Package: LqG 0.1.0

LqG: Robust Group Variable Screening Based on Maximum Lq-Likelihood Estimation

Produces a group screening procedure that is based on maximum Lq-likelihood estimation, to simultaneously account for the group structure and data contamination in variable screening. The methods are described in Li, Y., Li, R., Qin, Y., Lin, C., & Yang, Y. (2021) Robust Group Variable Screening Based on Maximum Lq-likelihood Estimation. Statistics in Medicine, 40:6818-6834.<doi:10.1002/sim.9212>.

Authors:Mingcong Wu, Yang Li, Rong Li

LqG_0.1.0.tar.gz
LqG_0.1.0.zip(r-4.7)LqG_0.1.0.zip(r-4.6)LqG_0.1.0.zip(r-4.5)
LqG_0.1.0.tgz(r-4.6-any)LqG_0.1.0.tgz(r-4.5-any)
LqG_0.1.0.tar.gz(r-4.7-any)LqG_0.1.0.tar.gz(r-4.6-any)
LqG_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
LqG/json (API)

# Install 'LqG' in R:
install.packages('LqG', repos = c('https://lirong95.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 195 downloads 3 exports 0 dependencies

Last updated from:8cc52d9d4e. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE91
source / vignettesOK138
linux-release-x86_64NOTE93
macos-release-arm64NOTE145
macos-oldrel-arm64NOTE117
windows-develNOTE58
windows-releaseNOTE64
windows-oldrelNOTE51
wasm-releaseOK86

Exports:grsc.marg.MLqEgrsc.MLqEMLqE.est

Dependencies: