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+).
|Author||Chenglong Ye <firstname.lastname@example.org>, Yi Yang <email@example.com>, Yuhong Yang <firstname.lastname@example.org>|
|Maintainer||Yi Yang <email@example.com>|
|Package repository||View on CRAN|
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