EconPapers    
Economics at your fingertips  
 

A note on adaptive group lasso

Hansheng Wang () and Chenlei Leng

Computational Statistics & Data Analysis, 2008, vol. 52, issue 12, 5277-5286

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.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (60)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00258-2
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:52:y:2008:i:12:p:5277-5286

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:csdana:v:52:y:2008:i:12:p:5277-5286