run_iivsearch {pharmr}

run_iivsearch

Description

Run IIVsearch tool. For more details, see :ref:iivsearch.

Usage

run_iivsearch(
  algorithm = "top_down_exhaustive",
  iiv_strategy = "no_add",
  rank_type = "bic",
  linearize = FALSE,
  cutoff = NULL,
  results = NULL,
  model = NULL,
  keep = c("CL"),
  strictness = "minimization_successful or (rounding_errors and sigdigs>=0.1)",
  correlation_algorithm = NULL,
  E_p = NULL,
  E_q = NULL,
  ...
)

Arguments

algorithm

(str) Which algorithm to run when determining number of IIVs.

iiv_strategy

(str) If/how IIV should be added to start model. Default is 'no_add'.

rank_type

(str) Which ranking type should be used. Default is BIC.

linearize

(logical) Wheter or not use linearization when running the tool.

cutoff

(numeric (optional)) Cutoff for which value of the ranking function that is considered significant. Default is NULL (all models will be ranked)

results

(ModelfitResults (optional)) Results for model

model

(Model (optional)) Pharmpy model

keep

(array(str) (optional)) List of IIVs to keep. Default is "CL"

strictness

(str (optional)) Strictness criteria

correlation_algorithm

(str (optional)) Which algorithm to run for the determining block structure of added IIVs. If NULL, the algorithm is determined based on the 'algorithm' argument

E_p

(numeric (optional)) Expected number of predictors for diagonal elements (used for mBIC). Must be set when using mBIC and when the argument 'algorithm' is not 'skip'

E_q

(numeric (optional)) Expected number of predictors for off-diagonal elements (used for mBIC). Must be set when using mBIC and when the argument correlation_algorithm is not skip or Non

...

Arguments to pass to tool

Value

(IIVSearchResults) IIVsearch tool result object

Examples

## Not run: 
model <- load_example_model("pheno")
results <- load_example_modelfit_results("pheno")
run_iivsearch('td_brute_force', results=results, model=model)

## End(Not run)