Package: msaenet 3.1.2.9000

msaenet: Multi-Step Adaptive Estimation Methods for Sparse Regressions

Multi-step adaptive elastic-net (MSAENet) algorithm for feature selection in high-dimensional regressions proposed in Xiao and Xu (2015) <doi:10.1080/00949655.2015.1016944>, with support for multi-step adaptive MCP-net (MSAMNet) and multi-step adaptive SCAD-net (MSASNet) methods.

Authors:Nan Xiao [aut, cre], Qing-Song Xu [aut]

msaenet_3.1.2.9000.tar.gz
msaenet_3.1.2.9000.zip(r-4.7)msaenet_3.1.2.9000.zip(r-4.6)msaenet_3.1.2.9000.zip(r-4.5)
msaenet_3.1.2.9000.tgz(r-4.6-any)msaenet_3.1.2.9000.tgz(r-4.5-any)
msaenet_3.1.2.9000.tar.gz(r-4.7-any)msaenet_3.1.2.9000.tar.gz(r-4.6-any)
msaenet_3.1.2.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
msaenet/json (API)
NEWS

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

Bug tracker:https://github.com/nanxstats/msaenet/issues

Pkgdown/docs site:https://nanx.me

On CRAN:

Conda:

false-positive-controlhigh-dimensional-datalinear-regressionmachine-learningvariable-selection

7.64 score 13 stars 6 packages 65 scripts 5.7k downloads 1 mentions 19 exports 12 dependencies

Last updated from:8cb5ef6ffc. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK130
source / vignettesOK198
linux-release-x86_64OK147
macos-release-arm64OK95
macos-oldrel-arm64OK113
windows-develOK121
windows-releaseOK102
windows-oldrelOK106
wasm-releaseOK116

Exports:aenetamnetasnetmsaenetmsaenet.fnmsaenet.fpmsaenet.maemsaenet.msemsaenet.nzvmsaenet.nzv.allmsaenet.rmsemsaenet.rmslemsaenet.sim.binomialmsaenet.sim.coxmsaenet.sim.gaussianmsaenet.sim.poissonmsaenet.tpmsamnetmsasnet

Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixmvtnormncvregRcppRcppEigenshapesurvival

A Quick Introduction to msaenet

Nan Xiao <https://nanx.me>

Rendered frommsaenet.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2024-05-10
Started: 2016-09-20