Bayesian Inference for Discrete Weibull Regression

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.


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install.packages("BDWreg")

1.2.0 by Hamed Haselimashhadi, 2 years ago


http://hamedhaseli.webs.com


Browse source code at https://github.com/cran/BDWreg


Authors: Hamed Haselimashhadi <[email protected]>


Documentation:   PDF Manual  


LGPL (>= 2) license


Imports coda, parallel, foreach, doParallel, MASS, methods, graphics, stats, utils, DWreg


See at CRAN