Package: LINselect 1.1.5
Benjamin Auder
LINselect: Selection of Linear Estimators
Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators, following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) <doi:10.1214/13-AIHP539>. In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso, elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
Authors:
LINselect_1.1.5.tar.gz
LINselect_1.1.5.tar.gz(r-4.5-noble)LINselect_1.1.5.tar.gz(r-4.4-noble)
LINselect_1.1.5.tgz(r-4.4-emscripten)LINselect_1.1.5.tgz(r-4.3-emscripten)
LINselect.pdf |LINselect.html✨
LINselect/json (API)
| # Install 'LINselect' in R: |
| install.packages('LINselect', 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 1 years agofrom:6d46db803b. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 02 2024 |
| R-4.5-linux | NOTE | Dec 02 2024 |
Exports:penaltysimulDatatuneLassoVARselect
Dependencies:elasticnetgtoolslarsMASSmvtnormplsrandomForest
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| penalty | penalty |
| simulData | simulData |
| tuneLasso | tuneLasso |
| VARselect | VARselect |