2 files changed, 42 insertions, 57 deletions
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index f2799bf4..3a2939e1 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -6,19 +6,7 @@
 \alias{mkinpredict.mkinfit}
 \title{Produce predictions from a kinetic model using specific parameters}
 \usage{
-mkinpredict(
-  x,
-  odeparms,
-  odeini,
-  outtimes = seq(0, 120, by = 0.1),
-  solution_type = "deSolve",
-  use_compiled = "auto",
-  method.ode = "lsoda",
-  atol = 1e-08,
-  rtol = 1e-10,
-  map_output = TRUE,
-  ...
-)
+mkinpredict(x, odeparms, odeini, outtimes, ...)
 
 \method{mkinpredict}{mkinmod}(
   x,
@@ -30,8 +18,8 @@ mkinpredict(
   method.ode = "lsoda",
   atol = 1e-08,
   rtol = 1e-10,
-  na_stop = TRUE,
   map_output = TRUE,
+  na_stop = TRUE,
   ...
 )
 
@@ -65,6 +53,9 @@ observed variables, for example in the case of the SFORB model.}
 \item{outtimes}{A numeric vector specifying the time points for which model
 predictions should be generated.}
 
+\item{\dots}{Further arguments passed to the ode solver in case such a
+solver is used.}
+
 \item{solution_type}{The method that should be used for producing the
 predictions. This should generally be "analytical" if there is only one
 observed variable, and usually "deSolve" in the case of several observed
@@ -89,9 +80,6 @@ the observed variables (default) or for all state variables (if set to
 FALSE). Setting this to FALSE has no effect for analytical solutions,
 as these always return mapped output.}
 
-\item{\dots}{Further arguments passed to the ode solver in case such a
-solver is used.}
-
 \item{na_stop}{Should it be an error if deSolve::ode returns NaN values}
 }
 \value{
diff --git a/man/saemix.Rd b/man/saem.Rd
index a664b0cc..39b66448 100644
--- a/man/saemix.Rd
+++ b/man/saem.Rd
@@ -1,17 +1,16 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/saemix.R
-\name{saemix}
-\alias{saemix}
-\alias{saemix.mmkin}
+\name{saem}
+\alias{saem}
+\alias{saem.mmkin}
 \alias{saemix_model}
 \alias{saemix_data}
-\title{Create saemix models}
+\title{Fit nonlinear mixed models with SAEM}
 \usage{
-saemix(model, data, control, ...)
+saem(object, control, ...)
 
-\method{saemix}{mmkin}(
-  model,
-  data,
+\method{saem}{mmkin}(
+  object,
   control = list(displayProgress = FALSE, print = FALSE, save = FALSE, save.graphs =
     FALSE),
   cores = 1,
@@ -25,9 +24,10 @@ saemix_model(object, cores = 1, verbose = FALSE, ...)
 saemix_data(object, verbose = FALSE, ...)
 }
 \arguments{
-\item{model}{For the default method, this is an \link[saemix:saemixModel]{saemix::saemixModel} object.
-If this is an \link{mmkin} row object, the \link[saemix:saemixModel]{saemix::saemixModel} is created
-internally from the \link{mmkin} object.}
+\item{object}{An \link{mmkin} row object containing several fits of the same
+\link{mkinmod} model to different datasets}
+
+\item{control}{Passed to \link[saemix:saemix]{saemix::saemix}}
 
 \item{\dots}{Further parameters passed to \link[saemix:saemixData]{saemix::saemixData}
 and \link[saemix:saemixModel]{saemix::saemixModel}.}
@@ -39,8 +39,8 @@ used.}
 
 \item{verbose}{Should we print information about created objects?}
 
-\item{object}{An \link{mmkin} row object containing several fits of the same
-\link{mkinmod} model to different datasets}
+\item{suppressPlot}{Should we suppress any plotting that is done
+by the saemix function?}
 }
 \value{
 An \link[saemix:SaemixObject-class]{saemix::SaemixObject}.
@@ -50,54 +50,51 @@ An \link[saemix:SaemixModel-class]{saemix::SaemixModel} object.
 An \link[saemix:SaemixData-class]{saemix::SaemixData} object.
 }
 \description{
-The saemix function defined in this package is an S3 generic function
-using \code{\link[saemix:saemix]{saemix::saemix()}} as its method for \link[saemix:SaemixModel-class]{saemix::SaemixModel} objects.
+This function uses \code{\link[saemix:saemix]{saemix::saemix()}} as a backend for fitting nonlinear mixed
+effects models created from \link{mmkin} row objects using the stochastic approximation
+to the expectation maximisation algorithm (SAEM).
 }
 \details{
-The method for mmkin row objects sets up a nonlinear mixed effects model 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.
-
-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
-\link{mmkin}.
+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 using \link{mkinfit}.
+
+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 \link{mmkin}.
 }
 \examples{
 \dontrun{
-# We can load saemix, but should exclude the saemix function
-# as it would mask our generic version of it
-library(saemix, exclude = "saemix")
 ds <- lapply(experimental_data_for_UBA_2019[6:10],
  function(x) subset(x$data[c("name", "time", "value")]))
 names(ds) <- paste("Dataset", 6:10)
 f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, cores = 1,
   state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE)
-f_saemix_p0_fixed <- saemix(f_mmkin_parent_p0_fixed)
+f_saem_p0_fixed <- saem(f_mmkin_parent_p0_fixed)
 
 f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
-f_saemix_sfo <- saemix(f_mmkin_parent["SFO", ])
-f_saemix_fomc <- saemix(f_mmkin_parent["FOMC", ])
-f_saemix_dfop <- saemix(f_mmkin_parent["DFOP", ])
+f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
+f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
+f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
 
-# As this returns an SaemixObject, we can use functions from saemix
-compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop))
+# The returned saem.mmkin object contains an SaemixObject, we can use
+# functions from saemix
+library(saemix)
+compare.saemix(list(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so))
 
 f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
-f_saemix_fomc_tc <- saemix(f_mmkin_parent_tc["FOMC", ])
-compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc))
+f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
+compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so))
 
 dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
   A1 = mkinsub("SFO"))
 f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "analytical")
 # This takes about 4 minutes on my system
-f_saemix <- saemix(f_mmkin)
+f_saem <- saem(f_mmkin)
 
-# Using a single core, it takes about 6 minutes, using 10 cores it is slower
-# instead of faster
 f_mmkin_des <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "deSolve")
-f_saemix_des <- saemix(f_mmkin_des, cores = 1)
-compare.saemix(list(f_saemix, f_saemix_des))
-
+# Using a single core, the following takes about 6 minutes, using 10 cores
+# it is slower instead of faster
+f_saem_des <- saem(f_mmkin_des, cores = 1)
+compare.saemix(list(f_saemix$so, f_saemix_des$so))
 }
 }