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sparsenet  

Fit Sparse Linear Regression Models via Nonconvex Optimization
View on CRAN: Click here


Download and install sparsenet package within the R console
Install from CRAN:
install.packages("sparsenet")

Install from Github:
library("remotes")
install_github("cran/sparsenet")

Install by package version:
library("remotes")
install_version("sparsenet", "1.6")



Attach the package and use:
library("sparsenet")
Maintained by
Trevor Hastie
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-03-03
Latest Update: 2024-02-05
Description:
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.
How to cite:
Trevor Hastie (2012). sparsenet: Fit Sparse Linear Regression Models via Nonconvex Optimization. R package version 1.6, https://cran.r-project.org/web/packages/sparsenet
Previous versions and publish date:
1.0 (2012-03-03 15:22), 1.1 (2013-01-07 08:25), 1.2 (2014-03-12 07:25), 1.3 (2019-02-11 09:40), 1.4 (2019-11-10 07:40), 1.5 (2023-08-22 06:00)
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