DBR: Discrete Beta Regression
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 |
Documentation:
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