nlmixr2auto (version 1.0.0)

step_compartments: Screen number of compartments

Description

Runs candidate models with one, two, and three compartments by modifying only the compartment setting in the current model code.

Usage

step_compartments(
  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 and fit statistics

• best_code: named integer vector corresponding to the best candidate

• best_row: one-row data frame containing the best candidate summary

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 folder name for storing intermediate results. If NULL (default), tempdir() is used for temporary storage. If specified, a cache directory is created in the current working directory.

.modEnv

Internal environment used to store model indices and cached results across steps.

verbose

Logical. If TRUE, print progress messages.

...

Additional arguments passed to mod.run. These may include custom_base, which is used to initialize the baseline model when no best_code is present in start.mod.

Author

Zhonghui Huang

Details

Three candidate models are created by modifying only the number of compartments in the starting model code. The candidate codes are evaluated sequentially, and a results table containing model names, model codes, Fitness values, and information criteria is returned for logging and decision making.

See Also

mod.run, base_model, penaltyControl

Examples

# \donttest{
  dat <- pheno_sd
  string <- c(1, 0, 0, 0, 0, 0, 0, 0, 0, 1)
  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")
  step_compartments(
    dat = dat,
    search.space = "ivbase",
    param_table = param_table,
    filename = "step_cmpt_test",
    penalty.control = penalty.control,
    saem.control = nlmixr2est::saemControl(logLik = TRUE,nBurn=15,nEm=15)
  )
# }