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在正态分布情形下,假定均值参数和误差方差服从正态-逆伽马分布先验时,导出了均值参数和误差方差的Bayes估计,利用历史样本构造了它们的参数型经验Bayes估计(PEBE).在均方误差(MSE)准则下,分别获得均值参数和误差方差相对于一致最小方差无偏估计(UMVUE)的优良性.最后,给出一个有关主要结果的注释.

关键词：正态分布均值参数误差方差参数型经验Bayes估计均方误差准则

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A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data

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Science China Mathematics 2013年第11期56卷 2367-2380页

作者： LIU XiaoYu ZHANG WeiPing Department of Statistics and Finance School of ManagementUniversity of Science and Technology of China

Modeling the mean and covariance simultaneously is a common strategy to efciently estimate the mean parameters when applying generalized estimating equation techniques to longitudinal *** this article,using generalized estimation equation techniques,we propose a new kind of regression models for parameterizing covariance *** a novel Cholesky factor,the entries in this decomposition have moving average and log innovation interpretation and are modeled as linear functions of *** resulting estimators for the regression coefcients in both the mean and the covariance are shown to be consistent and asymptotically normally *** studies and a real data analysis show that the proposed approach yields highly efcient estimators for the parameters in the mean,and provides parsimonious estimation for the covariance structure.

关键词：协方差结构移动平均线均值参数纵向数据子模型渐近正态分布回归模型回归系数

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维普期刊数据库

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