Man pages for benkeser/cvma
Cross-validation-based maximal association
| ci.cvAUC_withIC | ci.cvAUC_withIC |
| compare_control_diff | compare_control for taking a difference in cross-validated... |
| compare_control_logratio | compare_control for taking a ratio of cross-validated maximal... |
| compare_control_ratio | compare_control for taking a ratio of cross-validated maximal... |
| compare_cvma | Compare measures of association between two fits |
| cvma | Cross-validated maximal association measures |
| cv_risk_sl_auc | Cross-validated area under the receiver operating... |
| cv_risk_sl_nloglik | Cross-validated negative log-likelihood of the super learner |
| cv_risk_sl_r2 | Cross-validated non-parametric R-squared of the super learner |
| cv_risk_y_auc | Cross-validated area under the receiver operating... |
| cv_risk_y_nloglik | Cross-validated negative log-likelihood for evaluating... |
| cv_risk_y_r2 | Cross-validated nonparametric R-squared for evaluating... |
| dot-process_input | Unexported function from cvAUC package |
| ensemble_linear | Compute a linear ensemble of predictions |
| ensemble_logit_linear | Compute a logit-linear ensemble of predictions |
| get_fit | Fit a learner on training folds and get predictions on... |
| get_fold_out | Helper function to format the validation folds used in some... |
| get_fold_vector | Helper function to get a vector of fold assignments... |
| get_formatted_sl | Get a super learner fit for a given outcome with more... |
| get_learner_pred_out | Helper function to get super learner predictions formatted... |
| get_pred_out | Helper function to get learner prediction matrices formatted... |
| get_risk | Get cross-validated risk of entire procedure (i.e.,... |
| get_risk_input | Create input list for 'get_risk' |
| get_risk_learner | Get cross-validated risk of the super learner for a... |
| get_risk_learner_input | Create input list for 'get_risk_learner' |
| get_risk_sl | Get cross-validated risk of the super learner for a... |
| get_risk_sl_input | Create input list for 'get_risk_sl' |
| get_sl | Get super learner weights based on cross-validated learner... |
| get_sl_input | Create input list for 'get_sl' |
| get_sl_pred_out | Helper function to get super learner predictions formatted... |
| get_valid_pred_from_fit | Helper function to get validation fold predictions. Each... |
| get_valid_y | Helper function to get validation fold outcomes. |
| get_Y_out | Helper function to get outcomes in proper format needed for... |
| get_y_weight | Get outcome weights based on cross-validated super learner... |
| get_y_weight_input | Create input list for 'get_y_weight' |
| list_control_options | List all control options in the 'cvma' package. |
| make_fit_task_list | Helper function to make a task list for computing learner... |
| make_outer_learner_task_list | Helper function to make a task list for computing cv risks of... |
| make_outer_sl_task_list | Helper function to make a task list for computing the outer... |
| make_sl_task_list | Helper function to make a task list for computing super... |
| make_y_weight_task_list | Helper function to make a task list for computing outcome... |
| optim_risk_sl_auc | Cross-validated area under receiver operating characteristic... |
| optim_risk_sl_nloglik | Cross-validated negative log-likelihood for computing super... |
| optim_risk_sl_se | Cross-validated mean squared-error for computing super... |
| optim_risk_y_auc | Cross-validated area under the receiver operating... |
| optim_risk_y_nloglik | Cross-validated area under the receiver operating... |
| optim_risk_y_r2 | Cross-validated non-parametric R-squared for computing... |
| predict.cvma | Get predictions on cvma object |
| print.cvma | Print the output of 'cvma'. Only prints the cross-validated... |
| reweight_cvma | Changing options for super learner and outcome weighting... |
| search_fits_all_y | Helper function to search fits for particular training_folds. |
| search_fits_for_learner | Helper function to search fits for particular outcomes (or... |
| search_fits_for_training_folds | Helper function to search fits for particular outcomes (or... |
| search_fits_one_learner | Helper function to search fits for particular outcomes and... |
| search_fits_one_y | Helper function to search fits for particular outcomes and... |
| summary.cvma | Summarize results of 'cvma' fit. Can be used to summarize the... |
| trim_p | Helper function to trim a prediction |
| trim_qlogis | Helper function to compute a trimmed logit |
| weight_sl_01 | 0/1 weights for super learner (i.e., discrete super learner) |
| weight_sl_convex | Convex ensemble weights for super learner |
| weight_y_01 | Find single outcome with best risk |
| weight_y_convex | Compute optimized convex weights for outcomes |
