Summary: This article was published in the above mentioned Springer issue.
The material, including all portions thereof, is protected by copyright;
all rights are held exclusively by Springer Science + Business Media.
The material is for personal use only;
commercial use is not permitted.
Unauthorized reproduction, transfer and/or use
may be a violation of criminal as well as civil law.
ISSN 1133-0686, Volume 19, Number 2
Test (2010) 19: 257258
Comments on: 1-penalization for mixture regression
Received: 21 March 2010 / Accepted: 23 May 2010 / Published online: 30 June 2010
© Sociedad de Estadística e Investigación Operativa 2010
I congratulate the authors for a very interesting and timely contribution to an impor-
tant problem: regularizing and recovering a sparse set of covariates in a finite mixture
of regressions model with an extremely large number of predictors. The authors work
primary with a regularized maximum likelihood procedure in a well chosen parame-