| auc.model | Area under curve (AUC) |
| bivariate | Bivariate analysis |
| boots.vld | Bootstrap model validation |
| cat.bin | Categorical risk factor binning |
| create.partitions | Create partitions (aka nested dummy variables) |
| dp.testing | Testing the discriminatory power of PD rating model |
| evrs | Modelling the Economic Value of Credit Rating System |
| heterogeneity | Testing heterogeneity of the PD rating model |
| homogeneity | Testing homogeneity of the PD rating model |
| imp.outliers | Imputation methods for outliers |
| imp.sc | Imputation methods for special cases |
| interaction.transformer | Extract risk factors interaction from decision tree |
| kfold.vld | K-fold model cross-validation |
| loans | German Credit Data |
| power | Power of statistical tests for predictive ability testing |
| pp.testing | Testing the predictive power of PD rating model |
| psi | Population Stability Index (PSI) |
| replace.woe | Replace modalities of risk factor with weights of evidence (WoE) value |
| rf.clustering | Risk factor clustering |
| rs.calibration | Calibration of the rating scale |
| scaled.score | Scaling the probabilities |
| segment.vld | Model segment validation |
| stepMIV | Stepwise logistic regression based on marginal information value (MIV) |
| univariate | Univariate analysis |
| woe.tbl | Weights of evidence (WoE) table |