Use all cores per default, confint tolerance

Also, use more intelligent starting values for the variance of the
random effects for saemix. While this does not appear to speed up
the convergence, it shows where this variance is greatly reduced
by using mixed-effects models as opposed to the separate independent
fits.

1 files changed, 18 insertions, 5 deletions

diff --git a/man/saemix.Rd b/man/saemix.Rd
index 23b0a4ad..b41796ca 100644
--- a/man/saemix.Rd
+++ b/man/saemix.Rd
@@ -5,13 +5,16 @@
 \alias{saemix_data}
 \title{Create saemix models from mmkin row objects}
 \usage{
-saemix_model(object)
+saemix_model(object, cores = parallel::detectCores())
 
 saemix_data(object, ...)
 }
 \arguments{
 \item{object}{An mmkin row object containing several fits of the same model to different datasets}
 
+\item{cores}{The number of cores to be used for multicore processing.
+On Windows machines, cores > 1 is currently not supported.}
+
 \item{\dots}{Further parameters passed to \link[saemix:saemixData]{saemix::saemixData}}
 }
 \value{
@@ -25,17 +28,27 @@ object for use with the saemix package. An mmkin row object is essentially a
 list of mkinfit objects that have been obtained by fitting the same model to
 a list of datasets.
 }
+\details{
+Starting values for the fixed effects (population mean parameters, argument psi0 of
+\code{\link[saemix:saemixModel]{saemix::saemixModel()}} are the mean values of the parameters found using
+mmkin. Starting variances of the random effects (argument omega.init) are the
+variances of the deviations of the parameters from these mean values.
+}
 \examples{
 ds <- lapply(experimental_data_for_UBA_2019[6:10],
  function(x) subset(x$data[c("name", "time", "value")]))
 names(ds) <- paste("Dataset", 6:10)
 sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
   A1 = mkinsub("SFO"))
-f_mmkin <- mmkin(list("SFO-SFO" = sfo_sfo), ds, quiet = TRUE, cores = 5)
+\dontrun{
+f_mmkin <- mmkin(list("SFO-SFO" = sfo_sfo), ds, quiet = TRUE)
+library(saemix)
 m_saemix <- saemix_model(f_mmkin)
 d_saemix <- saemix_data(f_mmkin)
-saemix_options <- list(seed = 123456, save = FALSE, save.graphs = FALSE)
-\dontrun{
-  saemix(m_saemix, d_saemix, saemix_options)
+saemix_options <- list(seed = 123456,
+  save = FALSE, save.graphs = FALSE, displayProgress = FALSE,
+  nbiter.saemix = c(200, 80))
+f_saemix <- saemix(m_saemix, d_saemix, saemix_options)
+plot(f_saemix, plot.type = "convergence")
 }
 }