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PDtoolkit
View on CRAN: Click
here
Download and install PDtoolkit package within the R console
Install from CRAN:
install.packages("PDtoolkit")
Install from Github:
library("remotes")
install_github("cran/PDtoolkit") Install by package version:
library("remotes")
install_version("PDtoolkit", "1.2.0") Attach the package and use:
library("PDtoolkit")
Maintained by
Andrija Djurovic
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-01-04
Latest Update: 2023-09-20
Description:
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.
How to cite:
Andrija Djurovic (2022). PDtoolkit: Collection of Tools for PD Rating Model Development and Validation. R package version 1.2.0, https://cran.r-project.org/web/packages/PDtoolkit. Accessed 30 Oct. 2026.
Previous versions and publish date:
Other packages that cited PDtoolkit R package
View PDtoolkit citation profile
Other R packages that PDtoolkit depends,
imports, suggests or enhances
Complete documentation for PDtoolkit
Functions, R codes and Examples using
the PDtoolkit R package
Some associated functions: auc.model . bivariate . boots.vld . cat.bin . cat.slice . confusion.matrix . constrained.logit . create.partitions . cutoff.palette . decision.tree . dp.testing . embedded.blocks . encode.woe . ensemble.blocks . evrs . fairness.vld . heterogeneity . hhi . homogeneity . imp.outliers . imp.sc . interaction.transformer . kfold.idx . kfold.vld . loans . normal.test . num.slice . nzv . power . pp.testing . predict.cdt . psi . replace.woe . rf.clustering . rf.interaction.transformer . rs.calibration . scaled.score . segment.vld . smote . staged.blocks . stepFWD . stepMIV . stepRPC . univariate . ush.bin . ush.test . woe.tbl .
Some associated R codes: 00_GLOBALS.R . 01_UNIVARIATE_ANALYSIS.R . 02_BIVARIATE_ANALYSIS.R . 03_CAT_RF_BINNING.R . 04_RF_CLUSTERING.R . 05_STEP_MIV.R . 06_MODEL_CV_BOOTS.R . 07_SEGMENT_VLD.R . 08_SCALED_SCORE.R . 09_CALIBRATION.R . 10_HETEROGENEITY.R . 11_HOMOGENEITY.R . 12_PREDICTIVE_POWER.R . 13_POWER_OF_PP_TESTS.R . 14_DISCRIMINATORY_POWER.R . 15_PSI.R . 16_PARTITIONS.R . 17_EVRS.R . 18_INTERACTION_TRANSFORMER.R . 19_STEP_FWD.R . 20_STEP_RPC.R . 21_STAGED_BLOCKS.R . 22_EMBEDDED_BLOCKS.R . 23_ENSEMBLE_BLOCKS.R . 24_NZV.R . 25_SMOTE.R . 26_CONSTRAINED_LOGIT.R . 27_RF_INTERACTION_TRANSFORMER.R . 28_HHI.R . 29_NORMAL_TEST.R . 30_CONFUSION_MATRIX.R . 31_U_SHAPE.R . 32_KFOLD_INDICES.R . 33_FAIRNESS_VLD.R . 34_DECISION_TREE.R . 55_HELPERS_.R . data.R . Full PDtoolkit package functions and examples
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