Package index • restrictedROC

All functions

apply_restriction(): Apply a (nested list) of rROC results to new data

default_part_colors: This code here defines global variables for the package restrictedROC

generate_density_values(): Generate values for given densities

melt_gendata(): Melt generated data

merge_applied(): Merge (cbind) applied rROC results

perf_ROC(): Performance of ROC curves

perf_pROC(): Performance ROC curves (pROC)

plot_ROC_cdf(): ROC curve for given cumulative distribution functions

plot_ROC_theoretical(): ROC curve for positive cumulative distribution and negative quantile function

plot_density_ROC(): Plot density + ROC

plot_density_ROC_empirical(): Plot density + ROC

plot_density_ROC_str(): Plot density + ROC based on stats::_

plot_density_empirical(): Plot empirical densities kernel estimate

plot_density_rROC_empirical(): Plot 4 rROC plots

plot_distributions_2(): Plot exactly 2 distributions

plot_distributions_multiple(): Plot multiple (usually >2) distributions

plot_rROC(): plot ROC including AUC significance

plot_rROC_joint(): Plot ROC curve with rzAUC values inside

plot_rROC_part(): Plot (restricted) ROC curves

plot_rROC_single(): plot ROC including AUC significance

plot_rROC_theoretical(): Plot (restricted) ROC curves for theoretic distributions

plot_rzAUCs(): Plot rzAUC vs FPR

predict(<restrictedROC>): S3 class predict for class "restrictedROC"

predict_rROC_h2o(): Predict new data with a trained model

prepare_modeldata(): Prepare model data

prepare_modeldata(<data.frame>): Prepare model data

rROC(): Restriction for multiple dependent and independent variables

rROC(<data.frame>): Restriction for multiple dependent and independent variables

rROC(<matrix>): rROC on a matrix of (samples x features)

rROC(<numeric>): rROC on a single numeric vector

sim(): Simulate values from distributions

simple_rROC(): restricted ROC

simple_rROC_interpret(): restricted ROC interpretation

simple_rROC_permutation(): restricted ROC

summary(<rROC>): Give a summary of a rROC() result

train_rROC_h2o(): Train a predictive model using (rROC-preprocessed) data