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混合系数线性模型的几乎无偏岭估计
ALMOST UNBIASED RIDGE ESTIMATOR FOR A MIXED-EFFECT COEFFICIENT LINEAR MODEL
【摘要】 本文研究了连续测量数据情况下的混合系数线性模型的参数估计问题.利用岭估计方法得到了该模型的几乎无偏岭估计,并证明了在均方误差意义下,几乎无偏岭估计优于岭估计.最后讨论了有偏参数的选取问题.
【Abstract】 In the paper, we consider a mixed-effect coefficient linear model with the repeatedly measured data. Using the ridge method, the almost unbiased ridge estimator (AURE) of the model are given. It is proved that the AURE excels the ridge estimator (RE) under a mean square error (MSE), and the optimal value for the biased parameter is established by minimum MSE.
【关键词】 混合系数线性模型;
几乎无偏岭估计;
岭估计;
均方误差;
【Key words】 mixed-effect coefficient linear model; almost unbiased ridge estimator; ridge estimator; mean square error;
【Key words】 mixed-effect coefficient linear model; almost unbiased ridge estimator; ridge estimator; mean square error;
【基金】 教育部科学技术研究重点项目(209078);湖北省教育厅科学技术研究资助项目(D20092207)
- 【文献出处】 数学杂志 ,Journal of Mathematics , 编辑部邮箱 ,2013年02期
- 【分类号】O212.1
- 【被引频次】17
- 【下载频次】160