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Statistical Papers

, Volume 60, Issue 1, pp 19–34 | Cite as

Performance of the restricted almost unbiased type principal components estimators in linear regression model

  • Yalian LiEmail author
  • Hu Yang
Regular Article
  • 116 Downloads

Abstract

In this paper, two new classes of estimators called the restricted almost unbiased ridge-type principal components estimator and the restricted almost unbiased Liu-type principal components estimator are introduced. For the two cases when the restrictions are true and not true, necessary and sufficient conditions for the superiority of the proposed estimators are derived and compared, respectively. Finally, A Monte Carlo simulation study is given to illustrate the performance of the proposed estimators.

Keywords

Multicollinearity Principle components regression Equality Restrictions Almost unbiased ridge estimator Almost unbiased Liu estimator 

Mathematics Subject Classification

62J07 62J05 

Notes

Acknowledgments

We are grateful to the editor and the anonymous reviewers for the constructive comments and suggestions which have improved the quality of this paper. This work was supported in part by the National Natural Science Foundation of China (Grant No. 11671059) and the Fundamental Research Funds for the Central Universities (Grant No. 106112015CDJXY100004).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Statistics and Actuarial ScienceChongqing UniversityChongqingChina

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