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: 2026-10-05 10:02:36 UTC; root
Imports: coda, parallel, foreach, doParallel, MASS, methods, graphics,
        stats, utils, DWreg
URL: http://hamedhaseli.webs.com
NeedsCompilation: no
Repository: https://hamedhm.r-universe.dev
Date/Publication: 2017-02-17 13:37:54 UTC
RemoteUrl: https://github.com/hamedhm/bdwreg
RemoteRef: HEAD
RemoteSha: aabf2aa8e44b1544baae696f949246ba09beb68f