check_fitted_values {vimp} | R Documentation |
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
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
)
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 |
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.
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.
None. Called for the side effect of stopping the algorithm if any inputs are in an unexpected format.