Abstract
This paper considers the performance of the unbiased ridge estimator (Crouse et al. Commun Stat Theory Methods 24:2341–2354, 1995) over the ordinary least squares estimator of the regression parameter using the Pitman’s closeness criterion. Then, we introduce a new variance components estimator based on the unbiased ridge estimator. Furthermore we show that the new variance components estimator has smaller mean squared error than the variance components estimator based on the ordinary least squares estimator. A simulation study has been presented to compare the performance of the estimators, and a numerical example has been proposed to explain the performance of the estimators.
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Acknowledgments
The author is highly obliged to the editors and the reviewers for the comments and suggestions which improved the paper in its present form. This work was supported by the National Natural Science Foundation of China (Grant No: 11171361), the Natural Science Foundation of Yongchuan (Grant No: Ycstc2014nc8001) and the Ph.D. Programs Foundation of Ministry of Education of China (Grant No: 20110191110033).
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Wu, J., Yang, H. More on the unbiased ridge regression estimation. Stat Papers 57, 31–42 (2016). https://doi.org/10.1007/s00362-014-0637-z
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DOI: https://doi.org/10.1007/s00362-014-0637-z