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LassoHiDFastGibbs  

Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("LassoHiDFastGibbs", "0.1.5")



Attach the package and use:
library("LassoHiDFastGibbs")
Maintained by
Mohammad Javad Davoudabadi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-01-29
Latest Update: 2026-01-29
Description:
Provides fast and scalable Gibbs sampling algorithms for Bayesian Lasso regression model in high-dimensional settings. The package implements efficient partially collapsed and nested Gibbs samplers for Bayesian Lasso, with a focus on computational efficiency when the number of predictors is large relative to the sample size. Methods are described at Davoudabadi and Ormerod (2026) <https://github.com/MJDavoudabadi/LassoHiDFastGibbs>.
How to cite:
Mohammad Javad Davoudabadi (2026). LassoHiDFastGibbs: Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression. R package version 0.1.5, https://cran.r-project.org/web/packages/LassoHiDFastGibbs. Accessed 25 Oct. 2026.
Previous versions and publish date:
0.1.4 (2026-01-29 22:50), (2026-07-09 08:08)
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Functions, R codes and Examples using the LassoHiDFastGibbs R package
Full LassoHiDFastGibbs package functions and examples
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