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

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

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

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
)

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

Value

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

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

Details

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

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