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combreg  

Bayesian Regression for Combinatorial Response Data
View on CRAN: Click here


Download and install combreg package within the R console
Install from CRAN:
install.packages("combreg")

Install from Github:
library("remotes")
install_github("cran/combreg")

Install by package version:
library("remotes")
install_version("combreg", "0.2.0")



Attach the package and use:
library("combreg")
Maintained by
Hugh Zheng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-29
Latest Update: 2026-07-29
Description:
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.
How to cite:
Hugh Zheng (2026). combreg: Bayesian Regression for Combinatorial Response Data. R package version 0.2.0, https://cran.r-project.org/web/packages/combreg. Accessed 10 Nov. 2026.
Previous versions and publish date:
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Complete documentation for combreg
Functions, R codes and Examples using the combreg R package
Full combreg package functions and examples
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