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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | combreg_0.2.0.tar.gz |
563.5 KiB |
0.2.0 |
rolling linux/noble R-4.5 | combreg_0.2.0.tar.gz |
566.3 KiB |
0.2.0 |
rolling source/ R- | combreg_0.2.0.tar.gz |
403.6 KiB |
0.2.0 |
latest linux/jammy R-4.5 | combreg_0.2.0.tar.gz |
563.5 KiB |
0.2.0 |
latest linux/noble R-4.5 | combreg_0.2.0.tar.gz |
566.3 KiB |
0.2.0 |
latest source/ R- | combreg_0.2.0.tar.gz |
403.6 KiB |
0.2.0 |
2026-04-23 source/ R- | combreg_0.2.0.tar.gz |
0 B |