Abstract
In this paper, the problem of estimating the covariance matrix in general linear mixed models is considered. A new class of estimators is proposed. It is shown that this new estimator dominates the analysis of variance estimate under two squared loss functions. Finally, some simulation results to compare the performance of the proposed estimator with that of the analysis of variance estimate are reported. The simulation results indicate that this new estimator provides a substantial improvement in risk under most situations.
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This research is supported by National Natural Science Foundation of China, Tian Yuan Special Foundation under Grant No. 10926059 and Zhejiang Provincial Natural Science Foundation of China under Grant No. Y6100053.
This paper was recommended for publication by Editor Guohua ZOU.
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Ye, R., Ma, T. & Wang, S. Improved anovae of the covariance matrix in general linear mixed models. J Syst Sci Complex 24, 176–185 (2011). https://doi.org/10.1007/s11424-011-8309-8
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DOI: https://doi.org/10.1007/s11424-011-8309-8