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'.

Getting started

Package details

AuthorJerome Friedman, Xiaotong Suo and Robert Tibshirani
MaintainerXiaotong Suo <xiaotong@stanford.edu>
Package repositoryView on CRAN
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orderedLasso documentation built on May 2, 2019, 6:36 a.m.