cosso: Fit Regularized Nonparametric Regression Models Using COSSO Penalty

COSSO is a new regularization method that automatically estimates and selects important function components by a soft-thresholding penalty in the context of smoothing spline ANOVA models. Implemented models include mean regression, quantile regression, logistic regression and the Cox regression models.

Version: 2.1-1
Depends: quadprog, Rglpk, parallel, glmnet
Published: 2013-03-11
Author: Hao Helen Zhang and Chen-Yen Lin
Maintainer: Chen-Yen Lin <clin5 at ncsu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www4.stat.ncsu.edu/~hzhang/cosso.html
NeedsCompilation: no
CRAN checks: cosso results

Downloads:

Reference manual: cosso.pdf
Package source: cosso_2.1-1.tar.gz
Windows binaries: r-devel: cosso_2.1-1.zip, r-release: cosso_2.1-1.zip, r-oldrel: cosso_2.1-1.zip
OS X Snow Leopard binaries: r-release: cosso_2.1-1.tgz, r-oldrel: cosso_2.1-1.tgz
OS X Mavericks binaries: r-release: cosso_2.1-1.tgz
Old sources: cosso archive