Perform Inference on Algorithm-Agnostic Variable Importance
Average multiple independent importance estimates
Compute bootstrap-based standard error estimates for variable importan...
Check pre-computed fitted values for call to vim, cv_vim, or sp_vim
Check inputs to a call to vim, cv_vim, or sp_vim
Create complete-case outcome, weights, and Z
Nonparametric Intrinsic Variable Importance Estimates and Inference us...
Estimate a nonparametric predictiveness functional
Estimate a nonparametric predictiveness functional using cross-fitting
Obtain a Point Estimate and Efficient Influence Function Estimate for ...
Estimate a Predictiveness Measure
Estimate projection of EIF on fully-observed variables
Estimate nuisance functions for average value-based VIMs
Estimate Predictiveness Given a Type
Extract sampled-split predictions from a CV.SuperLearner object
Format a predictiveness_measure
object
Format a vim
object
Get a numeric vector with cross-validation fold IDs from CV.SuperLearn...
Obtain the type of VIM to estimate using partial matching
Return test-set only data
Create Folds for Cross-Fitting
Turn folds from 2K-fold cross-fitting into individual K-fold folds
Estimate the classification accuracy
Estimate ANOVA decomposition-based variable importance.
Estimate area under the receiver operating characteristic curve (AUC)
Estimate the average value under the optimal treatment rule
Estimate the cross-entropy
Estimate the deviance
Estimate mean squared error
Estimate R-squared
Merge multiple vim
objects into one
Construct a Predictiveness Measure
Print predictiveness_measure
objects
Print vim
objects
Process argument list for Super Learner estimation of the EIF
Run a Super Learner for the provided subset of features
Create necessary objects for SPVIMs
Return an estimator on a different scale
Shapley Population Variable Importance Measure (SPVIM) Estimates and I...
Influence function estimates for SPVIMs
Standard error estimate for SPVIM values
Nonparametric Intrinsic Variable Importance Estimates and Inference
vimp: Perform Inference on Algorithm-Agnostic Intrinsic Variable Impor...
Nonparametric Intrinsic Variable Importance Estimates: Classification ...
Nonparametric Intrinsic Variable Importance Estimates: ANOVA
Nonparametric Intrinsic Variable Importance Estimates: AUC
Confidence intervals for variable importance
Nonparametric Intrinsic Variable Importance Estimates: Deviance
Perform a hypothesis test against the null hypothesis of impo...
Nonparametric Intrinsic Variable Importance Estimates: ANOVA
Nonparametric Intrinsic Variable Importance Estimates: R-squared
Estimate variable importance standard errors
Calculate point estimates of and valid confidence intervals for nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (Biometrics, 2020), Williamson et al. (JASA, 2021), and Williamson and Feng (ICML, 2020).
Useful links