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:Lingfei Wang <[email protected]>

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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'))

Peer review:

Bug tracker:https://github.com/lingfeiwang/lassopv/issues

On CRAN:

feature-selectionlassolinear-regressionp-valuevariable-selection

2.00 score 1 stars 5 scripts 145 downloads 1 mentions 1 exports 1 dependencies

Last updated 2 years agofrom:0d828c0715. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 23 2024
R-4.5-winOKOct 23 2024
R-4.5-linuxOKOct 23 2024
R-4.4-winOKOct 23 2024
R-4.4-macOKOct 23 2024
R-4.3-winOKOct 23 2024
R-4.3-macOKOct 23 2024

Exports:lassopv

Dependencies:lars