BDWreg
Bayesian Inference for Discrete Weibull Regression
Last update: 29 January 2024
Copyright license: GNU Library General Public License, version 2.0, GNU Lesser General Public License, version 2.1, GNU Lesser General Public License, version 3.0
Software version identifier: 1.2.0, 1.0.0, 1.3.0
A Bayesian regression model for discrete response, where the conditional distribution is modelled via a discrete Weibull distribution. This package provides an implementation of Metropolis-Hastings and Reversible-Jumps algorithms to draw samples from the posterior. It covers a wide range of regularizations through any two parameter prior. Examples are Laplace (Lasso), Gaussian (ridge), Uniform, Cauchy and customized priors like a mixture of priors. An extensive visual toolbox is included to check the validity of the results as well as several measures of goodness-of-fit.
This page was built for software: BDWreg
