Package: msgps 1.3.5
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:
msgps_1.3.5.tar.gz
msgps_1.3.5.tar.gz(r-4.5-noble)msgps_1.3.5.tar.gz(r-4.4-noble)
msgps_1.3.5.tgz(r-4.4-emscripten)msgps_1.3.5.tgz(r-4.3-emscripten)
msgps.pdf |msgps.html✨
msgps/json (API)
# Install 'msgps' in R: |
install.packages('msgps', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:5f96b42596. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 01 2024 |
R-4.5-linux-x86_64 | OK | Dec 01 2024 |
Exports:aicc.dfgpsbic.dfgpscoef.dfgpscoef.msgpscoefmat.dfgpscp.dfgpsdfgpsgcv.dfgpsmsgpsplot.msgpspredict.msgpsprint.msgpssummary.msgps
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
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 |