Estimation of Multivariate Sample Selection Models via a Parameter-Expanded Monte Carlo EM Algorithm

• 作者: Phillip Li
• 来源期刊: 统计学期刊(英文)
• 学科: 医学
• 关键词: MULTIVARIATE Sample Selection HECKMAN Correction INCIDENTAL TRUNCATION EXPECTATION MAXIMIZATION
• 年，卷（期）: 2014,（10）
• 页码范围: 851-856
• 页数: 6页
• 分类号: R73

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.