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Generalized partially linear single-index model for zero-inflated count data

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Indexed by:期刊论文

Date of Publication:2015-02-28

Journal:STATISTICS IN MEDICINE

Included Journals:SCIE、PubMed、Scopus

Volume:34

Issue:5

Page Number:876-886

ISSN No.:0277-6715

Key Words:asymptotic normality; B-spline; generalized partially linear model; single-index model; zero-inflated count data

Abstract:Count data often arise in biomedical studies, while there could be a special feature with excessive zeros in the observed counts. The zero-inflated Poisson model provides a natural approach to accounting for the excessive zero counts. In the semiparametric framework, we propose a generalized partially linear single-index model for the mean of the Poisson component, the probability of zero, or both. We develop the estimation and inference procedure via a profile maximum likelihood method. Under some mild conditions, we establish the asymptotic properties of the profile likelihood estimators. The finite sample performance of the proposed method is demonstrated by simulation studies, and the new model is illustrated with a medical care dataset. Copyright (C) 2014 John Wiley & Sons, Ltd.

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