| cartesian_2D | Cartesian Product of Two Vectors | 
| ciAUC | Confidence Interval of AUC | 
| ciAUC.rocit | Confidence Interval of AUC | 
| ciROC | Confidence Interval of ROC curve | 
| ciROC.rocit | Confidence Interval of ROC curve | 
| ciROCbin | Confidence Interval of Binormal ROC Curve | 
| ciROCemp | Confidence Interval of Empirical ROC Curve | 
| convertclass | Converts Binary Vector into 1 and 0 | 
| Diabetes | Diabetes Data | 
| gainstable | Gains Table for Binary Classifier | 
| gainstable.default | Gains Table for Binary Classifier | 
| gainstable.rocit | Gains Table for Binary Classifier | 
| getsurvival | Survival Probability | 
| ksplot | KS Plot | 
| ksplot.rocit | KS Plot | 
| Loan | Loan Data | 
| measureit | Performance Metrics of Binary Classifier | 
| measureit.default | Performance Metrics of Binary Classifier | 
| measureit.rocit | Performance Metrics of Binary Classifier | 
| MLestimates | ML Estimate of Normal Parameters | 
| plot.gainstable | Plot '"gainstable"' Object | 
| plot.rocci | Plot ROC Curve with confidence limits | 
| plot.rocit | Plot ROC Curve | 
| print.gainstable | Print "gainstable" Object | 
| print.measureit | Print "measureit" Object | 
| print.rocci | Print 'rocci' Object | 
| print.rocit | Print 'rocit' Object | 
| print.rocitaucci | Print Confidence Interval of AUC | 
| rankorderdata | Rank order data | 
| rocit | ROC Analysis of Binary Classifier | 
| summary.rocit | Summary of rocit object | 
| trapezoidarea | Approximate Area with Trapezoid Rule |