect_known_output(print(test_summary_3), "summary_DFOP_FOCUS_D_deSolve.txt") }) +test_that("Summaries of mmkin objects are reproducible", { + test_summary <- summary(fits[ , 2:3]) + test_summary$time <- c(elapsed = "test time 0") + expect_known_output(print(test_summary), "summary_parent_FOCUS_2006.txt") +}) + test_that("A fit generated with mkin 0.9.48.1 can be summarised", { # Generated with mkin 0.9.48.1 # SFO_SFO <- mkinmod(parent = list(type = "SFO", to = "m1"), diff --git a/tests/testthat/test_tests.R b/tests/testthat/test_tests.R index 39649223..caa0f70a 100644 --- a/tests/testthat/test_tests.R +++ b/tests/testthat/test_tests.R @@ -8,6 +8,7 @@ test_that("The lack-of-fit test works and can be reproduced using nls", { # This code is a slightly modified version of that given in Ritz and Streibig # (2008) Nonlinear Regression using R, p. 64 + f_2_anova <- lm(value ~ as.factor(time), data = subset(DFOP_par_c, name == "parent")) Q <- as.numeric(- 2 * (logLik(f_2_nls) - logLik(f_2_anova))) df.Q <- df.residual(f_2_nls) - df.residual(f_2_anova) p_nls <- 1 - pchisq(Q, df.Q) diff --git a/vignettes/FOCUS_L.html b/vignettes/FOCUS_L.html index 13d0d9eb..da6c11fe 100644 --- a/vignettes/FOCUS_L.html +++ b/vignettes/FOCUS_L.html @@ -1517,7 +1517,7 @@ div.tocify { <h1 class="title toc-ignore">Example evaluation of FOCUS Laboratory Data L1 to L3</h1> <h4 class="author">Johannes Ranke</h4> -<h4 class="date">Last change 18 May 2022 (rebuilt 2022-07-08)</h4> +<h4 class="date">Last change 18 May 2022 (rebuilt 2022-09-14)</h4> </div> @@ -1536,17 +1536,17 @@ FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)</code></pre> <p>Since mkin version 0.9-32 (July 2014), we can use shorthand notation like <code>"SFO"</code> for parent only degradation models. The following two lines fit the model and produce the summary report of the model fit. This covers the numerical analysis given in the FOCUS report.</p> <pre class="r"><code>m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE) summary(m.L1.SFO)</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:39 2022 -## Date of summary: Fri Jul 8 15:44:39 2022 +## Date of fit: Wed Sep 14 22:28:35 2022 +## Date of summary: Wed Sep 14 22:28:35 2022 ## ## Equations: ## d_parent/dt = - k_parent * parent ## ## Model predictions using solution type analytical ## -## Fitted using 133 model solutions performed in 0.029 s +## Fitted using 133 model solutions performed in 0.032 s ## ## Error model: Constant variance ## @@ -1578,9 +1578,9 @@ summary(m.L1.SFO)</code></pre> ## ## Parameter correlation: ## parent_0 log_k_parent sigma -## parent_0 1.000e+00 6.186e-01 -1.712e-09 -## log_k_parent 6.186e-01 1.000e+00 -3.237e-09 -## sigma -1.712e-09 -3.237e-09 1.000e+00 +## parent_0 1.000e+00 6.186e-01 -1.516e-09 +## log_k_parent 6.186e-01 1.000e+00 -3.124e-09 +## sigma -1.516e-09 -3.124e-09 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. @@ -1627,25 +1627,27 @@ summary(m.L1.SFO)</code></pre> <pre class="r"><code>mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")</code></pre> <p><img src="data:image/png;base64,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" /><!-- --></p> <p>For comparison, the FOMC model is fitted as well, and the <span class="math inline"><em>χ</em><sup>2</sup></span> error level is checked.</p> -<pre class="r"><code>m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE) -plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")</code></pre> -<p><img src="data:image/png;base64,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" /><!-- --></p> +<pre class="r"><code>m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)</code></pre> +<pre><code>## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge: +## false convergence (8)</code></pre> +<pre class="r"><code>plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")</code></pre> +<p><img src="data:image/png;base64,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" /><!