Package: Bayesiangammareg 0.1.1

Bayesiangammareg: Double Generalized Gamma Regression Models

Fits double generalized Gamma regression models from a Bayesian perspective, where both the mean and shape parameters are modeled simultaneously using flexible link functions. The methodology is based on Cepeda-Cuervo and Urdinola (2012) <doi:10.1080/03610918.2011.600500> and extended in Cepeda-Cuervo (2026), 'Double Generalized Linear Models: Likelihood and Bayesian Methods' (ISBN: 9781041169970). The package provides parameter estimation, model fitting, and model comparison tools, including Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC).

Authors:Arturo Camargo-Lozano [aut, cre], Edilberto Cepeda-Cuervo [aut]

Bayesiangammareg_0.1.1.tar.gz
Bayesiangammareg_0.1.1.zip(r-4.7)Bayesiangammareg_0.1.1.zip(r-4.6)Bayesiangammareg_0.1.1.zip(r-4.5)
Bayesiangammareg_0.1.1.tgz(r-4.6-any)Bayesiangammareg_0.1.1.tgz(r-4.5-any)
Bayesiangammareg_0.1.1.tar.gz(r-4.7-any)Bayesiangammareg_0.1.1.tar.gz(r-4.6-any)
Bayesiangammareg_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
Bayesiangammareg/json (API)

# Install 'Bayesiangammareg' in R:
install.packages('Bayesiangammareg', repos = c('https://arturloza.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 298 downloads 8 exports 1 dependencies

Last updated from:c1ab4409fb. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK116
source / vignettesOK165
linux-release-x86_64OK109
macos-release-arm64OK99
macos-oldrel-arm64OK91
windows-develOK102
windows-releaseOK84
windows-oldrelOK64
wasm-releaseOK94

Exports:BayesiangammaregcriteriaGammaIdentityGammaLoggammaresidualsprint.Bayesiangammaregprint.summary.Bayesiangammaregsummary.Bayesiangammareg

Dependencies:mvtnorm