check_fitted_values: Check pre-computed fitted values for call to vim, cv_vim, or...

In vimp: Perform Inference on Algorithm-Agnostic Variable Importance

Check pre-computed fitted values for call to vim, cv_vim, or sp_vim

Description

Check pre-computed fitted values for call to vim, cv_vim, or sp_vim

Usage

check_fitted_values(
  Y = NULL,
  f1 = NULL,
  f2 = NULL,
  cross_fitted_f1 = NULL,
  cross_fitted_f2 = NULL,
  sample_splitting_folds = NULL,
  cross_fitting_folds = NULL,
  cross_fitted_se = TRUE,
  V = NULL,
  ss_V = NULL,
  cv = FALSE
)

Arguments

Y	the outcome
f1	estimator of the population-optimal prediction function using all covariates
f2	estimator of the population-optimal prediction function using the reduced set of covariates
cross_fitted_f1	cross-fitted estimator of the population-optimal prediction function using all covariates
cross_fitted_f2	cross-fitted estimator of the population-optimal prediction function using the reduced set of covariates
sample_splitting_folds	the folds for sample-splitting (used for hypothesis testing)
cross_fitting_folds	the folds for cross-fitting (used for point estimates of variable importance in cv_vim and sp_vim)
cross_fitted_se	logical; should cross-fitting be used to estimate standard errors?
V	the number of cross-fitting folds
ss_V	the number of folds for CV (if sample_splitting is TRUE)
cv	a logical flag indicating whether or not to use cross-fitting

Details

Ensure that inputs to vim, cv_vim, and sp_vim follow the correct formats.

Value

None. Called for the side effect of stopping the algorithm if any inputs are in an unexpected format.

vimp documentation built on Aug. 29, 2023, 1:06 a.m.