-- --></p> <pre class="r"><code>summary(m.L1.FOMC, data = FALSE)</code></pre> <pre><code>## Warning in sqrt(diag(covar)): NaNs produced</code></pre> <pre><code>## Warning in sqrt(1/diag(V)): NaNs produced</code></pre> <pre><code>## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is ## doubtful</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:39 2022 -## Date of summary: Fri Jul 8 15:44:40 2022 +## Date of fit: Wed Sep 14 22:28:35 2022 +## Date of summary: Wed Sep 14 22:28:35 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 357 model solutions performed in 0.071 s +## Fitted using 369 model solutions performed in 0.081 s ## ## Error model: Constant variance ## @@ -1666,34 +1668,39 @@ plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")</code></ ## Fixed parameter values: ## None ## +## +## Warning(s): +## Optimisation did not converge: +## false convergence (8) +## ## Results: ## -## AIC BIC logLik -## 95.88804 99.44953 -43.94402 +## AIC BIC logLik +## 95.88781 99.44929 -43.9439 ## ## Optimised, transformed parameters with symmetric confidence intervals: ## Estimate Std. Error Lower Upper ## parent_0 92.47 1.2820 89.720 95.220 -## log_alpha 11.37 NaN NaN NaN -## log_beta 13.72 NaN NaN NaN -## sigma 2.78 0.4621 1.789 3.771 +## log_alpha 13.78 NaN NaN NaN +## log_beta 16.13 NaN NaN NaN +## sigma 2.78 0.4598 1.794 3.766 ## ## Parameter correlation: ## parent_0 log_alpha log_beta sigma -## parent_0 1.0000000 NaN NaN 0.0005548 +## parent_0 1.0000000 NaN NaN 0.0001671 ## log_alpha NaN 1 NaN NaN ## log_beta NaN NaN 1 NaN -## sigma 0.0005548 NaN NaN 1.0000000 +## sigma 0.0001671 NaN NaN 1.0000000 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. ## t-test (unrealistically) based on the assumption of normal distribution ## for estimators of untransformed parameters. ## Estimate t value Pr(>t) Lower Upper -## parent_0 92.47 NA NA 89.720 95.220 -## alpha 87110.00 NA NA NA NA -## beta 911100.00 NA NA NA NA -## sigma 2.78 NA NA 1.789 3.771 +## parent_0 9.247e+01 NA NA 89.720 95.220 +## alpha 9.658e+05 NA NA NA NA +## beta 1.010e+07 NA NA NA NA +## sigma 2.780e+00 NA NA 1.794 3.766 ## ## FOCUS Chi2 error levels in percent: ## err.min n.optim df @@ -1701,8 +1708,8 @@ plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")</code></ ## parent 3.619 3 6 ## ## Estimated disappearance times: -## DT50 DT90 DT50back -## parent 7.249 24.08 7.249</code></pre> +## DT50 DT90 DT50back +## parent 7.25 24.08 7.25</code></pre> <p>We get a warning that the default optimisation algorithm <code>Port</code> did not converge, which is an indication that the model is overparameterised, <em>i.e.</em> contains too many parameters that are ill-defined as a consequence.</p> <p>And in fact, due to the higher number of parameters, and the lower number of degrees of freedom of the fit, the <span class="math inline"><em>χ</em><sup>2</sup></span> error level is actually higher for the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the parameters <code>log_alpha</code> and <code>log_beta</code> internally fitted in the model have excessive confidence intervals, that span more than 25 orders of magnitude (!) when backtransformed to the scale of <code>alpha</code> and <code>beta</code>. Also, the t-test for significant difference from zero does not indicate such a significant difference, with p-values greater than 0.1, and finally, the parameter correlation of <code>log_alpha</code> and <code>log_beta</code> is 1.000, clearly indicating that the model is overparameterised.