This function uses saemix::saemix() as a backend for fitting nonlinear mixed
effects models created from mmkin row objects using the Stochastic Approximation
Expectation Maximisation algorithm (SAEM).
saem(object, ...)
# S3 method for mmkin
saem(
object,
transformations = c("mkin", "saemix"),
degparms_start = numeric(),
test_log_parms = TRUE,
conf.level = 0.6,
solution_type = "auto",
nbiter.saemix = c(300, 100),
control = list(displayProgress = FALSE, print = FALSE, nbiter.saemix = nbiter.saemix,
save = FALSE, save.graphs = FALSE),
fail_with_errors = TRUE,
verbose = FALSE,
quiet = FALSE,
...
)
# S3 method for saem.mmkin
print(x, digits = max(3, getOption("digits") - 3), ...)
saemix_model(
object,
solution_type = "auto",
transformations = c("mkin", "saemix"),
degparms_start = numeric(),
test_log_parms = FALSE,
verbose = FALSE,
...
)
saemix_data(object, verbose = FALSE, ...)An mmkin row object containing several fits of the same mkinmod model to different datasets
Further parameters passed to saemix::saemixModel.
Per default, all parameter transformations are done in mkin. If this argument is set to 'saemix', parameter transformations are done in 'saemix' for the supported cases. Currently this is only supported in cases where the initial concentration of the parent is not fixed, SFO or DFOP is used for the parent and there is either no metabolite or one.
Parameter values given as a named numeric vector will be used to override the starting values obtained from the 'mmkin' object.
If TRUE, an attempt is made to use more robust starting values for population parameters fitted as log parameters in mkin (like rate constants) by only considering rate constants that pass the t-test when calculating mean degradation parameters using mean_degparms.
Possibility to adjust the required confidence level for parameter that are tested if requested by 'test_log_parms'.
Possibility to specify the solution type in case the automatic choice is not desired
Convenience option to increase the number of iterations
Passed to saemix::saemix.
Should a failure to compute standard errors from the inverse of the Fisher Information Matrix be a failure?
Should we print information about created objects of type saemix::SaemixModel and saemix::SaemixData?
Should we suppress the messages saemix prints at the beginning and the end of the optimisation process?
An saem.mmkin object to print
Number of digits to use for printing
An S3 object of class 'saem.mmkin', containing the fitted saemix::SaemixObject as a list component named 'so'. The object also inherits from 'mixed.mmkin'. An saemix::SaemixModel object. An saemix::SaemixData object.
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.
# \dontrun{
ds <- lapply(experimental_data_for_UBA_2019[6:10],
function(x) subset(x$data[c("name", "time", "value")]))
names(ds) <- paste("Dataset", 6:10)
f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds,
state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE)
f_saem_p0_fixed <- saem(f_mmkin_parent_p0_fixed)
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
# The returned saem.mmkin object contains an SaemixObject, therefore we can use
# functions from saemix
library(saemix)
#> Loading required package: npde
#>
#> Attaching package: ‘npde’
#> The following object is masked from ‘package:nlmixr’:
#>
#> warfarin
#> Package saemix, version 3.0
#> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr
#>
#> Attaching package: ‘saemix’
#> The following objects are masked from ‘package:npde’:
#>
#> kurtosis, skewness
#> The following object is masked from ‘package:RxODE’:
#>
#> phi
compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so)
#> Error in compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so): object 'f_saem_sfo' not found
plot(f_saem_fomc$so, plot.type = "convergence")
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "individual.fit")
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "npde")
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "vpc")
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so)
#> Error in compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so): object 'f_saem_fomc' not found
sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
A1 = mkinsub("SFO"))
#> Temporary DLL for differentials generated and loaded
fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
A1 = mkinsub("SFO"))
#> Temporary DLL for differentials generated and loaded
dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
A1 = mkinsub("SFO"))
#> Temporary DLL for differentials generated and loaded
# The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,
# and compiled ODEs for FOMC that are much slower
f_mmkin <- mmkin(list(
"SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
ds, quiet = TRUE)
# saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds
# each on this system, as we use analytical solutions written for saemix.
# When using the analytical solutions written for mkin this took around
# four minutes
f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
# We can use print, plot and summary methods to check the results
print(f_saem_dfop_sfo)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'f_saem_dfop_sfo' not found
plot(f_saem_dfop_sfo)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_dfop_sfo' not found
summary(f_saem_dfop_sfo, data = TRUE)
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_saem_dfop_sfo' not found
# The following takes about 6 minutes
#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",
# control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))
#saemix::compare.saemix(list(
# f_saem_dfop_sfo$so,
# f_saem_dfop_sfo_deSolve$so))
# If the model supports it, we can also use eigenvalue based solutions, which
# take a similar amount of time
#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",
# control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))
# }