Article ID Journal Published Year Pages File Type
417218 Computational Statistics & Data Analysis 2008 10 Pages PDF
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.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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