</p> <p>The <span class="math inline"><em>χ</em><sup>2</sup></span> error levels reported in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to integer percentages and partly deviate by one percentage point from the results calculated by mkin. The reason for this is not known. However, mkin gives the same <span class="math inline"><em>χ</em><sup>2</sup></span> error levels as the kinfit package and the calculation routines of the kinfit package have been extensively compared to the results obtained by the KinGUI software, as documented in the kinfit package vignette. KinGUI was the first widely used standard package in this field. Also, the calculation of <span class="math inline"><em>χ</em><sup>2</sup></span> error levels was compared with KinGUII, CAKE and DegKin manager in a project sponsored by the German Umweltbundesamt <span class="citation">(Ranke 2014)</span>.</p> @@ -1735,17 +1742,17 @@ plot(m.L2.FOMC, show_residuals = TRUE, main = "FOCUS L2 - FOMC")</code></pre> <p><img src="data:image/png;base64,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" /><!-- --></p> <pre class="r"><code>summary(m.L2.FOMC, data = FALSE)</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:40 2022 -## Date of summary: Fri Jul 8 15:44:40 2022 +## Date of fit: Wed Sep 14 22:28:35 2022 +## Date of summary: Wed Sep 14 22:28:35 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 239 model solutions performed in 0.045 s +## Fitted using 239 model solutions performed in 0.049 s ## ## Error model: Constant variance ## @@ -1780,10 +1787,10 @@ plot(m.L2.FOMC, show_residuals = TRUE, ## ## Parameter correlation: ## parent_0 log_alpha log_beta sigma -## parent_0 1.000e+00 -1.151e-01 -2.085e-01 -7.637e-09 -## log_alpha -1.151e-01 1.000e+00 9.741e-01 -1.617e-07 -## log_beta -2.085e-01 9.741e-01 1.000e+00 -1.387e-07 -## sigma -7.637e-09 -1.617e-07 -1.387e-07 1.000e+00 +## parent_0 1.000e+00 -1.151e-01 -2.085e-01 -7.828e-09 +## log_alpha -1.151e-01 1.000e+00 9.741e-01 -1.602e-07 +## log_beta -2.085e-01 9.741e-01 1.000e+00 -1.372e-07 +## sigma -7.828e-09 -1.602e-07 -1.372e-07 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. @@ -1813,10 +1820,10 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, main = "FOCUS L2 - DFOP")</code></pre> <p><img 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" /><!-- --></p> <pre class="r"><code>summary(m.L2.DFOP, data = FALSE)</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:40 2022 -## Date of summary: Fri Jul 8 15:44:40 2022 +## Date of fit: Wed Sep 14 22:28:36 2022 +## Date of summary: Wed Sep 14 22:28:36 2022 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1825,7 +1832,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, ## ## Model predictions using solution type analytical ## -## Fitted using 581 model solutions performed in 0.119 s +## Fitted using 581 model solutions performed in 0.135 s ## ## Error model: Constant variance ## @@ -1856,18 +1863,18 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, ## Optimised, transformed parameters with symmetric confidence intervals: ## Estimate Std. Error Lower Upper ## parent_0 93.950 9.998e-01 91.5900 96.3100 -## log_k1 3.113 1.845e+03 -4360.0000 4367.0000 +## log_k1 3.112 1.842e+03 -4353.0000 4359.0000 ## log_k2 -1.088 6.285e-02 -1.2370 -0.9394 ## g_qlogis -0.399 9.946e-02 -0.6342 -0.1638 ## sigma 1.414 2.886e-01 0.7314 2.0960 ## ## Parameter correlation: ## parent_0 log_k1 log_k2 g_qlogis sigma -## parent_0 1.000e+00 6.784e-07 -5.188e-10 2.665e-01 -5.800e-10 -## log_k1 6.784e-07 1.000e+00 1.114e-04 -2.191e-04 -1.029e-05 -## log_k2 -5.188e-10 1.114e-04 1.000e+00 -7.903e-01 5.080e-09 -## g_qlogis 2.665e-01 -2.191e-04 -7.903e-01 1.000e+00 -7.991e-09 -## sigma -5.800e-10 -1.029e-05 5.080e-09 -7.991e-09 1.000e+00 +## parent_0 1.000e+00 6.783e-07 -3.390e-10 2.665e-01 -2.967e-10 +## log_k1 6.783e-07 1.000e+00 1.116e-04 -2.196e-04 -1.031e-05 +## log_k2 -3.390e-10 1.116e-04 1.000e+00 -7.903e-01 2.917e-09 +## g_qlogis 2.665e-01 -2.196e-04 -7.903e-01 1.000e+00 -4.408e-09 +## sigma -2.967e-10 -1.031e-05 2.917e-09 -4.408e-09 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. @@ -1875,7 +1882,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, ## for estimators of untransformed parameters. ## Estimate t value Pr(>t) Lower Upper ## parent_0 93.9500 9.397e+01 2.036e-12 91.5900 96.3100 -## k1 22.4800 5.544e-04 4.998e-01 0.0000 Inf +## k1 22.4800 5.553e-04 4.998e-01 0.0000 Inf ## k2 0.3369 1.591e+01 4.697e-07 0.2904 0.3909 ## g 0.4016 1.680e+01 3.238e-07 0.3466 0.4591 ## sigma 1.4140 4.899e+00 8.776e-04 0.7314 2.0960 @@ -1887,7 +1894,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, ## ## Estimated disappearance times: ## DT50 DT90 DT50back DT50_k1 DT50_k2 -## parent 0.5335 5.311 1.599 0.03083 2.058</code></pre> +## parent 0.5335 5.311 1.599 0.03084 2.058</code></pre> <p>Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion.</p> </div> </div> @@ -1913,10 +1920,10 @@ plot(mm.L3)</code></pre> <p>The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index.</p> <p>We can extract the summary and plot for <em>e.g.</em> the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.</p> <pre class="r"><code>summary(mm.L3[["DFOP", 1]])</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:40 2022 -## Date of summary: Fri Jul 8 15:44:41 2022 +## Date of fit: Wed Sep 14 22:28:36 2022 +## Date of summary: Wed Sep 14 22:28:36 2022 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1925,7 +1932,7 @@ plot(mm.L3)</code></pre> ## ## Model predictions using solution type analytical ## -## Fitted using 376 model solutions performed in 0.072 s +## Fitted using 376 model solutions performed in 0.081 s ## ## Error model: Constant variance ## @@ -1963,11 +1970,11 @@ plot(mm.L3)</code></pre> ## ## Parameter correlation: ## parent_0 log_k1 log_k2 g_qlogis sigma -## parent_0 1.000e+00 1.732e-01 2.282e-02 4.009e-01 -9.632e-08 -## log_k1 1.732e-01 1.000e+00 4.945e-01 -5.809e-01 7.145e-07 -## log_k2 2.282e-02 4.945e-01 1.000e+00 -6.812e-01 1.021e-06 -## g_qlogis 4.009e-01 -5.809e-01 -6.812e-01 1.000e+00 -7.925e-07 -## sigma -9.632e-08 7.145e-07 1.021e-06 -7.925e-07 1.000e+00 +## parent_0 1.000e+00 1.732e-01 2.282e-02 4.009e-01 -9.664e-08 +## log_k1 1.732e-01 1.000e+00 4.945e-01 -5.809e-01 7.147e-07 +## log_k2 2.282e-02 4.945e-01 1.000e+00 -6.812e-01 1.022e-06 +## g_qlogis 4.009e-01 -5.809e-01 -6.812e-01 1.000e+00 -7.926e-07 +## sigma -9.664e-08 7.147e-07 1.022e-06 -7.926e-07 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. @@ -2021,17 +2028,17 @@ plot(mm.L4)</code></pre> <p><img src="data:image/png;base64,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" /><!-- --></p> <p>The <span class="math inline"><em>χ</em><sup>2</sup></span> error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the <span class="math inline"><em>χ</em><sup>2</sup></span> test passes is slightly lower for the FOMC model. However, the difference appears negligible.</p> <pre class="r"><code>summary(mm.L4[["SFO", 1]], data = FALSE)</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:41 2022 -## Date of summary: Fri Jul 8 15:44:41 2022 +## Date of fit: Wed Sep 14 22:28:36 2022 +## Date of summary: Wed Sep 14 22:28:37 2022 ## ## Equations: ## d_parent/dt = - k_parent * parent ## ## Model predictions using solution type analytical ## -## Fitted using 142 model solutions performed in 0.027 s +## Fitted using 142 model solutions performed in 0.034 s ## ## Error model: Constant variance ## @@ -2063,9 +2070,9 @@ plot(mm.L4)</code></pre> ## ## Parameter correlation: ## parent_0 log_k_parent sigma -## parent_0 1.000e+00 5.938e-01 3.440e-07 -## log_k_parent 5.938e-01 1.000e+00 5.885e-07 -## sigma 3.440e-07 