Package: HDBRR
Type: Package
Title: High Dimensional Bayesian Ridge Regression without MCMC
Version: 1.1.5
Authors@R: c(
    person("Blanca", "Monroy-Castillo", role = c("aut", "cre"),
           email = "blancamonroy.96@gmail.com"),
    person("Paulino", "Perez-Rodriguez", role = "ctb"),
    person("Jose", "Crossa", role = "ctb"),
    person("Sergio", "Perez-Elizalde", role = "aut")
    )
Description: 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.
License: GPL (>= 2)
Depends: R (>= 3.0.0)
Encoding: UTF-8
Imports: numDeriv, parallel, bigparallelr, bigstatsr, graphics, stats
NeedsCompilation: no
LazyData: true
Config/roxygen2/version: 8.1.0
Packaged: 2026-10-23 11:24:46 UTC; root
Author: Blanca Monroy-Castillo [aut, cre], Paulino Perez-Rodriguez
        [ctb], Jose Crossa [ctb], Sergio Perez-Elizalde [aut]
Maintainer: Blanca Monroy-Castillo <blancamonroy.96@gmail.com>
Repository: https://castlemon.r-universe.dev
Date/Publication: 2026-09-23 11:50:41 UTC
RemoteUrl: https://github.com/cran/HDBRR
RemoteRef: HEAD
RemoteSha: 5f45f8a8659c634b1328159feb63fd321692e311