sparsenet (1.3)

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Fit Sparse Linear Regression Models via Nonconvex Optimization.

http://www.stanford.edu/~hastie/Papers/Sparsenet/jasa_MFH_final.pdf
http://cran.r-project.org/web/packages/sparsenet

Efficient procedure for fitting regularization paths between L1 and L0, using the MC+ penalty of Zhang, C.H. (2010). Implements the methodology described in Mazumder, Friedman and Hastie (2011) . Sparsenet computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.

Maintainer: Trevor Hastie
Author(s): Rahul Mazumder [aut, cre], Trevor Hastie [aut, cre], Jerome Friedman [aut, cre]

License: GPL-2

Uses: glmnet, Matrix, shape

Released 8 days ago.


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