5.885e-07 1.000e+00 +## parent_0 1.000e+00 5.938e-01 3.387e-07 +## log_k_parent 5.938e-01 1.000e+00 5.830e-07 +## sigma 3.387e-07 5.830e-07 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. @@ -2085,17 +2092,17 @@ plot(mm.L4)</code></pre> ## DT50 DT90 ## parent 106 352</code></pre> <pre class="r"><code>summary(mm.L4[["FOMC", 1]], data = FALSE)</code></pre> -<pre><code>## mkin version used for fitting: 1.1.0 +<pre><code>## mkin version used for fitting: 1.1.2 ## R version used for fitting: 4.2.1 -## Date of fit: Fri Jul 8 15:44:41 2022 -## Date of summary: Fri Jul 8 15:44:41 2022 +## Date of fit: Wed Sep 14 22:28:37 2022 +## Date of summary: Wed Sep 14 22:28:37 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 224 model solutions performed in 0.041 s +## Fitted using 224 model solutions performed in 0.045 s ## ## Error model: Constant variance ## @@ -2130,10 +2137,10 @@ plot(mm.L4)</code></pre> ## ## Parameter correlation: ## parent_0 log_alpha log_beta sigma -## parent_0 1.000e+00 -4.696e-01 -5.543e-01 -2.563e-07 -## log_alpha -4.696e-01 1.000e+00 9.889e-01 4.066e-08 -## log_beta -5.543e-01 9.889e-01 1.000e+00 6.818e-08 -## sigma -2.563e-07 4.066e-08 6.818e-08 1.000e+00 +## parent_0 1.000e+00 -4.696e-01 -5.543e-01 -2.468e-07 +## log_alpha -4.696e-01 1.000e+00 9.889e-01 2.478e-08 +## log_beta -5.543e-01 9.889e-01 1.000e+00 5.211e-08 +## sigma -2.468e-07 2.478e-08 5.211e-08 1.000e+00 ## ## Backtransformed parameters: ## Confidence intervals for internally transformed parameters are asymmetric. diff --git a/vignettes/web_only/benchmarks.html b/vignettes/web_only/benchmarks.html index 4afe49c4..5f81f39f 100644 --- a/vignettes/web_only/benchmarks.html +++ b/vignettes/web_only/benchmarks.html @@ -1599,13 +1599,23 @@ div.tocify { <h1 class="title toc-ignore">Benchmark timings for mkin</h1> <h4 class="author">Johannes Ranke</h4> -<h4 class="date">Last change 1 July 2022 (rebuilt 2022-07-12)</h4> +<h4 class="date">Last change 14 July 2022 (rebuilt 2022-07-14)</h4> </div> <p>Each system is characterized by the operating system type, the CPU type, the mkin version, and, as in June 2022 the current R version lead to worse performance, the R version. A compiler was available, so if no analytical solution was available, compiled ODE models are used.</p> <p>Every fit is only performed once, so the accuracy of the benchmarks is limited.</p> +<p>The following wrapper function for <code>mmkin</code> is used because the way the error model is specified was changed in mkin version 0.9.49.1.</p> +<pre class="r"><code>if (packageVersion("mkin") > "0.9.48.1") { + mmkin_bench <- function(models, datasets, error_model = "const") { + mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + } +} else { + mmkin_bench <- function(models, datasets, error_model = NULL) { + mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + } +}</code></pre> <div id="test-cases" class="section level2"> <h2>Test cases</h2> <p>Parent only:</p> @@ -1613,6 +1623,7 @@ div.tocify { FOCUS_D <- subset(FOCUS_2006_D, value != 0) parent_datasets <- list(FOCUS_C, FOCUS_D) + t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets))[["elapsed"]] t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets, error_model = "tc"))[["elapsed"]]</code></pre> @@ -1658,11 +1669,6 @@ t10 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a), error_model = "obs"))[["elapsed"]] t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "obs"))[["elapsed"]]</code></pre> -<pre class="r"><code>mkin_benchmarks[system_string, paste0("t", 1:11)] <- - c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11) -save(mkin_benchmarks, file = benchmark_path) -# Hide rownames from kable for results section -rownames(mkin_benchmarks) <- NULL</code></pre> </div> <div id="results" class="section