HDBRR: High Dimensional Bayesian Ridge Regression without MCMC

The svd(singular value decomposition) or qr decomposition was using for the implementation, this avoid the recursion optimizing the time in the compute.

Version: 1.1.1
Depends: R (≥ 3.0.0)
Imports: numDeriv, parallel, bigstatsr, MASS, graphics
Published: 2021-09-22
Author: Sergio Perez-Elizalde Developer [aut], Blanca Monroy-Castillo Developer [aut, cre], Paulino Perez-Rodriguez User [ctb], Jose Crossa User [ctb]
Maintainer: Blanca Monroy-Castillo Developer <blancamonroy.96 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: HDBRR results


Reference manual: HDBRR.pdf
Vignettes: BGLR-extdoc
Package source: HDBRR_1.1.1.tar.gz
Windows binaries: r-devel: HDBRR_1.1.1.zip, r-release: HDBRR_1.1.1.zip, r-oldrel: HDBRR_1.1.1.zip
macOS binaries: r-release (arm64): HDBRR_1.1.1.tgz, r-release (x86_64): HDBRR_1.1.1.tgz, r-oldrel: HDBRR_1.1.1.tgz
Old sources: HDBRR archive


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