APPROXIMATE MAXIMUM-LIKELIHOOD-ESTIMATION IN THE PRESENCE OF EXTRA-POISSON VARIATION

作     者：JOHAADIEN, H GOUTIS, C 

作者机构：UNIV LONDON UNIV COLL DEPT STAT SCI LONDON WC1E 6BT ENGLAND 

出 版 物：《COMMUNICATIONS IN STATISTICS-THEORY AND METHODS》 (统计学通讯：理论与方法)

年 卷 期：1995年第24卷第6期

页      面：1625-1636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）] 

主　　题：BAYESIAN APPROXIMATIONS EM ALGORITHM LOG-LINEAR MODELS OVERDISPERSION 

摘      要：A two-stage hierarchical model for analysis of discrete data with extra-Poisson variation is examined. The model consists of a Poisson distribution with a mixing lognormal distribution for the mean. A method of approximate maximum likelihood estimation of the parameters is proposed. The method uses the EM algorithm and approximations to facilitate its implementation are derived. Approximate standard errors of the estimates are. provided and a numerical example is used to illustrate the method.