On the asymptotic properties of the group lasso estimator for linear models | Zendy

Yuval Nardi | Zendy; Alessandro Rinaldo | Zendy

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On the asymptotic properties of the group lasso estimator for linear models

Author(s) -

Yuval Nardi,

Alessandro Rinaldo

Publication year - 2008

Publication title -

electronic journal of statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.482

H-Index - 54

ISSN - 1935-7524

DOI - 10.1214/08-ejs200

Subject(s) - mathematics , estimator , lasso (programming language) , consistency (knowledge bases) , covariate , model selection , statistics , strong consistency , least squares function approximation , sample size determination , linear model , group (periodic table) , discrete mathematics , computer science , chemistry , organic chemistry , world wide web

We establish estimation and model selection consistency, pre- diction and estimation boundsand persistencefor the group-lassoestimator and model selectorproposed by Yuan and Lin (2006) for least squares prob- lems when the covariates have a natural grouping structure. We consider the case of a fixed-dimensionalparameter space with increasing sample size and the double asymptotic scenario where the model complexity changes with the sample size.

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