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Rank theory approach to ridge, LASSO, preliminary test and Stein-type estimators: A comparative study

  • Published:2018-12 Issue:4 Volume:46 Page:690-704
  • ISSN:0319-5724
  • Container-title:Canadian Journal of Statistics
  • language:en
  • Short-container-title:Can J Statistics

Author:

Saleh A. K. Md. Ehsanes1ORCID,Navrátil Radim2,Norouzirad Mina3ORCID

Affiliation:

1. School of Mathematics and Statistics; Carleton University; 1125 Colonel By Drive, Ottawa, ON K1S 5B6 Canada

2. Department of Mathematics and Statistics; Masaryk University; Brno 611 37 Czech Republic

3. Department of Statistics, Faculty of Mathematical Sciences; Shahrood University of Technology, P.O. Box 316-3619995181; Shahrood Iran

Funder

Radim Navratil

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference22 articles.

1. Least squares after model selection in high-dimensional sparse models;Belloni;Bernoulli,2013

2. Heuristics of instability and stabilization in model selection;Breiman;The Annals of Statistics,1996

3. Minimax estimation via wavelet shrinkage;Donoho;The Annals of Statistics,1994

4. Ridge regression and James-Stein estimation: Review and comments;Draper;Technometrics,1979

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

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bibliography;Rank‐Based Methods for Shrinkage and Selection;2022-03-21

2. Penalized regression via the restricted bridge estimator;Soft Computing;2021-04-19

3. Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High‐Dimension Regime;International Statistical Review;2020-04
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