文章基本信息

标题：Estimation of Multivariate Sample Selection Models via a Parameter-Expanded Monte Carlo EM Algorithm
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作者：Phillip Li
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2014
卷号：04
期号：10
页码：851-856
DOI：10.4236/ojs.2014.410080
语种：English
出版社：Scientific Research Publishing
摘要：This paper develops a parameter-expanded Monte Carlo EM (PX-MCEM) algorithm to perform maximum likelihood estimation in a multivariate sample selection model. In contrast to the current methods of estimation, the proposed algorithm does not directly depend on the observed-data likelihood, the evaluation of which requires intractable multivariate integrations over normal densities. Moreover, the algorithm is simple to implement and involves only quantities that are easy to simulate or have closed form expressions.
关键词：Multivariate Sample Selection; Heckman Correction; Incidental Truncation; Expectation Maximization