Package: msgps 1.3.5

Kei Hirose

msgps: Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net

Computes the degrees of freedom of the lasso, elastic net, generalized elastic net and adaptive lasso based on the generalized path seeking algorithm. The optimal model can be selected by model selection criteria including Mallows' Cp, bias-corrected AIC (AICc), generalized cross validation (GCV) and BIC.

Authors:Kei Hirose

msgps_1.3.5.tar.gz
msgps_1.3.5.zip(r-4.7-x86_64)msgps_1.3.5.zip(r-4.7-arm64)msgps_1.3.5.zip(r-4.6-x86_64)msgps_1.3.5.zip(r-4.6-arm64)
msgps_1.3.5.tar.gz(r-4.7-arm64)msgps_1.3.5.tar.gz(r-4.7-x86_64)msgps_1.3.5.tar.gz(r-4.6-arm64)msgps_1.3.5.tar.gz(r-4.6-x86_64)
msgps_1.3.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
msgps/json (API)

# Install 'msgps' in R:
install.packages('msgps', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

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

openblas

2.18 score 5 packages 4 scripts 411 downloads 1 mentions 13 exports 0 dependencies

Last updated from:5f96b42596. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK76
linux-devel-x86_64OK100
source / vignettesOK139
linux-release-arm64OK65
linux-release-x86_64OK90
windows-devel-arm64OK210
windows-devel-x86_64OK93
windows-release-arm64OK208
windows-release-x86_64OK62
wasm-releaseOK70

Exports:aicc.dfgpsbic.dfgpscoef.dfgpscoef.msgpscoefmat.dfgpscp.dfgpsdfgpsgcv.dfgpsmsgpsplot.msgpspredict.msgpsprint.msgpssummary.msgps

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
msgps (Degrees of Freedom of Elastic Net, Adaptive Lasso and Generalized Elastic Net)aicc.dfgps bic.dfgps cp.dfgps dfgps gcv.dfgps msgps print.msgps
plot the solution path from a "msgps" object.plot.df plot.msgps
make predictions from a "msgps" object.coef.dfgps coef.msgps coef.step.dfgps coefmat.dfgps predict.msgps
A summary of "msgps" object..summary.msgps