A Bayesian regression model for discrete response, where the conditional distribution is modelled via a discrete Weibull distribution. This package provides an implementation of MetropolisHastings and ReversibleJumps 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 goodnessoffit.
Package details 


Author  Hamed Haselimashhadi <hamedhaseli@gmail.com> 
Date of publication  20170217 14:37:54 
Maintainer  Hamed Haselimashhadi <hamedhaseli@gmail.com> 
License  LGPL (>= 2) 
Version  1.2.0 
URL  http://hamedhaseli.webs.com 
Package repository  View on CRAN 
Installation 
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