Improving the EM algorithm for mixtures

作     者：Karlis, D Xekalaki, E 

作者机构：Athens Univ Econ & Business Dept Stat Athens 10434 Greece 

出 版 物：《STATISTICS AND COMPUTING》 (统计学与计算)

年 卷 期：1999年第9卷第4期

页      面：303-307页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：EM algorithm k-finite mixtures normal mixtures Poisson mixtures semiparametric maximum likelihood 

摘      要：One of the estimating equations of the Maximum Likelihood Estimation method, for finite mixtures of the one parameter exponential family, is the first moment equation. This can help considerably in reducing the labor and the cost of calculating the Maximum Likelihood estimates. In this paper it is shown that the EM algorithm can be substantially improved by using this result when applied for mixture models. A short discussion about other methods proposed for the calculation of the Maximum Likelihood estimates are also reported showing that the above findings can help in this direction too.