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'.


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install.packages("orderedLasso")

1.7 by Xiaotong Suo, 3 years ago


Browse source code at https://github.com/cran/orderedLasso


Authors: Jerome Friedman, Xiaotong Suo and Robert Tibshirani


Documentation:   PDF Manual  


Task views: Time Series Analysis


GPL-2 license


Imports Iso, quadprog, ggplot2, reshape2

Depends on Matrix


See at CRAN