A note on adaptive group lasso

Authors:
Hansheng Wang;Chenlei Leng
Affiliations:
Peking University, China and National University of Singapore, Singapore;Peking University, China and National University of Singapore, Singapore
Venue:
Computational Statistics & Data Analysis
Year:
2008

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Abstract

Group lasso is a natural extension of lasso and selects variables in a grouped manner. However, group lasso suffers from estimation inefficiency and selection inconsistency. To remedy these problems, we propose the adaptive group lasso method. We show theoretically that the new method is able to identify the true model consistently, and the resulting estimator can be as efficient as oracle. Numerical studies confirmed our theoretical findings.