Package: sparsenet 1.7
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:
sparsenet_1.7.tar.gz
sparsenet_1.7.tar.gz(r-4.5-noble)sparsenet_1.7.tar.gz(r-4.4-noble)
sparsenet_1.7.tgz(r-4.4-emscripten)sparsenet_1.7.tgz(r-4.3-emscripten)
sparsenet.pdf |sparsenet.html✨
sparsenet/json (API)
# Install 'sparsenet' in R: |
install.packages('sparsenet', repos = 'https://cloud.r-project.org') |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 months agofrom:ea4cba4da1. Checks:3 OK. Indexed: no.
Target | Result | Latest binary |
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Doc / Vignettes | OK | Mar 25 2025 |
R-4.5-linux-x86_64 | OK | Mar 25 2025 |
R-4.4-linux-x86_64 | OK | Mar 25 2025 |
Exports:coef.cv.sparsenetcoef.sparsenetcv.sparsenetgendatagetcoef_listplot.cv.sparsenetplot.sparsenetpredict.cv.sparsenetpredict.sparsenetprint.cv.sparsenetprint.sparsenetsparsenetsparsepredictsummary.sparsenet
Citation
To cite sparsenet in publications use:
Mazumder R, Friedman J, Hastie T (2011). “SparseNet: Coordinate Descent With Nonconvex Penalties.” Journal of American Statistical Association, 106(495), 1125–1138. https://hastie.su.domains/public/Papers/Sparsenet/Mazumder-SparseNetCoordinateDescent-2011.pdf.
Corresponding BibTeX entry:
@Article{, title = {SparseNet: Coordinate Descent With Nonconvex Penalties}, author = {Rahul Mazumder and Jerome Friedman and Trevor Hastie}, journal = {Journal of American Statistical Association}, year = {2011}, volume = {106}, number = {495}, pages = {1125--1138}, url = {https://hastie.su.domains/public/Papers/Sparsenet/Mazumder-SparseNetCoordinateDescent-2011.pdf}, }
Readme and manuals
Help Manual
Help page | Topics |
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Fit a linear model regularized by the nonconvex MC+ sparsity penalty | sparsenet-package |
Cross-validation for sparsenet | cv.sparsenet |
Generate data for testing sparse model selection | gendata |
plot the cross-validation curves produced by cv.sparsenet | plot.cv.sparsenet |
plot coefficients from a "sparsenet" object | plot.sparsenet |
make predictions from a "cv.sparsenet" object. | coef.cv.sparsenet predict.cv.sparsenet |
make predictions from a "sparsenet" object. | coef.sparsenet predict.sparsenet |
Fit a linear model regularized by the nonconvex MC+ sparsity penalty | sparsenet |