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: 1.2.3
Depends: R (≥ 3.5.0)
Imports: MfUSampler, methods
Published: 2022-03-24
Author: Alireza Mahani [cre, aut], Mansour Sharabiani [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:

Reference manual: DBR.pdf
Vignettes: Discretised Beta Regression

Downloads:

Package source: DBR_1.2.3.tar.gz
Windows binaries: r-devel: DBR_1.2.3.zip, r-release: DBR_1.2.3.zip, r-oldrel: DBR_1.2.3.zip
macOS binaries: r-release (arm64): DBR_1.2.3.tgz, r-oldrel (arm64): DBR_1.2.3.tgz, r-release (x86_64): DBR_1.2.3.tgz, r-oldrel (x86_64): DBR_1.2.3.tgz
Old sources: DBR archive

Linking:

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