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Diffstat (limited to 'R/plot.mixed.mmkin.R')
| -rw-r--r-- | R/plot.mixed.mmkin.R | 17 |
1 files changed, 17 insertions, 0 deletions
diff --git a/R/plot.mixed.mmkin.R b/R/plot.mixed.mmkin.R index f0682c10..1ac62b07 100644 --- a/R/plot.mixed.mmkin.R +++ b/R/plot.mixed.mmkin.R @@ -40,12 +40,17 @@ utils::globalVariables("ds") #' #' # For this fit we need to increase pnlsMaxiter, and we increase the #' # tolerance in order to speed up the fit for this example evaluation +#' # It still takes 20 seconds to run #' f_nlme <- nlme(f, control = list(pnlsMaxIter = 120, tolerance = 1e-3)) #' plot(f_nlme) #' #' f_saem <- saem(f, transformations = "saemix") #' plot(f_saem) #' +#' f_obs <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, error_model = "obs") +#' f_nlmix <- nlmix(f_obs) +#' plot(f_nlmix) +#' #' # We can overlay the two variants if we generate predictions #' pred_nlme <- mkinpredict(dfop_sfo, #' f_nlme$bparms.optim[-1], @@ -109,6 +114,18 @@ plot.mixed.mmkin <- function(x, names(degparms_pop) <- degparms_i_names } + if (inherits(x, "nlmixr.mmkin")) { + eta_i <- random.effects(x$nm)[-1] + names(eta_i) <- gsub("^eta.", "", names(eta_i)) + degparms_i <- eta_i + degparms_pop <- x$nm$theta + for (parm_name in names(degparms_i)) { + degparms_i[parm_name] <- eta_i[parm_name] + degparms_pop[parm_name] + } + residual_type = ifelse(standardized, "standardized", "residual") + residuals <- x$data[[residual_type]] + } + degparms_fixed <- fit_1$fixed$value names(degparms_fixed) <- rownames(fit_1$fixed) degparms_all <- cbind(as.matrix(degparms_i), |