sparsenet: Fit sparse linear regression models via nonconvex optimization

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Sparsenet uses the MC+ penalty of Zhang. It computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.

Author
Rahul Mazumder, Trevor Hastie, Jerome Friedman
Date of publication
2014-03-12 07:25:03
Maintainer
Trevor Hastie <hastie@stanford.edu>
License
GPL-2
Version
1.2
URLs

View on CRAN

Man pages

cv.sparsenet
Cross-validation for sparsenet
gendata
Generate data for testing sparse model selection
plot.cv.sparsenet
plot the cross-validation curves produced by cv.sparsenet
plot.sparsenet
plot coefficients from a "sparsenet" object
predict.cv.sparsenet
make predictions from a "cv.sparsenet" object.
predict.sparsenet
make predictions from a "sparsenet" object.
sparsenet
Fit a linear model regularized by the nonconvex MC+ sparsity...
sparsenet-internal
Internal sparsenet functions
sparsenet-package
Fit a linear model regularized by the nonconvex MC+ sparsity...

Files in this package

sparsenet
sparsenet/configure.in
sparsenet/src
sparsenet/src/Makevars.in
sparsenet/src/sparsenet.f90
sparsenet/src/Makevars.win
sparsenet/NAMESPACE
sparsenet/R
sparsenet/R/sparsepredict.R
sparsenet/R/gendata.R
sparsenet/R/lambda0.R
sparsenet/R/predict.cv.sparsenet.R
sparsenet/R/onAttach.R
sparsenet/R/argmin.R
sparsenet/R/print.sparsenet.R
sparsenet/R/coef.sparsenet.R
sparsenet/R/summary.sparsenet.R
sparsenet/R/cv.sparsenet.R
sparsenet/R/print.cv.sparsenet.R
sparsenet/R/sparsenet.R
sparsenet/R/predict.sparsenet.R
sparsenet/R/zeromat.R
sparsenet/R/coef.cv.sparsenet.R
sparsenet/R/plot.cv.sparsenet.R
sparsenet/R/plot.sparsenet.R
sparsenet/R/getcoef_list.R
sparsenet/MD5
sparsenet/DESCRIPTION
sparsenet/configure
sparsenet/man
sparsenet/man/predict.sparsenet.Rd
sparsenet/man/cv.sparsenet.Rd
sparsenet/man/gendata.Rd
sparsenet/man/sparsenet.Rd
sparsenet/man/sparsenet-internal.Rd
sparsenet/man/plot.sparsenet.Rd
sparsenet/man/plot.cv.sparsenet.Rd
sparsenet/man/predict.cv.sparsenet.Rd
sparsenet/man/sparsenet-package.Rd
sparsenet/configure.win
sparsenet/cleanup