Estimation and testing linearity for non-linear mixed Poisson autoregressions

Christou, V. and Fokianos, K. (2015) Estimation and testing linearity for non-linear mixed Poisson autoregressions. Electronic Journal of Statistics, 9 (1). pp. 1357-1377. ISSN 1935-7524

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Abstract

Non-linear mixed Poisson autoregressive models are studied for the analysis of count time series. Given a correct mean specification of the model, we discuss quasi maximum likelihood estimation based on Poisson log-likelihood function. A score testing procedure for checking linearity of the mean process is developed. We consider the cases of identifiable and non identifiable parameters under the null hypothesis. When the parameters are identifiable then a chi-square approximation to the distribution of the score test is obtained. In the case of non identifiable parameters, a supremum score type test statistic is employed for checking linearity of the mean process. The methodology is applied to simulated and real data.

Item Type:
Journal Article
Journal or Publication Title:
Electronic Journal of Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? statistics and probability ??
ID Code:
127755
Deposited By:
Deposited On:
26 Sep 2018 07:44
Refereed?:
Yes
Published?:
Published
Last Modified:
15 Jul 2024 18:22