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")
 }
 }