combreg: Bayesian Regression for Combinatorial Response Data

Bayesian regression whose response data are integer-valued vectors subject to combinatorial constraints in the form of Ay<=b. Implements the Metropolis-Hastings-within-Gibbs sampler of Zheng et al. (2026+) <doi:10.48550/arXiv.2504.11630>, an unconstrained probit baseline for comparison, benchmarking helpers, MCMC and regression diagnostics (effective sample sizes, split-Rhat, structured reports), plotting methods (trace, autocorrelation, violin, effective-sample-size, sampling-efficiency, residual heat map), and utilities for constraint validation (total unimodularity, feasibility) and data simulation.

Version:	0.2.0
Depends:	R (≥ 4.0)
Imports:	Rcpp, coda, grDevices, graphics, stats, truncnorm, utils
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	lpSolve, posterior, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-07-29
DOI:	10.32614/CRAN.package.combreg
Author:	Hugh Zheng [aut, cre, cph]
Maintainer:	Hugh Zheng <hugh.stats at gmail.com>
BugReports:	https://github.com/YuZh98/combreg/issues
License:	MIT + file LICENSE
URL:	https://github.com/YuZh98/combreg
NeedsCompilation:	yes
Citation:	combreg citation info
Materials:	README, NEWS
CRAN checks:	combreg results

Documentation:

Reference manual:	combreg.html , combreg.pdf
Vignettes:	Introduction to combreg (source, R code) Diagnostics and benchmarking (source, R code)

Downloads:

Package source:	combreg_0.2.0.tar.gz
Windows binaries:	r-devel: combreg_0.2.0.zip, r-release: combreg_0.2.0.zip, r-oldrel: combreg_0.2.0.zip
macOS binaries:	r-release (arm64): combreg_0.2.0.tgz, r-oldrel (arm64): combreg_0.2.0.tgz, r-release (x86_64): combreg_0.2.0.tgz, r-oldrel (x86_64): combreg_0.2.0.tgz

Linking:

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