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Estimation Methods for a Flexible INAR(1) COM-Poisson Time Series Model


Time series of counts occur in many real-life situations where they exhibit various forms of dispersion. To facilitate the modeling of such time series, this paper introduces a flexible first-order integer-valued non-stationary autoregressive (INAR(1)) process where the innovation terms follow a Conway-Maxwell Poisson distribution (COM-Poisson). To estimate the unknown parameters in this model, different estimation approaches based on likelihood and quasi-likelihood formulations are considered. From simulation experiments and a real-life data application, the Generalized Quasi-Likelihood (GQL) approach yields estimates with lower bias than the other estimation approaches.

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Theodore the Studite’s Christology Against Its Logical Background

: Teubner, 1987. 49. Васюков, В. Л. Логика Галена: наследие Аристотеля или научная инновация? [Vasyukov, V. L. Galen’s Logic: Aristotelian Heritage or Scientific Innovation?], История медицины , vol. 2, 2015, pp. 5-16. 50. Желтов, М. “Догматик” [Zheltov, Mikhail. “Dogmatikon”] In Православная энциклопедия , vol. 15, Москва: ЦНТ «Православная энциклопедия», 2007, pp. 532-533. 51. Христов, И. Битие и съществуване в дискусията за метода между св.Григорий Палама и Варлаам [Christov, I. Being and Existence in the Discussion on the Method between St. Gregory

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Selected Ethical Issues in Artificial Intelligence, Autonomous System Development and Large Data Set Processing

and patients, European Surgery , vol. 44, 2012, pp. 155–163. 24. Industry 4.0. Australian Government, Department of Industry, Innovation and Science , Available at: , accessed: 2017-03-01. 25. Japanese scholars issue ethical guidelines on AI, NHK World (2017), Available at: , accessed: 2017-03-01. 26. Jurevicius, O. Google mission statement 2013, Strategic Management Insight , 2013. Available at: https

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