level2"> <h2>Results</h2> @@ -1807,8 +1813,8 @@ rownames(mkin_benchmarks) <- NULL</code></pre> <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">1.767</td> -<td align="right">3.396</td> +<td align="right">1.770</td> +<td align="right">3.377</td> </tr> </tbody> </table> @@ -1969,9 +1975,9 @@ rownames(mkin_benchmarks) <- NULL</code></pre> <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">1.320</td> -<td align="right">5.774</td> -<td align="right">2.575</td> +<td align="right">1.308</td> +<td align="right">5.758</td> +<td align="right">2.558</td> </tr> </tbody> </table> @@ -2180,12 +2186,12 @@ rownames(mkin_benchmarks) <- NULL</code></pre> <td align="left">Ryzen 7 1700</td> <td align="left">4.2.1</td> <td align="left">1.1.1</td> -<td align="right">0.700</td> -<td align="right">1.146</td> -<td align="right">1.334</td> -<td align="right">2.807</td> -<td align="right">1.750</td> -<td align="right">2.593</td> +<td align="right">0.696</td> +<td align="right">1.124</td> +<td align="right">1.321</td> +<td align="right">2.786</td> +<td align="right">1.744</td> +<td align="right">2.566</td> </tr> </tbody> </table> diff --git a/vignettes/web_only/benchmarks.rmd b/vignettes/web_only/benchmarks.rmd index 420bef27..9c8c10b7 100644 --- a/vignettes/web_only/benchmarks.rmd +++ b/vignettes/web_only/benchmarks.rmd @@ -1,7 +1,7 @@ --- title: "Benchmark timings for mkin" author: "Johannes Ranke" -date: Last change 1 July 2022 (rebuilt `r Sys.Date()`) +date: Last change 14 July 2022 (rebuilt `r Sys.Date()`) output: html_document: toc: true @@ -26,6 +26,21 @@ solution was available, compiled ODE models are used. Every fit is only performed once, so the accuracy of the benchmarks is limited. +The following wrapper function for `mmkin` is used because the way the error +model is specified was changed in mkin version 0.9.49.1. + +```{r} +if (packageVersion("mkin") > "0.9.48.1") { + mmkin_bench <- function(models, datasets, error_model = "const") { + mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) + } +} else { + mmkin_bench <- function(models, datasets, error_model = NULL) { + mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) + } +} +``` + ```{r include = FALSE} cpu_model <- benchmarkme::get_cpu()$model_name # Abbreviate CPU identifiers @@ -53,18 +68,11 @@ load(benchmark_path) mkin_benchmarks[system_string, c("CPU", "OS", "mkin", "R")] <- c(cpu_model, operating_system, mkin_version, R_version) - -if (mkin_version > "0.9.48.1") { - mmkin_bench <- function(models, datasets, error_model = "const") { - mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE) - } -} else { - mmkin_bench <- function(models, datasets, error_model = NULL) { - mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE) - } -} ``` + + + ## Test cases Parent only: @@ -74,6 +82,7 @@ FOCUS_C <- FOCUS_2006_C FOCUS_D <- subset(FOCUS_2006_D, value != 0) parent_datasets <- list(FOCUS_C, FOCUS_D) + t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets))[["elapsed"]] t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets, error_model = "tc"))[["elapsed"]] @@ -129,7 +138,7 @@ t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c), error_model = "obs"))[["elapsed"]] ``` -```{r results} +```{r results, include = FALSE} mkin_benchmarks[system_string, paste0("t", 1:11)] <- c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11) save(mkin_benchmarks, file = benchmark_path) diff --git a/vignettes/web_only/mkin_benchmarks.rda b/vignettes/web_only/mkin_benchmarks.rda Binary files differindex 49a91664..06d62afd 100644 --- a/vignettes/web_only/mkin_benchmarks.rda +++ b/vignettes/web_only/mkin_benchmarks.rda diff --git a/vignettes/web_only/multistart.html b/vignettes/web_only/multistart.html new file mode 100644 index 00000000..5568ad2c --- /dev/null +++ b/vignettes/web_only/multistart.html @@ -0,0 +1,461 @@ +<!DOCTYPE html> + +<html> + +<head> + +<meta charset="utf-8" /> +<meta name="generator" content="pandoc" /> +<meta http-equiv="X-UA-Compatible" content="IE=EDGE" /> + + +<meta name="author" content="Johannes Ranke" /> + + +<title>Short demo of the multistart method</title> + +<script>// Pandoc 2.9 adds attributes on both header and div. 