Title of article :
Sieve maximum likelihood estimation for doubly semiparametric zero-inflated Poisson models
Author/Authors :
He، نويسنده , , Xuming and Xue، نويسنده , , Hongqi and Shi، نويسنده , , Ning-Zhong، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2010
Pages :
13
From page :
2026
To page :
2038
Abstract :
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.
Keywords :
Asymptotic efficiency , partly linear model , Sieve maximum likelihood estimator , Zero-inflated Poisson model
Journal title :
Journal of Multivariate Analysis
Serial Year :
2010
Journal title :
Journal of Multivariate Analysis
Record number :
1565482
Link To Document :
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