Model selection by LASSO methods in a change-point model

被引：35
|
作者：
Ciuperca, Gabriela [1 ]
机构：
[1] Univ Lyon 1, Inst Camille Jordan, CNRS, UMR 5208, F-69622 Villeurbanne, France
来源：
STATISTICAL PAPERS | 2014年 / 55卷 / 02期
关键词：
LASSO; Change-points; Selection criterion; Asymptotic behavior; Oracle properties; VARIABLE SELECTION; ADAPTIVE LASSO; MULTIPLE; ASYMPTOTICS; LIKELIHOOD;
D O I：
10.1007/s00362-012-0482-x
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
The paper considers a linear regression model with multiple change-points occurring at unknown times. The LASSO technique is very interesting since it allows simultaneously the parametric estimation, including the change-points estimation, and the automatic variable selection. The asymptotic properties of the LASSO-type (which has as particular case the LASSO estimator) and of the adaptive LASSO estimators are studied. For this last estimator the Oracle properties are proved. In both cases, a model selection criterion is proposed. Numerical examples are provided showing the performances of the adaptive LASSO estimator compared to the least squares estimator.
引用
收藏
页码：349 / 374
页数：26
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