Bayesian Regression for Combinatorial Response Data R package combreg version 0.2.0 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. Software Depends: R (>= 4.0) Imports: Rcpp, coda, grDevices, graphics, stats, truncnorm, utils LinkingTo: Rcpp, RcppArmadillo Suggests: lpSolve, posterior, testthat (>= 3.0.0), knitr, rmarkdown Hugh Zheng <hugh.stats@gmail.com> Comprehensive R Archive Network (CRAN) Hugh Zheng [aut, cre, cph] MIT + file LICENSE (https://CRAN.R-project.org/package=combreg/LICENSE) 2026-07-29 application/tgz https://CRAN.R-project.org/package=combreg doi:10.32614/CRAN.package.combreg