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-rw-r--r--R/mkinpredict.R10
-rw-r--r--R/saemix.R85
2 files changed, 48 insertions, 47 deletions
diff --git a/R/mkinpredict.R b/R/mkinpredict.R
index a6e7ca1c..7222e247 100644
--- a/R/mkinpredict.R
+++ b/R/mkinpredict.R
@@ -103,12 +103,7 @@
#' }
#'
#' @export
-mkinpredict <- function(x, odeparms, odeini,
- outtimes = seq(0, 120, by = 0.1),
- solution_type = "deSolve",
- use_compiled = "auto",
- method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
- map_output = TRUE, ...)
+mkinpredict <- function(x, odeparms, odeini, outtimes, ...)
{
UseMethod("mkinpredict", x)
}
@@ -122,8 +117,9 @@ mkinpredict.mkinmod <- function(x,
solution_type = "deSolve",
use_compiled = "auto",
method.ode = "lsoda", atol = 1e-8, rtol = 1e-10,
+ map_output = TRUE,
na_stop = TRUE,
- map_output = TRUE, ...)
+ ...)
{
# Names of state variables and observed variables
diff --git a/R/saemix.R b/R/saemix.R
index 280490a0..1db8b011 100644
--- a/R/saemix.R
+++ b/R/saemix.R
@@ -1,20 +1,16 @@
-#' Create saemix models
+#' Fit nonlinear mixed models with SAEM
#'
-#' The saemix function defined in this package is an S3 generic function
-#' using [saemix::saemix()] as its method for [saemix::SaemixModel] objects.
+#' This function uses [saemix::saemix()] as a backend for fitting nonlinear mixed
+#' effects models created from [mmkin] row objects using the stochastic approximation
+#' to the expectation maximisation algorithm (SAEM).
#'
-#' 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.
+#' 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 [mkinfit].
#'
-#' Starting values for the fixed effects (population mean parameters, argument psi0 of
-#' [saemix::saemixModel()] are the mean values of the parameters found using
-#' [mmkin].
+#' Starting values for the fixed effects (population mean parameters, argument
+#' psi0 of [saemix::saemixModel()] are the mean values of the parameters found
+#' using [mmkin].
#'
-#' @param model For the default method, this is an [saemix::saemixModel] object.
-#' If this is an [mmkin] row object, the [saemix::saemixModel] is created
-#' internally from the [mmkin] object.
#' @param object An [mmkin] row object containing several fits of the same
#' [mkinmod] model to different datasets
#' @param verbose Should we print information about created objects?
@@ -22,75 +18,84 @@
#' [parallel::mclapply()]. Using more than 1 core is experimental and may
#' lead to uncontrolled forking, apparently depending on the BLAS version
#' used.
+#' @param suppressPlot Should we suppress any plotting that is done
+#' by the saemix function?
+#' @param control Passed to [saemix::saemix]
#' @param \dots Further parameters passed to [saemix::saemixData]
#' and [saemix::saemixModel].
#' @return An [saemix::SaemixObject].
#' @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))
#' }
#' @export
-saemix <- function(model, data, control, ...) UseMethod("saemix")
+saem <- function(object, control, ...) UseMethod("saem")
-#' @rdname saemix
+#' @rdname saem
#' @export
-saemix.mmkin <- function(model, data,
+saem.mmkin <- function(object,
control = list(displayProgress = FALSE, print = FALSE,
save = FALSE, save.graphs = FALSE),
cores = 1,
verbose = FALSE, suppressPlot = TRUE, ...)
{
- m_saemix <- saemix_model(model, cores = cores, verbose = verbose)
- d_saemix <- saemix_data(model, verbose = verbose)
+ m_saemix <- saemix_model(object, cores = cores, verbose = verbose)
+ d_saemix <- saemix_data(object, verbose = verbose)
if (suppressPlot) {
# We suppress the log-likelihood curve that saemix currently
# produces at the end of the fit by plotting to a file
# that we discard afterwards
tmp <- tempfile()
- png(tmp)
+ grDevices::png(tmp)
}
- result <- saemix::saemix(m_saemix, d_saemix, control)
+ f_saemix <- saemix::saemix(m_saemix, d_saemix, control)
if (suppressPlot) {
- dev.off()
+ grDevices::dev.off()
unlink(tmp)
}
+ result <- list(
+ mkinmod = object[[1]]$mkinmod,
+ mmkin = object,
+ solution_type = object[[1]]$solution_type,
+ transform_rates = object[[1]]$transform_rates,
+ transform_fractions = object[[1]]$transform_fractions,
+ so = f_saemix)
+ class(result) <- "saem.mmkin"
return(result)
}
-#' @rdname saemix
+#' @rdname saem
#' @return An [saemix::SaemixModel] object.
#' @export
saemix_model <- function(object, cores = 1, verbose = FALSE, ...) {
@@ -254,7 +259,7 @@ saemix_model <- function(object, cores = 1, verbose = FALSE, ...) {
return(res)
}
-#' @rdname saemix
+#' @rdname saem
#' @return An [saemix::SaemixData] object.
#' @export
saemix_data <- function(object, verbose = FALSE, ...) {

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