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) 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+ + + +<div id="header"> + + + +<h1 class="title toc-ignore">Short demo of the multistart method</h1> +<h4 class="author">Johannes Ranke</h4> +<h4 class="date">Last change 26 September 2022 (rebuilt 2022-10-26)</h4> + +</div> + + +<p>The dimethenamid data from 2018 from seven soils is used as example data in this vignette.</p> +<pre class="r"><code>library(mkin) +dmta_ds <- lapply(1:7, function(i) { + ds_i <- dimethenamid_2018$ds[[i]]$data + ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" + ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] + ds_i +}) +names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) +dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) +dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL</code></pre> +<p>First, we check the DFOP model with the two-component error model and random effects for all degradation parameters.</p> +<pre class="r"><code>f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE) +f_saem_full <- saem(f_mmkin) +illparms(f_saem_full)</code></pre> +<pre><code>## [1] "sd(log_k2)"</code></pre> +<p>We see that not all variability parameters are identifiable. The <code>illparms</code> function tells us that the confidence interval for the standard deviation of ‘log_k2’ includes zero. We check this assessment using multiple runs with different starting values.</p> +<pre class="r"><code>f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16) +parhist(f_saem_full_multi)</code></pre> +<p><img 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width="672" /></p> +<p>This confirms that the variance of k2 is the most problematic parameter, so we reduce the parameter distribution model by removing the intersoil variability for k2.</p> +<pre class="r"><code>f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") +illparms(f_saem_reduced)</code></pre> +<pre><code>## character(0)</code></pre> +<pre class="r"><code>f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 16) +parhist(f_saem_reduced_multi, lpos = "topright")</code></pre> +<p><img 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" width="672" /></p> +<p>The results confirm that all remaining parameters can be determined with sufficient certainty.</p> +<p>We can also analyse the log-likelihoods obtained in the multiple runs:</p> +<pre class="r"><code>llhist(f_saem_reduced_multi)</code></pre> +<p><img src="data:image/png;base64,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" width="672" /></p> +<p>The parameter histograms can be further improved by excluding the result with the low likelihood.</p> +<pre class="r"><code>parhist(f_saem_reduced_multi, lpos = "topright", llmin = -326, ylim = c(0.5, 2))</code></pre> +<p><img src="data:image/png;base64,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" width="672" /></p> +<p>We can use the <code>anova</code> method to compare the models, including a likelihood ratio test if the models are nested.</p> +<pre class="r"><code>anova(f_saem_full, best(f_saem_reduced_multi), test = TRUE)</code></pre> +<pre><code>## Data: 155 observations of 1 variable(s) grouped in 6 datasets +## +## npar AIC BIC Lik Chisq Df Pr(>Chisq) +## best(f_saem_reduced_multi) 9 663.81 661.93 -322.90 +## f_saem_full 10 668.27 666.19 -324.13 0 1 1</code></pre> +<p>While AIC and BIC are lower for the reduced model, the likelihood ratio test does not indicate a significant difference between the fits.