Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models

JOURNAL OF MULTIVARIATE ANALYSIS

卷:101

Article

He, Xuming ; Xue, Hongqi ; Shi, Ning-Zhong

关键词: Asymptotic efficiency;    Partly linear model;    Sieve maximum likelihood estimator;    Zero-inflated Poisson model;   

DOI  :  10.1016/j.jmva.2010.05.003

来源: Elsevier

【 摘 要 】

For nonnegative measurements such as income or sick days, zero counts often have special status. Furthermore, the incidence of zero counts is often greater than expected for the Poisson model. This article considers a doubly semiparametric zero-inflated Poisson model to fit data of this type, which assumes two partially linear link functions in both the mean of the Poisson component and the probability of zero. We study a sieve maximum likelihood estimator for both the regression parameters and the nonparametric functions. We show, under routine conditions, that the estimators are strongly consistent. Moreover, the parameter estimators are asymptotically normal and first order efficient, while the nonparametric components achieve the optimal convergence rates. Simulation studies suggest that the extra flexibility inherent from the doubly semiparametric model is gained with little loss in statistical efficiency. We also illustrate our approach with a dataset from a public health study. (c) 2010 Elsevier Inc. All rights reserved.

【 授权许可】

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