Package: BDWreg
Type: Package
Version: 1.3.0
Date: 2024-01-28
Author: Hamed Haselimashhadi <hamedhaseli@gmail.com>
Maintainer: Hamed Haselimashhadi <hamedhaseli@gmail.com>
Depends: R (>= 3.0)
Description: 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.
Title: Bayesian Inference for Discrete Weibull Regression
License: LGPL (>= 2)
Imports: coda, parallel, foreach, doParallel, MASS, methods, graphics,
        stats, utils, DWreg
NeedsCompilation: no
Repository: CRAN
Packaged: 2024-01-29 09:25:28 UTC; Hamed
Date/Publication: 2024-01-29 12:40:02 UTC
Built: R 4.6.0; ; 2026-04-28 23:47:00 UTC; unix
