abess: Fast Best Subset Selection

Extremely efficient toolkit for solving the best subset selection problem <arXiv:2110.09697>. This package is its R interface. The package implements and generalizes algorithms designed in <doi:10.1073/pnas.2014241117> that exploits a novel sequencing-and-splicing technique to guarantee exact support recovery and globally optimal solution in polynomial times for linear model. It also supports best subset selection for logistic regression, Poisson regression, Cox proportional hazard model, Gamma regression, multiple-response regression, multinomial logistic regression, (sequential) principal component analysis, and robust principal component analysis. The other valuable features such as the best subset of group selection <arXiv:2104.12576> and sure independence screening <doi:10.1111/j.1467-9868.2008.00674.x> are also provided.

Version: 0.4.0
Depends: R (≥ 3.1.0)
Imports: Rcpp, MASS, methods, Matrix
LinkingTo: Rcpp, RcppEigen
Suggests: testthat, knitr, rmarkdown
Published: 2021-12-08
Author: Jin Zhu ORCID iD [aut, cre], Liyuan Hu [aut], Junhao Huang [aut], Kangkang Jiang [aut], Yanhang Zhang [aut], Zezhi Wang [aut], Borui Tang [aut], Shiyun Lin [aut], Junxian Zhu [aut], Canhong Wen [aut], Heping Zhang ORCID iD [aut], Xueqin Wang ORCID iD [aut], spectra contributors [cph] (Spectra implementation)
Maintainer: Jin Zhu <zhuj37 at mail2.sysu.edu.cn>
BugReports: https://github.com/abess-team/abess/issues
License: GPL (≥ 3) | file LICENSE
Copyright: see file COPYRIGHTS
URL: https://github.com/abess-team/abess, https://abess-team.github.io/abess/, https://abess.readthedocs.io
NeedsCompilation: yes
SystemRequirements: C++11
Citation: abess citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: abess results


Reference manual: abess.pdf
Vignettes: An Introduction to abess
Positive response: Poisson and Gamma regression


Package source: abess_0.4.0.tar.gz
Windows binaries: r-devel: abess_0.4.0.zip, r-devel-UCRT: abess_0.4.0.zip, r-release: abess_0.4.0.zip, r-oldrel: abess_0.4.0.zip
macOS binaries: r-release (arm64): abess_0.4.0.tgz, r-release (x86_64): abess_0.4.0.tgz, r-oldrel: abess_0.4.0.tgz
Old sources: abess archive


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