Square-root lasso: pivotal recovery of sparse signals via conic programming

We propose a pivotal method for estimating high-dimensional sparse linear regression models, where the overall number of regressors p is large, possibly much larger than n, but only s regressors are significant. The method is a modification of the lasso, called the square-root lasso. The method is p...

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Bibliographic Details
Main Authors: Bellini, A., Chernozhukov, Victor V., Wang, Lie
Other Authors: Massachusetts Institute of Technology. Department of Economics
Format: Article
Language:en_US
Published: Oxford University Press 2012
Online Access:http://hdl.handle.net/1721.1/71663
https://orcid.org/0000-0003-3582-8898
https://orcid.org/0000-0002-3250-6714