A note on adaptive group lasso
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.
Year of publication: |
2008
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Authors: | Wang, Hansheng ; Leng, Chenlei |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 52.2008, 12, p. 5277-5286
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Publisher: |
Elsevier |
Saved in:
Online Resource
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