Aknouche, Abdelhakim and Bentarzi, Wissam and Demouche, Nacer (2017): On periodic ergodicity of a general periodic mixed Poisson autoregression.
Preview |
PDF
MPRA_paper_79650.pdf Download (154kB) | Preview |
Abstract
We propose a general class of non-linear mixed Poisson autoregressions whose form and parameters are periodic over time. Under a periodic contraction condition on the forms of the conditional mean, we show the existence of a unique nonanticipative solution to the model, which is strictly periodically stationary, periodically ergodic and periodically weakly dependent having in the pure Poisson case finite higher-order moments. Applications to some well-known integer-valued time series models are considered.
Item Type: | MPRA Paper |
---|---|
Original Title: | On periodic ergodicity of a general periodic mixed Poisson autoregression |
English Title: | On periodic ergodicity of a general periodic mixed Poisson autoregression |
Language: | English |
Keywords: | Periodic mixed Poisson autoregression, periodic INGARCH models, non-linear INGARCH models, weak dependence, strict periodic stationarity, periodic ergodicity, periodic contraction condition. |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C19 - Other C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C62 - Existence and Stability Conditions of Equilibrium |
Item ID: | 79650 |
Depositing User: | Prof. Abdelhakim Aknouche |
Date Deposited: | 13 Jun 2017 06:21 |
Last Modified: | 01 Oct 2019 18:48 |
References: | Ahmad, A.; Francq, C. (2016). Poisson qmle of count time series models. Journal of Time Series Analysis, 37, 291-314. Aknouche, A., Al-Eid, E.; Demouche, N. (2017). Generalized quasi-maximum likelihood inference for periodic conditionally heteroskedastic models. Statistical Inference for Stochastic Processes, forthcoming. DOI: 10.1007/s11203-017-9160-x. Bentarzi, M.; Bentarzi, W. (2017). Periodic integer-valued GARCH(1,1) model. Communications in Statistics -Simulation and Computation, 47, 1167-1188. Christou, V.; Fokianos, K. (2014). Quasi-likelihood inference for negative binomial time series models. Journal of Time Series Analysis, 35, 55-78. Christou, V.; Fokianos, K. (2015). Estimation and testing linearity for non-linear mixed Poisson autoregressions. Electronic Journal of Statistics, 9, 1357-1377. Davis, R.A., Holan, S.H., Lund, R.; Ravishanker, N. (2016). Handbook of discrete-valued time series. Chapman and Hall. Davis, R.A.; Liu, H. (2016). Theory and inference for a class of observation-driven models with application to time series of counts. Statistica Sinica, 26, 1673-1707. Dedecker, J.; Prieur, C. (2004). Coupling for τ-dependent sequences and applications. Journal of Theoretical Probability, 17, 861-885. Douc, R., Doukhan, P.; Moulines, E. (2013). Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator. Stochastic Processes and their Applications, 123, 2620-2647. Doukhan, P., Fokianos, K.; Tjøstheim, D. (2012). On weak dependence conditions for Poisson autoregressions. Statistics and Probability Letters, 82, 942-948. Doukhan, P.; Wintenberger, O. (2008). Weakly dependent chains with infinite memory. Stochastic Processes and their Applications, 118, 1997-2013. Ferland, R., Latour, A.; Oraichi, D. (2006). Integer-valued GARCH process. Journal of Time Series Analysis, 27, 923-942. Fokianos, K., Rahbek, A.; Tjøstheim, D. (2009). Poisson autoregression. Journal of the American Statistical Association, 140, 1430-1439. Fokianos, K.; Tjøstheim, D. (2011). Log-linear Poisson autoregression. Journal of Multivariate Analysis, 102, 563-578. Franke, J. (2010). Weak dependence of functional INGARCH processes. Technical report, University of Kaiserslautern. Grunwald, G.K., Hyndman, R.J., Tedesco, L; Tweedie, R.L. (2000). Non-Gaussian conditional linear AR(1) models. Australian & New Zealand Journal of Statistics, 42, 479-495. Neumann, M.H. (2011). Absolute regularity and ergodicity of Poisson count processes. Bernoulli, 17, 1268-1284. Rydberg, T.H.; Shephard, N. (2000). BIN models for trade-by-trade data. Modelling the number of trades in a fixed interval of time. In World Conference Econometric Society, 2000, Seattle. Contributed Paper 0740. Wang, C., Liu, H., Yao, J.-F., Davis, R.A.; Li, W.K. (2014). Self-excited threshold Poisson autoregression. Journal of the American Statistical Association, 109, 777-787. Zhu, F. (2011). A negative binomial integer-valued GARCH model. Journal of Time Series Analysis, 32, 54-67. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/79650 |