nlmixr2auto (version 1.0.0)

step_elimination: Screen elimination type (linear vs Michaelis-Menten)

Description

Runs linear and Michaelis-Menten elimination candidates by modifying only the elimination setting in the current model code.

Usage

step_elimination(
  dat,
  start.mod = NULL,
  search.space = "ivbase",
  no.cores = NULL,
  param_table = NULL,
  penalty.control = NULL,
  precomputed_results_file = NULL,
  filename = "test",
  foldername = NULL,
  .modEnv = NULL,
  verbose = TRUE,
  ...
)

Value

A list with the following elements:

• results_table: a data.frame with one row per candidate model, including model description, Fitness, AIC, BIC, and OFV.

• best_code: named integer vector corresponding to the best candidate's model code.

• best_row: one-row data.frame summarizing the best candidate.

Arguments

dat

A data frame containing pharmacokinetic data in standard nlmixr2 format, including "ID", "TIME", "EVID", and "DV", and may include additional columns.

start.mod

A named integer vector specifying the starting model code. If NULL, a base model is generated using base_model().

search.space

Character, one of "ivbase" or "oralbase". Default is "ivbase".

no.cores

Integer. Number of CPU cores to use. If NULL, uses rxode2::getRxThreads().

param_table

Optional data frame of initial parameter estimates. If NULL, the table is generated by auto_param_table().

penalty.control

A list of penalty control parameters defined by penaltyControl(), specifying penalty values used for model diagnostics during fitness evaluation.

precomputed_results_file

Optional path to a CSV file of previously computed model results used for caching.

filename

Optional character string used as a prefix for output files. Defaults to "test".

foldername

Character string specifying the name of the folder to be created in the current working directory to store intermediate results. If NULL, a name is generated automatically.

.modEnv

Optional internal environment used to store model indices and cached results across model-selection steps.

verbose

Logical. If TRUE, print progress messages.

...

Additional arguments passed to mod.run().

Author

Zhonghui Huang

Details

When mm = 0, any inter-individual variability term for Km (eta.km) present in the model code is automatically set to zero.

See Also

mod.run, base_model, penaltyControl

Examples

# \donttest{
  dat <- pheno_sd
  param_table <- initialize_param_table()
  param_table$init[param_table$Name == "lcl"] <- log(0.008)
  param_table$init[param_table$Name == "lvc"] <- log(0.6)
  penalty.control = penaltyControl()
  penalty.control$penalty.terms = c("rse", "theta", "covariance")
  # Initialize start.mod with a base model
   start.mod <- base_model("ivbase")
  step_elimination(
    dat = dat,
    start.mod = start.mod,
    search.space = "ivbase",
    param_table = param_table,
    filename = "step_elim_test",
    penalty.control = penalty.control,
    saem.control = nlmixr2est::saemControl(logLik = TRUE,nBurn=15,nEm=15)
  )
# }