Package: sparsenet 1.6

sparsenet: Fit Sparse Linear Regression Models via Nonconvex Optimization

Efficient procedure for fitting regularization paths between L1 and L0, using the MC+ penalty of Zhang, C.H. (2010)<doi:10.1214/09-AOS729>. Implements the methodology described in Mazumder, Friedman and Hastie (2011) <doi:10.1198/jasa.2011.tm09738>. Sparsenet computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.

Authors:Rahul Mazumder [aut, cre], Trevor Hastie [aut, cre], Jerome Friedman [aut, cre]

sparsenet_1.6.tar.gz
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sparsenet.pdf |sparsenet.html✨
sparsenet/json (API)

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

14 exports 2 stars 1.00 score 3 dependencies 1 dependents 1 mentions 20 scripts 214 downloads

Last updated 7 months agofrom:7a6f3c32fc. Checks:OK: 9. Indexed: yes.

Exports:coef.cv.sparsenetcoef.sparsenetcv.sparsenetgendatagetcoef_listplot.cv.sparsenetplot.sparsenetpredict.cv.sparsenetpredict.sparsenetprint.cv.sparsenetprint.sparsenetsparsenetsparsepredictsummary.sparsenet

Dependencies:latticeMatrixshape