L1 penalty and shrinkage estimation in partially linear models with random coefficient autoregressive errors

Author:

Fallahpour Saber1,Ahmed S. Ejaz1,Doksum Kjell A.2

Affiliation:

1. Department of Mathematics and Statistics; University of Windsor; Windsor; ON; Canada

2. Department of Statistics; University of Wisconsin-Madison; Madison; WI; U.S.A.

Publisher

Wiley

Subject

Management Science and Operations Research,General Business, Management and Accounting,Modeling and Simulation

Reference39 articles.

1. Variable selection via nonconcave penalized likelihood and its oracle properties;Fan;Journal of the American Statistical Association,2001

2. Regression shrinkage and selection via the lasso;Tibshirani;Journal of the Royal Statistical Society: Series B,1996

3. The adaptive lasso and its oracle properties;Zou;Journal of the American Statistical Association,2006

4. Least angle and ℓ1 penalized regression: A review;Hesterberg;Statistics surveys,2008

5. Shrinkage, pretest and absolute penalty estimators in partially linear models;Ahmed;Australian & New Zealand Journal of Statistics,2007

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