Estimate projection of EIF on fully-observed variables
extract_sampled_split_predictions
Extract sampled-split predictions from a CV.SuperLearner object
estimate_type_predictiveness
Estimate Predictiveness Given a Type
vimp: Perform Inference on Algorithm-Agnostic Intrinsic Variable Importance
Return an estimator on a different scale
Shapley Population Variable Importance Measure (SPVIM) Estimates and Inference
Nonparametric Intrinsic Variable Importance Estimates and Inference
Return test-set only data
Create Folds for Cross-Fitting
Estimate ANOVA decomposition-based variable importance.
Estimate nuisance functions for average value-based VIMs
Estimate area under the receiver operating characteristic curve (AUC)
Process argument list for Super Learner estimation of the EIF
Print vim objects
Estimate the deviance
Estimate mean squared error
Nonparametric Intrinsic Variable Importance Estimates: Deviance
Perform a hypothesis test against the null hypothesis of \(\delta\) importance
Construct a Predictiveness Measure
print.predictiveness_measure
Print predictiveness_measure objects
Run a Super Learner for the provided subset of features
Nonparametric Intrinsic Variable Importance Estimates: Classification accuracy
Estimate the classification accuracy
Turn folds from 2K-fold cross-fitting into individual K-fold folds
Create necessary objects for SPVIMs
Get a numeric vector with cross-validation fold IDs from CV.SuperLearner
Obtain the type of VIM to estimate using partial matching
Estimate the average value under the optimal treatment rule
Estimate the cross-entropy
Influence function estimates for SPVIMs
Estimate variable importance standard errors
Nonparametric Intrinsic Variable Importance Estimates: ANOVA
Neutralization sensitivity of HIV viruses to antibody VRC01
Standard error estimate for SPVIM values
Nonparametric Intrinsic Variable Importance Estimates: AUC
Confidence intervals for variable importance
format.predictiveness_measure
Format a predictiveness_measure object
Format a vim object
Nonparametric Intrinsic Variable Importance Estimates and Inference using Cross-fitting
Estimate R-squared
Nonparametric Intrinsic Variable Importance Estimates: ANOVA
Nonparametric Intrinsic Variable Importance Estimates: R-squared
Merge multiple vim objects into one
estimate.predictiveness_measure
Obtain a Point Estimate and Efficient Influence Function Estimate for a Given Predictiveness Measure
Estimate a nonparametric predictiveness functional using cross-fitting
Estimate a Predictiveness Measure
Create complete-case outcome, weights, and Z
Check pre-computed fitted values for call to vim, cv_vim, or sp_vim
Compute bootstrap-based standard error estimates for variable importance
Average multiple independent importance estimates
Check inputs to a call to vim, cv_vim, or sp_vim
Estimate a nonparametric predictiveness functional