CRAN/E | lassopv

lassopv

Nonparametric P-Value Estimation for Predictors in Lasso

Installation

About

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.

github.com/lingfeiwang/lassopv
Copyright Copyright 2016-2018 Lingfei Wang

Key Metrics

Version 0.2.0
R ≥ 2.10
Published 2018-02-22 2260 days ago
Needs compilation? no
License GPL-3
CRAN checks lassopv results

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Maintainer

Maintainer

Lingfei Wang

Lingfei.Wang.github@outlook.com

Authors

Lingfei Wang

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

lassopv archive

Depends

R ≥ 2.10

Imports

lars
stats

Reverse Imports

trena