BDWreg: 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.

Author
Hamed Haselimashhadi <hamedhaseli@gmail.com>
Date of publication
2016-01-12 12:13:15
Maintainer
Hamed Haselimashhadi <hamedhaseli@gmail.com>
License
LGPL (>= 2)
Version
1.0.0
URLs

View on CRAN

Man pages

bdw
Bayesian parameter estimation for discrete Weibull regression
bdw.multicore
Producing several chains from a MCMC object of class 'bdw'
plot.bdw
Plot a MCMC object of class 'bdw'
summary.bdw
Summary for a MCMC object of class 'bdw'

Files in this package

BDWreg
BDWreg/NAMESPACE
BDWreg/R
BDWreg/R/bayesian.dw.R
BDWreg/R/others.R
BDWreg/R/zzz.R
BDWreg/R/main.R
BDWreg/MD5
BDWreg/DESCRIPTION
BDWreg/man
BDWreg/man/summary.bdw.Rd
BDWreg/man/bdw.multicore.Rd
BDWreg/man/bdw.Rd
BDWreg/man/plot.bdw.Rd