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.

5 files changed, 31 insertions, 10 deletions

diff --git a/man/confint.mkinfit.Rd b/man/confint.mkinfit.Rd
index f295afc4..fd2890ff 100644
--- a/man/confint.mkinfit.Rd
+++ b/man/confint.mkinfit.Rd
@@ -13,7 +13,8 @@
   method = c("quadratic", "profile"),
   transformed = TRUE,
   backtransform = TRUE,
-  cores = round(detectCores()/2),
+  cores = parallel::detectCores(),
+  rel_tol = 0.01,
   quiet = FALSE,
   ...
 )
@@ -48,6 +49,10 @@ their confidence intervals?}
 \item{cores}{The number of cores to be used for multicore processing.
 On Windows machines, cores > 1 is currently not supported.}
 
+\item{rel_tol}{If the method is 'profile', what should be the accuracy
+of the lower and upper bounds, relative to the estimate obtained from
+the quadratic method?}
+
 \item{quiet}{Should we suppress the message "Profiling the likelihood"}
 
 \item{\dots}{Not used}
diff --git a/man/mmkin.Rd b/man/mmkin.Rd
index eda0d837..9a74a9cd 100644
--- a/man/mmkin.Rd
+++ b/man/mmkin.Rd
@@ -8,7 +8,7 @@ more datasets}
 mmkin(
   models = c("SFO", "FOMC", "DFOP"),
   datasets,
-  cores = round(detectCores()/2),
+  cores = detectCores(),
   cluster = NULL,
   ...
 )
@@ -24,7 +24,8 @@ data for \code{\link{mkinfit}}.}
 \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.}
+argument to use multiple logical processors. Per default, all cores
+detected by \code{\link[parallel:detectCores]{parallel::detectCores()}} are used.}
 
 \item{cluster}{A cluster as returned by \code{\link{makeCluster}} to be used
 for parallel execution.}
diff --git a/man/nlme.Rd b/man/nlme.Rd
index 5e981a14..2ee2a20c 100644
--- a/man/nlme.Rd
+++ b/man/nlme.Rd
@@ -23,7 +23,7 @@ A function that can be used with nlme
 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?
+nlme for the case of a single grouping variable ds.
 
 A \code{\link{groupedData}} object
 }
diff --git a/man/parms.Rd b/man/parms.Rd
index d3917639..af92bd2a 100644
--- a/man/parms.Rd
+++ b/man/parms.Rd
@@ -42,9 +42,11 @@ parms(fit, transformed = TRUE)
 ds <- lapply(experimental_data_for_UBA_2019[6:10],
  function(x) subset(x$data[c("name", "time", "value")]))
 names(ds) <- paste("Dataset", 6:10)
-fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
+\dontrun{
+fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
 parms(fits["SFO", ])
 parms(fits[, 2])
 parms(fits)
 parms(fits, transformed = TRUE)
 }
+}
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")
 }
 }