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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: | ChangeLog |
| CRAN checks: | DBR results |
| Reference manual: | DBR.pdf |
| Vignettes: |
Bayesian Discretised Beta Regression |
| Package source: | DBR_1.4.1.tar.gz |
| Windows binaries: | r-devel: DBR_1.4.1.zip, r-release: DBR_1.4.1.zip, r-oldrel: DBR_1.4.1.zip |
| macOS binaries: | r-release (arm64): DBR_1.4.1.tgz, r-oldrel (arm64): DBR_1.4.1.tgz, r-release (x86_64): DBR_1.4.1.tgz, r-oldrel (x86_64): DBR_1.4.1.tgz |
| Old sources: | DBR archive |
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