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abess  

Fast Best Subset Selection
View on CRAN: Click here


Download and install abess package within the R console
Install from CRAN:
install.packages("abess")

Install from Github:
library("remotes")
install_github("cran/abess")

Install by package version:
library("remotes")
install_version("abess", "0.4.9")



Attach the package and use:
library("abess")
Maintained by
Jin Zhu
[Scholar Profile | Author Map]
First Published: 2021-04-21
Latest Update: 2023-09-19
Description:
Extremely efficient toolkit for solving the best subset selection problem . This package is its R interface. The package implements and generalizes algorithms designed in 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 and sure independence screening are also provided.
How to cite:
Jin Zhu (2021). abess: Fast Best Subset Selection. R package version 0.4.9, https://cran.r-project.org/web/packages/abess. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2021-04-21 14:00), 0.2.0 (2021-07-31 15:40), 0.3.0 (2021-09-03 18:30), 0.4.0 (2021-12-08 17:50), 0.4.5 (2022-03-22 11:10), 0.4.6 (2022-11-06 06:10), 0.4.7 (2023-02-20 00:00), 0.4.8 (2023-09-19 15:20)
Other packages that cited abess R package
View abess citation profile
Other R packages that abess depends, imports, suggests or enhances
Complete documentation for abess
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