Package: abess 0.4.9

Jin Zhu

abess: Fast Best Subset Selection

Extremely efficient toolkit for solving the best subset selection problem <https://www.jmlr.org/papers/v23/21-1060.html>. 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.

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]

abess_0.4.9.tar.gz
abess_0.4.9.tar.gz(r-4.5-noble)abess_0.4.9.tar.gz(r-4.4-noble)
abess_0.4.9.tgz(r-4.4-emscripten)abess_0.4.9.tgz(r-4.3-emscripten)
abess.pdf |abess.html
abess/json (API)
NEWS

# Install 'abess' in R:
install.packages('abess', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/abess-team/abess/issues

Pkgdown:https://abess-team.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • trim32 - The Bardet-Biedl syndrome Gene expression data

4.28 score 6 stars 63 scripts 818 downloads 7 exports 5 dependencies

Last updated 3 months agofrom:5070b6062c. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-linux-x86_64OKNov 09 2024

Exports:abessabesspcaabessrpcaextractgenerate.datagenerate.matrixgenerate.spc.matrix

Dependencies:latticeMASSMatrixRcppRcppEigen

Quick start for abess: Linear regression

Rendered fromv01-abess-guide.Rmdusingknitr::rmarkdownon Nov 09 2024.

Last update: 2024-09-10
Started: 2021-07-31