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A Homotopy Algorithm for the Quantile Regression Lasso and Related Piecewise Linear Problems

Osborne, Michael; Turlach, B

Description

We show that the homotopy algorithm of Osborne, Presnell, and Turlach (2000), which has proved such an effective optimal path following method for implementing Tibshirani's "lasso" for variable selection in least squares estimation problems, can be extended to polyhedral objectives in examples such as the quantile regression lasso. The new algorithm introduces the novel feature that it requires two homotopy sequences involving continuation steps with respect to both the constraint bound and the...[Show more]

CollectionsANU Research Publications
Date published: 2011
Type: Journal article
URI: http://hdl.handle.net/1885/25610
Source: Journal of Computational and Graphical Statistics
DOI: 10.1198/jcgs.2011.09184

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