Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression
Bayesian lasso Gibbs sampler: 2-block (beta–lambda2) variant
Bayesian lasso Gibbs sampler: 2-block (beta–sigma2) variant
Bayesian lasso PCG sampler: lambda2 collapsed over local scales
Bayesian lasso PCG sampler: sigma2 collapsed over local scales
Fast High-Dimensional Gibbs Samplers for Bayesian Lasso Regression
Normalize Response and Covariates
Penalized nested Gibbs sampler for Bayesian linear regression
Penalized PCG sampler: beta block, lambda2 collapsed over sigma2
Penalized PCG sampler: lambda2 collapsed over sigma2
Penalized PCG sampler: sigma2 collapsed over beta
Penalized PCG sampler: sigma2 collapsed over lambda2
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>.
Useful links