期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2016
卷号：78
期号：2
页码：269-303
DOI：10.1007/s13171-016-0089-8
语种：English
出版社：Indian Statistical Institute
摘要：This paper considers a semi-parametric model for longitudinal negative binomial counts under the assumption that the repeated count responses follow an ARMA type non-stationary correlation structure. A step-by-step estimation approach is developed which provides consistent estimators for the non-parametric function, the auto-correlation structure and overdispersion parameter involved in the marginal negative binomial model, subsequently yielding a consistent estimator for the main regression parameter. Proofs for the consistency properties of the estimators are given. Also the convergence rates for the estimators of the non-parametric function as well as main parameters of the model are derived.
关键词：Auto-correlations for negative binomial counts ; Kernel based semi-parametric generalized quasi-likelihood estimation ; Moments for correlation estimation ; Non-parametric function ; Quasi-likelihood estimation ; Semi-parametric marginal regression model
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