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'.


Reference manual

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1.7.1 by Xiaotong Suo, a year 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