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.

Nonnegative Integer Solutions of Linear Diophantine Equations with Applications

Routines for enumerating all existing nonnegative integer solutions of a linear Diophantine equation. The package provides routines for solving 0-1, bounded and unbounded knapsack problems; 0-1, bounded and unbounded subset sum problems; additive partitioning of natural numbers; and one-dimensional bin-packing problem.

Generate Visual Predictive Checks (VPC) Using 'shiny'

Utilize the 'shiny' interface to parameterize a Visual Predictive Check (VPC), including selecting from different binning or binless methods and performing stratification, censoring, and prediction correction. Generate the underlying 'tidyvpc' and 'ggplot2' code directly from the user interface and download R or Rmd scripts to reproduce the VPCs in R.

Soundscape Spectral Metrics

Accessible and flexible implementation of spectral ecoacoustic indices. The functions were design to accommodate a variety of sampling designs. Users can tailor calculations by specifying spectrogram time bin size, amplitude thresholds and normality tests. By simplifying computation and standardizing reproducible methods, the package aims to support ecoacoustics studies.

Interface to the 'HWSD' Web Services

Programmatic interface to the Harmonized World Soil Database 'HWSD' web services (< https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1247>). Allows for easy downloads of 'HWSD' soil data directly to your R workspace or your computer. Routines for both single pixel data downloads and gridded data are provided.

Combined Visualisation of Phylogenetic and Epidemiological Data

A collection of utilities and 'ggplot2' extensions to assist with visualisations in genomic epidemiology. This includes the 'phylepic' chart, a visual combination of a phylogenetic tree and a matched epidemic curve. The included 'ggplot2' extensions such as date axes binned by week are relevant for other applications in epidemiology and beyond. The approach is described in Suster et al. (2024) .

Various Useful Web Tools (Including Full CRAN Dataset Search and Fetch)

A set of useful web tools to improve your productivity. Including: searching DuckDuckGo; finding and loading datasets across all CRAN packages (not just those you've installed); sharing a file to a paste-bin; getting a fast GUID; useful info on all countries; Random Seinfeld show quotes; Seinfeld guessing game.

Interactive 3D Surface Plots for Multi-Factor Interaction Visualization

Visualize interactions between multiple experimental factors using interactive 3D surface plots powered by 'plotly'. Instead of examining combinatorial pairwise interaction plots, map factor combinations to response surfaces and use surface crossings as geometric indicators of interaction effects. Supports continuous, categorical, and mixed factor designs with automatic binning for continuous conditioning variables.

Mapping ML Scores to Calibrated Predictions

Transforms your uncalibrated Machine Learning scores to well-calibrated prediction estimates that can be interpreted as probability estimates. The implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0). Please cite this paper: Schwarz J and Heider D, Bioinformatics 2019, 35(14):2458-2465.

Bayesian Meta-Analysis with Publications Bias and P-Hacking

Tools for Bayesian estimation of meta-analysis models that account for publications bias or p-hacking. For publication bias, this package implements a variant of the p-value based selection model of Hedges (1992) with discrete selection probabilities. It also implements the mixture of truncated normals model for p-hacking described in Moss and De Bin (2019) .