Performance of the restricted almost unbiased type principal components estimators in linear regression model
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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.
KeywordsMulticollinearity Principle components regression Equality Restrictions Almost unbiased ridge estimator Almost unbiased Liu estimator
Mathematics Subject Classification62J07 62J05
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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