</p> + + + + +</div> + +<script> + +// add bootstrap table styles to pandoc tables +function bootstrapStylePandocTables() { + $('tr.odd').parent('tbody').parent('table').addClass('table table-condensed'); +} +$(document).ready(function () { + bootstrapStylePandocTables(); +}); + + +</script> + +<!-- tabsets --> + +<script> +$(document).ready(function () { + window.buildTabsets("TOC"); +}); + +$(document).ready(function () { + $('.tabset-dropdown > .nav-tabs > li').click(function () { + $(this).parent().toggleClass('nav-tabs-open'); + }); +}); +</script> + +<!-- code folding --> + + +<!-- dynamically load mathjax for compatibility with self-contained --> +<script> + (function () { + var script = document.createElement("script"); + script.type = "text/javascript"; + script.src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"; + document.getElementsByTagName("head")[0].appendChild(script); + })(); +</script> + +</body> +</html> diff --git a/vignettes/web_only/multistart.rmd b/vignettes/web_only/multistart.rmd new file mode 100644 index 00000000..27a8a96a --- /dev/null +++ b/vignettes/web_only/multistart.rmd @@ -0,0 +1,82 @@ +--- +title: Short demo of the multistart method +author: Johannes Ranke +date: Last change 26 September 2022 (rebuilt `r Sys.Date()`) +output: + html_document +vignette: > + %\VignetteEngine{knitr::rmarkdown} + %\VignetteIndexEntry{Short demo of the multistart method} + %\VignetteEncoding{UTF-8} +--- + +The dimethenamid data from 2018 from seven soils is used as example data in this vignette. + +```{r} +library(mkin) +dmta_ds <- lapply(1:7, function(i) { + ds_i <- dimethenamid_2018$ds[[i]]$data + ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" + ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] + ds_i +}) +names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) +dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) +dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL +``` + +First, we check the DFOP model with the two-component error model and +random effects for all degradation parameters. + +```{r} +f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE) +f_saem_full <- saem(f_mmkin) +illparms(f_saem_full) +``` +We see that not all variability parameters are identifiable. The `illparms` +function tells us that the confidence interval for the standard deviation +of 'log_k2' includes zero. We check this assessment using multiple runs +with different starting values. + +```{r} +f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16) +parplot(f_saem_full_multi) +``` + +This confirms that the variance of k2 is the most problematic parameter, so we +reduce the parameter distribution model by removing the intersoil variability +for k2. + +```{r} +f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") +illparms(f_saem_reduced) +f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 16) +parplot(f_saem_reduced_multi, lpos = "topright") +``` + +The results confirm that all remaining parameters can be determined with sufficient +certainty. + +We can also analyse the log-likelihoods obtained in the multiple runs: + +```{r} +llhist(f_saem_reduced_multi) +``` + +The parameter histograms can be further improved by excluding the result with +the low likelihood. + +```{r} +parplot(f_saem_reduced_multi, lpos = "topright", llmin = -326, ylim = c(0.5, 2)) +``` + +We can use the `anova` method to compare the models, including a likelihood ratio +test if the models are nested. + +```{r} +anova(f_saem_full, best(f_saem_reduced_multi), test = TRUE) +``` + +While AIC and BIC are lower for the reduced model, the likelihood ratio test +does not indicate a significant difference between the fits. + |
