Package: lassopv 0.2.1
lassopv: Nonparametric P-Value Estimation for Predictors in Lasso
Estimate the p-values for predictors x against target variable y in lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic. This is based on the assumption that predictors (of the same variance) that (first) become active earlier tend to be more significant. Three null distributions are supported: normal and spherical, which are computed separately for each predictor and analytically under approximation, which aims at efficiency and accuracy for small p-values.
Authors:
lassopv_0.2.1.tar.gz
lassopv_0.2.1.zip(r-4.5)lassopv_0.2.1.zip(r-4.4)lassopv_0.2.1.zip(r-4.3)
lassopv_0.2.1.tgz(r-4.4-any)lassopv_0.2.1.tgz(r-4.3-any)
lassopv_0.2.1.tar.gz(r-4.5-noble)lassopv_0.2.1.tar.gz(r-4.4-noble)
lassopv_0.2.1.tgz(r-4.4-emscripten)lassopv_0.2.1.tgz(r-4.3-emscripten)
lassopv.pdf |lassopv.html✨
lassopv/json (API)
# Install 'lassopv' in R: |
install.packages('lassopv', repos = c('https://lingfeiwang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lingfeiwang/lassopv/issues
feature-selectionlassolinear-regressionp-valuevariable-selection
Last updated 2 years agofrom:0d828c0715. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 23 2024 |
R-4.5-win | OK | Oct 23 2024 |
R-4.5-linux | OK | Oct 23 2024 |
R-4.4-win | OK | Oct 23 2024 |
R-4.4-mac | OK | Oct 23 2024 |
R-4.3-win | OK | Oct 23 2024 |
R-4.3-mac | OK | Oct 23 2024 |
Exports:lassopv
Dependencies:lars
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Nonparametric P-Value Estimation for Predictors in Lasso | lassopv-package |
Estimation of Nonparametric P-Value Estimation for Predictors in Lasso | lassopv |