orderedLasso: Ordered Lasso and Time-lag Sparse Regression

Ordered lasso and time-lag sparse regression. Ordered Lasso fits a linear model and imposes an order constraint on the coefficients. It writes the coefficients as positive and negative parts, and requires positive parts and negative parts are non-increasing and positive. Time-Lag Lasso generalizes the ordered Lasso to a general data matrix with multiple predictors. For more details, see Suo, X.,Tibshirani, R., (2014) 'An Ordered Lasso and Sparse Time-lagged Regression'.

Version: 1.7
Depends: R (≥ 3.0.0), Matrix
Imports: Iso, quadprog, ggplot2, reshape2
Published: 2014-11-27
Author: Jerome Friedman, Xiaotong Suo and Robert Tibshirani
Maintainer: Xiaotong Suo <xiaotong at stanford.edu>
License: GPL-2
NeedsCompilation: yes
In views: TimeSeries
CRAN checks: orderedLasso results

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Reference manual: orderedLasso.pdf
Package source: orderedLasso_1.7.tar.gz
Windows binaries: r-devel: orderedLasso_1.7.zip, r-release: orderedLasso_1.7.zip, r-oldrel: orderedLasso_1.7.zip
OS X Mavericks binaries: r-release: orderedLasso_1.7.tgz, r-oldrel: orderedLasso_1.7.tgz

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