High Dimensional Bayesian Ridge Regression without MCMC R package HDBRR version 1.1.5 Implements Bayesian ridge regression for high-dimensional data without using Markov chain Monte Carlo (MCMC). Posterior computations are performed using singular value decomposition (SVD) or QR decomposition. The package also provides variable selection and prediction methods. Software Depends: R (>= 3.0.0) Imports: numDeriv, parallel, bigparallelr, bigstatsr, graphics, stats Blanca Monroy-Castillo <blancamonroy.96@gmail.com> Comprehensive R Archive Network (CRAN) Blanca Monroy-Castillo [aut, cre], Paulino Perez-Rodriguez [ctb], Jose Crossa [ctb], Sergio Perez-Elizalde [aut] GPL (>= 2) 2026-09-23 application/tgz https://CRAN.R-project.org/package=HDBRR doi:10.32614/CRAN.package.HDBRR