SOIL (1.1)

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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+).

Maintainer: Yi Yang
Author(s): Chenglong Ye <>, Yi Yang <>, Yuhong Yang <>

License: GPL-2

Uses: brglm2, glmnet, MASS, ncvreg

Released over 2 years ago.

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