DBR: Discrete Beta Regression (original) (raw)
Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses. Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler (Neal (2003) <doi:10.1214/aos/1056562461>), as implemented in the R package MfUSampler (Mahani and Sharabiani (2017) <doi:10.18637/jss.v078.c01>).
| Version: | 1.4.1 |
|---|---|
| Depends: | R (≥ 3.5.0) |
| Imports: | MfUSampler, methods, coda |
| Published: | 2023-02-20 |
| DOI: | 10.32614/CRAN.package.DBR |
| Author: | Alireza Mahani [cre, aut], Mansour Sharabiani [aut], Alex Bottle [aut], Cathy Price [aut] |
| Maintainer: | Alireza Mahani <alireza.s.mahani at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | |
| CRAN checks: | DBR results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=DBRto link to this page.