Package: Bayenet
Type: Package
Title: Bayesian Quantile Elastic Net for Genetic Study
Version: 0.2
Date: 2024-04-04
Authors@R: c( person("Xi", "Lu", role = c("aut", "cre"),
                      email = "xilu@ksu.edu"),
              person("Cen", "Wu", role = "aut"))
Description: As heavy-tailed error distribution and outliers in the
        response variable widely exist, models which are robust to data
        contamination are highly demanded. Here, we develop a novel
        robust Bayesian variable selection method with elastic net
        penalty for quantile regression in genetic analysis. In
        particular, the spike-and-slab priors have been incorporated to
        impose sparsity. An efficient Gibbs sampler has been developed
        to facilitate computation.The core modules of the package have
        been developed in 'C++' and R.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, stats, MCMCpack, base, gsl, VGAM, MASS, hbmem, SuppDists
RoxygenNote: 7.3.1
NeedsCompilation: yes
Config/pak/sysreqs: libgsl0-dev
Repository: https://xilustat.r-universe.dev
Date/Publication: 2025-03-22 03:17:20 UTC
RemoteUrl: https://github.com/xilustat/bayenet
RemoteRef: HEAD
RemoteSha: 78fc630b33aa92ccf56074dbe5f757bb05f3b434
Packaged: 2026-06-18 08:24:16 UTC; root
Author: Xi Lu [aut, cre],
  Cen Wu [aut]
Maintainer: Xi Lu <xilu@ksu.edu>