Collection of Tools for PD Rating Model Development and Validation

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Documentation for package ‘PDtoolkit’ version 1.2.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

auc.model	Area under curve (AUC)
bivariate	Bivariate analysis
boots.vld	Bootstrap model validation
cat.bin	Categorical risk factor binning
cat.slice	Slice categorical variable
confusion.matrix	Confusion matrix
constrained.logit	Constrained logistic regression
create.partitions	Create partitions (aka nested dummy variables)
cutoff.palette	Palette of cutoff values that minimize and maximize metrics from the confusion matrix
decision.tree	Custom decision tree algorithm
dp.testing	Testing the discriminatory power of PD rating model
embedded.blocks	Embedded blocks regression
encode.woe	Encode WoE
ensemble.blocks	Ensemble blocks regression
evrs	Modelling the Economic Value of Credit Rating System
fairness.vld	Model fairness validation
heterogeneity	Testing heterogeneity of the PD rating model
hhi	Herfindahl-Hirschman Index (HHI)
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.idx	Indices for K-fold validation
kfold.vld	K-fold model cross-validation
loans	German Credit Data
normal.test	Multi-period predictive power test
num.slice	Slice numeric variable
nzv	Near-zero variance
power	Power of statistical tests for predictive ability testing
pp.testing	Testing the predictive power of PD rating model
predict.cdt	Predict method for custom decision tree
psi	Population Stability Index (PSI)
replace.woe	Replace modalities of risk factor with weights of evidence (WoE) value
rf.clustering	Risk factor clustering
rf.interaction.transformer	Extract interactions from random forest
rs.calibration	Calibration of the rating scale
scaled.score	Scaling the probabilities
segment.vld	Model segment validation
smote	Synthetic Minority Oversampling Technique (SMOTE)
staged.blocks	Staged blocks regression
stepFWD	Customized stepwise regression with p-value and trend check
stepFWDr	Customized stepwise regression with p-value and trend check on raw risk factors
stepMIV	Stepwise logistic regression based on marginal information value (MIV)
stepRPC	Stepwise logistic regression based on risk profile concept
stepRPCr	Stepwise regression based on risk profile concept and raw risk factors
univariate	Univariate analysis
ush.bin	U-shape binning algorithm
ush.test	Testing for U-shape relation
woe.tbl	Weights of evidence (WoE) table