Package: HDBRR
Type: Package
Title: High Dimensional Bayesian Ridge Regression without MCMC
Version: 1.1.4
Authors@R: c(person("Sergio Perez-Elizalde", "Developer", role = "aut"),
             person("Blanca Monroy-Castillo", "Developer", role = c("aut","cre"), 
             email = "blancamonroy.96@gmail.com"),
             person("Paulino Perez-Rodriguez", "User", role = "ctb"),
	    person("Jose Crossa", "User", role = "ctb"))
Description: Ridge regression provide biased estimators of the regression parameters with lower variance. The HDBRR ("High Dimensional Bayesian Ridge Regression") function fits Bayesian Ridge regression without MCMC, this one uses the SVD or QR decomposition for the posterior computation.
License: GPL (>= 2)
Depends: R (>= 3.0.0)
Encoding: UTF-8
Imports: numDeriv, parallel, bigstatsr, MASS, graphics
RoxygenNote: 7.2.1
NeedsCompilation: no
LazyData: true
Packaged: 2022-10-05 22:41:42 UTC; monroy
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@gmail.com>
Repository: CRAN
Date/Publication: 2022-10-05 23:10:08 UTC
Built: R 4.1.3; ; 2023-04-17 18:53:23 UTC; windows
