betaBayes swMATH ID: 41055 Software Authors: Haiming Zhou, Xianzheng Huang Description: R package betaBayes: Bayesian Beta Regression. Provides a class of Bayesian beta regression models for the analysis of continuous data with support restricted to an unknown finite support. The response variable is modeled using a four-parameter beta distribution with the mean or mode parameter depending linearly on covariates through a link function. When the response support is known to be (0,1), the above class of models reduce to traditional (0,1) supported beta regression models. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou and Huang (2021, ”Bayesian beta regression for bounded responses with unknown supports”) <https://sites.google.com/view/haimingzhou/research>. Homepage: https://cran.r-project.org/web/packages/betaBayes/index.html Source Code: https://github.com/cran/betaBayes Dependencies: R Related Software: EMVS; RStan; GLMsData; pi-MASS; rstan; betareg; R2jags; Stan; JAGS; CODA; R Cited in: 1 Publication Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year Bayesian beta regression for bounded responses with unknown supports. Zbl 07464453Zhou, Haiming; Huang, Xianzheng 2022 Cited by 2 Authors 1 Huang, Xianzheng 1 Zhou, Haiming Cited in 1 Serial 1 Computational Statistics and Data Analysis Cited in 1 Field 1 Statistics (62-XX) Citations by Year