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BDWreg  

Bayesian Inference for Discrete Weibull Regression
View on CRAN: Click here


Download and install BDWreg package within the R console
Install from CRAN:
install.packages("BDWreg")

Install from Github:
library("remotes")
install_github("cran/BDWreg")

Install by package version:
library("remotes")
install_version("BDWreg", "1.3.0")



Attach the package and use:
library("BDWreg")
Maintained by
Hamed Haselimashhadi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-01-12
Latest Update: 2017-02-17
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.
How to cite:
Hamed Haselimashhadi (2016). BDWreg: Bayesian Inference for Discrete Weibull Regression. R package version 1.3.0, https://cran.r-project.org/web/packages/BDWreg. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0.0 (2016-01-12 12:13), 1.2.0 (2017-02-17 14:37)
Other packages that cited BDWreg R package
View BDWreg citation profile
Other R packages that BDWreg depends, imports, suggests or enhances
Complete documentation for BDWreg
Functions, R codes and Examples using the BDWreg R package
Some associated functions: bdw.multicore . bdw . plot.bdw . summary.bdw . 
Some associated R codes: bayesian.dw.R . main.R . others.R . zzz.R .  Full BDWreg package functions and examples
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