lassopv: Nonparametric P-Value Estimation for Predictors in Lasso

Estimate 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 that (first) become active earlier tend to be more significant. Null distribution for each predictor is computed analytically under approximation, which aims at efficiency and accuracy for small p-values.

Version: 0.1.3
Depends: R (≥ 2.10)
Imports: lars, stats
Published: 2017-02-08
Author: Lingfei Wang
Maintainer: Lingfei Wang <Lingfei.Wang.github at>
License: GPL-3
Copyright: Copyright 2016, 2017 Lingfei Wang
NeedsCompilation: no
CRAN checks: lassopv results


Reference manual: lassopv.pdf
Package source: lassopv_0.1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: lassopv_0.1.3.tgz
OS X Mavericks binaries: r-oldrel: lassopv_0.1.3.tgz
Old sources: lassopv archive


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