Package: bestridge
Type: Package
Title: A Comprehensive R Package for Best Subset Selection
Version: 1.0.7
Date: 2021-10-10
Authors@R: c(
  person(given = "Liyuan", family = "Hu", email = "huly5@mail2.sysu.edu.cn", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2064-8990")),
  person(given = "Jin", family = "Zhu", email = "zhuj37@mail2.sysu.edu.cn", role = c("aut"), comment = c(ORCID = "0000-0001-8550-5822")),
  person(given = "Junxian", family="Zhu", email = "zhujx1@mail2.sysu.edu.cn", role=c("aut")),
  person(given = "Kangkang", family = "Jiang", email = "jiangkk3@mail2.sysu.edu.cn" ,role = c("aut")),
  person(given = "Yanhang", family = "Zhang", email = "zhangyh98@ruc.edu.cn", role = c("aut")),
  person(given = "Xueqin", family = "Wang", email = "wangxq20@ustc.edu.cn", role = c("aut"), comment = c(ORCID = "0000-0001-5205-9950")),
  person(given = "Canhong", family = "Wen", email = "wencanhong@gmail.com", role = c("aut")))
Maintainer: Liyuan Hu <huly5@mail2.sysu.edu.cn>
Description: The bestridge package is designed to provide a one-stand service for users to successfully carry out best ridge regression in various complex situations via the primal dual active set algorithm proposed by Wen, C., Zhang, A., Quan, S. and Wang, X. (2020) <doi:10.18637/jss.v094.i04>. This package allows users to perform the regression, classification, count regression and censored regression for (ultra) high dimensional data, and it also supports advanced usages like group variable selection and nuisance variable selection.
License: GPL-3
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.3), Matrix(>= 1.2-6), MASS, pheatmap, survival
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-10-10 11:12:50 UTC; test
Author: Liyuan Hu [aut, cre] (<https://orcid.org/0000-0003-2064-8990>),
  Jin Zhu [aut] (<https://orcid.org/0000-0001-8550-5822>),
  Junxian Zhu [aut],
  Kangkang Jiang [aut],
  Yanhang Zhang [aut],
  Xueqin Wang [aut] (<https://orcid.org/0000-0001-5205-9950>),
  Canhong Wen [aut]
Repository: CRAN
Date/Publication: 2021-10-10 11:40:02 UTC
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