CRAN/E | abess

abess

Fast Best Subset Selection

Installation

About

Extremely efficient toolkit for solving the best subset selection problem . 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, ordinal regression, (sequential) principal component analysis, and robust principal component analysis. The other valuable features such as the best subset of group selection doi:10.1287/ijoc.2022.1241 and sure independence screening doi:10.1111/j.1467-9868.2008.00674.x are also provided.

Citation abess citation info
github.com/abess-team/abess
abess-team.github.io/abess/
abess.readthedocs.io
Copyright see file COPYRIGHTS
Bug report File report

Key Metrics

Version 0.4.8
R ≥ 3.1.0
Published 2023-09-19 219 days ago
Needs compilation? yes
License GPL (≥ 3)
License File
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Maintainer

Maintainer

Jin Zhu

zhuj37@mail2.sysu.edu.cn

Authors

Jin Zhu

aut / cre

Zezhi Wang

aut

Liyuan Hu

aut

Junhao Huang

aut

Kangkang Jiang

aut

Yanhang Zhang

aut

Borui Tang

aut

Shiyun Lin

aut

Junxian Zhu

aut

Canhong Wen

aut

Heping Zhang

aut

Xueqin Wang

aut

spectra contributors

cph

(Spectra implementation)

Material

README
NEWS
Reference manual
Package source

In Views

MachineLearning

Vignettes

An Introduction to abess

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

abess archive

Depends

R ≥ 3.1.0

Imports

Rcpp
MASS
methods
Matrix

Suggests

testthat
knitr
rmarkdown

LinkingTo

Rcpp
RcppEigen

Reverse Suggests

tramvs