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CRAN: Package LassoHiDFastGibbs

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

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>.

Version: 0.1.5
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppNumerical
Suggests: posterior
Published: 2026-02-22
DOI: 10.32614/CRAN.package.LassoHiDFastGibbs
Author: John Ormerod ORCID iD [aut], Mohammad Javad Davoudabadi [aut, cre, cph], Garth Tarr ORCID iD [aut], Samuel Mueller ORCID iD [aut], Jonathon Tidswell [ctb] (Contributed code to src/lasso_distribution.cpp (originally from BayesianLasso package))
Maintainer: Mohammad Javad Davoudabadi <mohammad.davoudabadi at qut.edu.au>
BugReports: https://github.com/MJDavoudabadi/LassoHiDFastGibbs/issues
License: GPL-3
Copyright: see file COPYRIGHTS
URL: https://github.com/MJDavoudabadi/LassoHiDFastGibbs
NeedsCompilation: yes
SystemRequirements: C++17
Citation: LassoHiDFastGibbs citation info
Materials: README, NEWS
CRAN checks: LassoHiDFastGibbs results

Documentation:

Reference manual: LassoHiDFastGibbs.html , LassoHiDFastGibbs.pdf

Downloads:

Package source: LassoHiDFastGibbs_0.1.5.tar.gz
Windows binaries: r-devel: LassoHiDFastGibbs_0.1.5.zip, r-release: LassoHiDFastGibbs_0.1.5.zip, r-oldrel: LassoHiDFastGibbs_0.1.5.zip
macOS binaries: r-release (arm64): LassoHiDFastGibbs_0.1.5.tgz, r-oldrel (arm64): LassoHiDFastGibbs_0.1.5.tgz, r-release (x86_64): LassoHiDFastGibbs_0.1.5.tgz, r-oldrel (x86_64): LassoHiDFastGibbs_0.1.5.tgz
Old sources: LassoHiDFastGibbs archive

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