文章基本信息

标题：Quasi-Monte Carlo Estimation in Generalized Linear Mixed Model with Correlated Random Effects
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作者：Yin Chen ; Yu Fei ; Jianxin Pan 等
期刊名称：Open Access Library Journal
印刷版ISSN：2333-9705
电子版ISSN：2333-9721
出版年度：2015
卷号：2
期号：10
页码：1-16
DOI：10.4236/oalib.1102002
语种：English
出版社：Scientific Research Pub
摘要：Parameter estimation by maximizing the marginal likelihood function in generalized linear mixed models (GLMMs) is highly challenging because it may involve analytically intractable high-dimensional integrals. In this paper, we propose to use Quasi-Monte Carlo (QMC) approximation through implementing Newton-Raphson algorithm to address the estimation issue in GLMMs. The random effects release to be correlated and joint mean-covariance modelling is considered. We demonstrate the usefulness of the proposed QMC-based method in approximating high-dimensional integrals and estimating the parameters in GLMMs through simulation studies. For illustration, the proposed method is used to analyze the infamous salamander mating binary data, of which the marginalized likelihood involves six 20-dimensional integrals that are analytically intractable, showing that it works well in practices.
关键词：Generalized Linear Mixed ModelsCorrelated Random EffectsQuasi-Monte CarloMean-Covariance ModellingHigh-Dimensional IntegralsNewton-Raphson Method