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:

Reference manual:	DBR.pdf
Vignettes:	Bayesian Discretised Beta Regression

Downloads:

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DBR to link to this page.