Package: BDWreg
Type: Package
Version: 1.2.0
Date: 2017-02-16
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)
Packaged: 2017-02-17 10:24:44 UTC; hamedhm
Imports: coda, parallel, foreach, doParallel, MASS, methods, graphics,
        stats, utils, DWreg
URL: http://hamedhaseli.webs.com
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-02-17 14:37:54
Built: R 4.0.2; ; 2020-07-16 22:16:54 UTC; unix
