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缺失数据下多元正态模型Monte Carlo EM算法
引用本文:王继霞,刘次华.缺失数据下多元正态模型Monte Carlo EM算法[J].郑州大学学报(理学版),2011(3).
作者姓名:王继霞  刘次华
作者单位:河南师范大学数学与信息科学学院;华中科技大学数学与统计学院;
基金项目:国家自然科学基金资助项目,编号10671057; 河南省教育厅软科学研究计划,编号2010B110013
摘    要:研究含有缺失数据的多元正态模型参数的极大似然估计问题,利用Monte Carlo EM算法求得多元正态模型参数的迭代解,并证明了此迭代解收敛到最优解,且其收敛速度是二阶的.

关 键 词:多元正态模型  缺失数据  EM算法  Monte  Carlo  EM算法  Newton-Raphson算法  

Monte Carlo EM Algorithm for Multivariate Normal Distribution under Missing Data
WANG Ji-xia,LIU Ci-hua.Monte Carlo EM Algorithm for Multivariate Normal Distribution under Missing Data[J].Journal of Zhengzhou University:Natural Science Edition,2011(3).
Authors:WANG Ji-xia  LIU Ci-hua
Institution:WANG Ji-xia1,LIU Ci-hua2(1.College of Mathematics and Information Science,Henan Normal University,Xinxiang 453007,China,2.Department of Math,Huazhong University of Science and Technology,Wuhan 430074,China)
Abstract:Maximum likelihood estimations of the parameters of multivariate normal distribution models under missing data were studied.The iterative solution of the parameters of multivariate normal distribution models were obtained through the Monte Carlo EM algorithm and this solution converge to the optimum solution were proved and the convergence rate of this solution was secondary.
Keywords:multivariate normal distribution  missing data  EM algorithm  Monte Carlo EM algorithm  Newton-Raphson algorithm  
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