# Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples

## Documentation for package ‘nlpred’ version 1.0.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

.Dy | Compute one of the terms of the efficient influence function
.estim_fn | An estimating function for cvAUC
.estim_fn_nested_cv | An estimating function for cvAUC with initial estimates generated via nested cross-validation
.get_auc | Compute the AUC given the cdf and pdf of psi
.get_cv_estim | Helper function to turn prediction_list into CV estimate of SCRNP
.get_density | Function to estimate density needed to evaluate standard errors.
.get_nested_cv_quantile | Helper function to get quantile for a single training fold data when nested CV is used.
.get_one_fold | Helper function to get results for a single cross-validation fold
.get_predictions | Worker function for fitting prediction functions (possibly in parallel)
.get_psi_distribution | Compute the conditional (given Y = y) estimated distribution of psi
.get_psi_distribution_nested_cv | Compute the conditional (given Y = y) CV-estimated distribution of psi
.get_quantile | Helper function to get quantile for a single training fold data when nested CV is NOT used.
.make_long_data | Worker function to make long form data set needed for CVTMLE targeting step
.make_long_data_nested_cv | Worker function to make long form data set needed for CVTMLE targeting step when nested cv is used
.make_targeting_data | Helper function for making data set in proper format for CVTMLE
.process_input | Unexported function from cvAUC package
adult | adult
bank | bank
boot_auc | Compute the bootstrap-corrected estimator of AUC.
boot_scrnp | Compute the bootstrap-corrected estimator of SCRNP.
cardio | Cardiotocography
ci.cvAUC_withIC | ci.cvAUC_withIC
cv_auc | Estimates of CVAUC
cv_scrnp | Estimates of CV SCNP
drugs | drugs
fluc_mod_optim_0 | Helper function for CVTMLE grid search
fluc_mod_optim_1 | Helper function for CVTMLE grid search
F_nBn_star | Compute the targeted conditional cumulative distribution of the learner at a point
F_nBn_star_nested_cv | Compute the targeted conditional cumulative distribution of the learner at a point where the initial distribution is based on cross validation
glmnet_wrapper | Wrapper for fitting a lasso using package 'glmnet'.
glm_wrapper | Wrapper for fitting a logistic regression using 'glm'.
lpo_auc | Compute the leave-pair-out cross-validation estimator of AUC.
one_boot_auc | Internal function used to perform one bootstrap sample. The function 'try's to fit 'learner' on a bootstrap sample. If for some reason (e.g., the bootstrap sample contains no observations with 'Y = 1') the learner fails, then the function returns 'NA'. These 'NA's are ignored later when computing the bootstrap corrected estimate.
one_boot_scrnp | Internal function used to perform one bootstrap sample. The function 'try's to fit 'learner' on a bootstrap sample. If for some reason (e.g., the bootstrap sample contains no observations with 'Y = 1') the learner fails, then the function returns 'NA'. These 'NA's are ignored later when computing the bootstrap corrected estimate.
print.cvauc | Print results of cv_auc
print.scrnp | Print results of cv_scrnp
randomforest_wrapper | Wrapper for fitting a random forest using randomForest.
ranger_wrapper | Wrapper for fitting a random forest using ranger.
stepglm_wrapper | Wrapper for fitting a forward stepwise logistic regression using 'glm'.
superlearner_wrapper | Wrapper for fitting a super learner based on 'SuperLearner'.
wine | wine
xgboost_wrapper | Wrapper for fitting eXtreme gradient boosting via 'xgboost'