PDtoolkit - Collection of Tools for PD Rating Model Development and
Validation
The goal of this package is to cover the most common steps
in probability of default (PD) rating model development and
validation. The main procedures available are those that refer
to univariate, bivariate, multivariate analysis, calibration
and validation. Along with accompanied 'monobin' and
'monobinShiny' packages, 'PDtoolkit' provides functions which
are suitable for different data transformation and modeling
tasks such as: imputations, monotonic binning of numeric risk
factors, binning of categorical risk factors, weights of
evidence (WoE) and information value (IV) calculations, WoE
coding (replacement of risk factors modalities with WoE
values), risk factor clustering, area under curve (AUC)
calculation and others. Additionally, package provides set of
validation functions for testing homogeneity, heterogeneity,
discriminatory and predictive power of the model.
