Estimation and testing linearity for non-linear mixed poisson autoregressions
Date
2015ISSN
1935-7524Source
Electronic Journal of StatisticsVolume
9Pages
1357-1377Google Scholar check
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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. © 2015, Institute of Mathematical Statistics. All rights reserved.