Package: SOIL
Type: Package
Title: Sparsity Oriented Importance Learning
Version: 1.1
Date: 2017-09-20
Author: Chenglong Ye <yexxx323@umn.edu>, Yi Yang <yi.yang6@mcgill.ca>,
        Yuhong Yang <yyang@stat.umn.edu>
Maintainer: Yi Yang <yi.yang6@mcgill.ca>
Imports: stats, glmnet, ncvreg, MASS, parallel, brglm2
Description: Sparsity Oriented Importance Learning (SOIL) provides a
        new variable importance measure for high dimensional linear
        regression and logistic regression from a sparse penalization
        perspective, by taking into account the variable selection
        uncertainty via the use of a sensible model weighting. The
        package is an implementation of Ye, C., Yang, Y., and Yang, Y.
        (2017+).
License: GPL-2
URL: https://github.com/emeryyi/SOIL
Packaged: 2026-06-19 11:17:57 UTC; root
NeedsCompilation: no
Repository: https://archer-yang-lab.r-universe.dev
Date/Publication: 2017-10-18 01:51:55 UTC
RemoteUrl: https://github.com/archer-yang-lab/soil
RemoteRef: HEAD
RemoteSha: 9013bb4f3becf16910042d49f357683ae923daaf