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SOIL: Sparsity Oriented Importance Learning
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+).
Getting started
Browse package contents
Package details |
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| 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> |
| License | GPL-2 |
| Version | 1.1 |
| URL | https://github.com/emeryyi/SOIL |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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