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Bayesiangammareg
View on CRAN: Click
here
Download and install Bayesiangammareg package within the R console
Install from CRAN:
install.packages("Bayesiangammareg")
Install from Github:
library("remotes")
install_github("cran/Bayesiangammareg") Install by package version:
library("remotes")
install_version("Bayesiangammareg", "0.1.1") Attach the package and use:
library("Bayesiangammareg")
Maintained by
Arturo Camargo Lozano
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-06
Latest Update: 2020-02-06
Description:
Adjust the Gamma regression models from a Bayesian perspective described by Cepeda and Urdinola (2012) , modeling the parameters of mean and shape and using different link functions for the parameter associated to the mean. And calculates different adjustment statistics such as the Akaike information criterion and Bayesian information criterion.
How to cite:
Arturo Camargo Lozano (2020). Bayesiangammareg: Double Generalized Gamma Regression Models. R package version 0.1.1, https://cran.r-project.org/web/packages/Bayesiangammareg. Accessed 29 Oct. 2026.
Previous versions and publish date:
0.1.0 (2020-02-06 11:50), (2026-07-09 07:58)
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imports, suggests or enhances
Complete documentation for Bayesiangammareg
Functions, R codes and Examples using
the Bayesiangammareg R package
Some associated functions: Bayesiangammareg . GammaIdentity . GammaLog . criteria . gammaresiduals . print.Bayesiangammareg . print.summary.Bayesiangammareg . summary.Bayesiangammareg .
Some associated R codes: Bayesiangammareg.R . GammaIdentity.R . GammaLog.R . criteria.R . gammaresiduals.R . print.Bayesiangammareg.R . print.summary.Bayesiangammareg.R . summary.Bayesiangammareg.R . Full Bayesiangammareg package functions and examples
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