It is well known that the likelihood inferences in dynamic mixed models for count data is extremely complicated. In this paper, we, first, develop a generalized method of moments (GMM) approach for the estimation of the parameters of such models. We then consider an alternative generalized quasi-likelihood (GQL) approach. The relative efficiency of the GQL approach to the GMM approach is examined by comparing the asymptotic variances of the GQL estimates of the parameters to the corresponding asymptotic variances of the GMM estimates. (C) 2009 Elsevier B.V. All rights reserved.
机构:
Cent China Normal Univ, Dept Stat, Wuhan, Peoples R China
Univ Missouri, Dept Stat, Columbia, MO 65211 USACent China Normal Univ, Dept Stat, Wuhan, Peoples R China
Zhao, Hui
Virkler, Kate
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机构:
Univ Missouri, Dept Stat, Columbia, MO 65211 USACent China Normal Univ, Dept Stat, Wuhan, Peoples R China
Virkler, Kate
Sun, Jianguo
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机构:
Univ Missouri, Dept Stat, Columbia, MO 65211 USACent China Normal Univ, Dept Stat, Wuhan, Peoples R China