run_modelrank: run_modelrank

Description

Run ModelRank tool.

Usage

run_modelrank(
  models,
  results,
  ref_model,
  strictness = "minimization_successful or (rounding_errors and sigdigs >= 0.1)",
  rank_type = "ofv",
  alpha = 0.05,
  search_space = NULL,
  E = NULL,
  parameter_uncertainty_method = NULL,
  exclude_reference_model = FALSE,
  ...
)

Value

(ModelRankResults) ModelRank tool result object

Arguments

models: (array(Model)) Models to rank
results: (array(ModelfitResults)) Modelfit results to rank on
ref_model: (Model) Model to compare to
strictness: (str) Strictness criteria
rank_type: (str) Which ranking type should be used. Supported types are OFV, LRT, AIC, BIC (mixed, IIV, random), and mBIC (mixed, IIV, random). Default is OFV.
alpha: (numeric (optional)) Cutoff p-value that is considered significant in likelihood ratio test. Default is NULL
search_space: (str or ModelFeatures (optional)) Search space to test. Either as a string or a ModelFeatures object.
E: (numeric or str or list(numeric or str,numeric or str) (optional)) Expected number of predictors (used for mBIC). Must be set when using mBIC. Tuple if mBIC for IIV (both diagonals and off-diagonals)
parameter_uncertainty_method: (str (optional)) Parameter uncertainty method. Will be used in ranking models if strictness includes parameter uncertainty
exclude_reference_model: (logical) Should it be possible to select the reference model? Default is TRUE
...: Arguments to pass to tool