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

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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'