LassoHiDFastGibbs: Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression

2026 Dataset Open access

Read full text
Authors: John Ormerod, Mohammad Javad Davoudabadi, Garth Tarr, Samuel Mueller
DOI: 10.32614/cran.package.lassohidfastgibbs
Cited by: 0

Abstract

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) .

Fields of Study & Subjects

Markov Chains and Monte Carlo Methods Statistical Methods and Inference Statistical Methods and Bayesian Inference

Publication details

Publication date
29 January 2026
Document type
Dataset