Abstract
In this paper, we consider the problem of testing for a parameter change in bivariate Poisson integer-valued GARCH(1, 1) models, constructed via a trivariate reduction method of independent Poisson variables. We verify that the conditional maximum-likelihood estimator of the model parameters is asymptotically normal. Then, based on these results, we construct CMLE- and residual-based CUSUM tests and derive that their limiting null distributions are a function of independent Brownian bridges. A simulation study and real data analysis are conducted for illustration.
Similar content being viewed by others
References
Alzaid A, Al-Osh M (1990) An integer-valued pth-order autoregressive structure (INAR(p)) process. J Appl Probab 27:314–324
Andreassen CM (2013) Models and inference for correlated count data. Ph.D. thesis, Aarhus University
Csörgö M, Horváth L (1997) Limit theorems in change-point analysis, 18th edn. Wiley, New York
Denuit M, Lambert P (2005) Constraints on concordance measures in bivariate discrete data. J Multi Anal 93(1):40–57
Doukhan P, Kengne W (2015) Inference and testing for structural change in general poisson autoregressive models. Electron J Stat 9(1):1267–1314
Doukhan P, Fokianos K, Tjøstheim D (2012) On weak dependence conditions for Poisson autoregressions. Stat Probab Lett 82(5):942–948
Doukhan P, Fokianos K, Tjøstheim D (2013) Correction to “On weak dependence conditions for Poisson autoregressions”. Stat Probab Lett 83(8):1926–1927
Efron B (1986) Double exponential families and their use in generalized linear regression. J Am Stat Assoc 81(395):709–721
Ferland R, Latour A, Oraichi D (2006) Integer-valued GARCH process. J Time Series Anal 27(6):923–942
Fokianos K, Fried R (2010) Interventions in INGARCH processes. J Time Series Anal 31(3):210–225
Fokianos K, Fried R (2012) Interventions in log-linear Poisson autoregression. Stat Model 12(4):299–322
Fokianos K, Rahbek A, Tjøstheim D (2009) Poisson autoregression. J Am Stat Assoc 104(488):1430–1439
Fokianos K, Gombay E, Hussein A (2014) Retrospective change detection for binary time series models. J Stat Plan Inference 145:102–112
Franke J, Kirch C, Kamgaing JT (2012) Changepoints in times series of counts. J Time Series Anal 33(5):757–770
Heinen A (2003) Modelling time series count data: an autoregressive conditional Poisson model. CORE Discussion Paper 2003/62, Université catholique de Louvain
Heinen A, Rengifo E (2003) Multivariate modeling of time series count data: an AR conditional Poisson model. CORE Discussion Paper 2003/23, Université catholique de Louvain
Heinen A, Rengifo E (2007) Multivariate autoregressive modeling of time series count data using copulas. J Empir Fin 14(4):564–583
Hudecová Š (2013) Structural changes in autoregressive models for binary time series. J Stat Plan Inference 143(10):1744–1752
Jin-Guan D, Yuan L (1991) The integer-valued autoregressive (INAR(p)) model. J Time Series Anal 12(2):129–142
Kang J, Lee S (2009) Parameter change test for random coefficient integer-valued autoregressive processes with application to polio data analysis. J Time Series Anal 30(2):239–258
Kang J, Lee S (2014) Parameter change test for Poisson autoregressive models. Scand J Stat 41(4):1136–1152
Lee S, Ha J, Na O, Na S (2003) The cusum test for parameter change in time series models. Scand J Stat 40(4):781–796
Lee S, Lee Y, Chen CW (2016) Parameter change test for zero-inflated generalized Poisson autoregressive models. Statistics 50(3):1–18
Liu H (2012) Some models for time series of counts. Ph.D. thesis, Columbia University
McKenzie E (1985) Some simple models for discrete variate time series. Water Resour Bull 21(4):645–650
McKenzie E (2003) Ch. 16. Discrete variate time series. Handb Stat 21:573–606
Neumann MH (2011) Absolute regularity and ergodicity of Poisson count processes. Bernoulli 17(4):1268–1284
Pedeli X, Karlis D (2011) A bivariate INAR(1) process with application. Stat Model 11(4):325–349
Pedeli X, Karlis D (2013a) On composite likelihood estimation of a multivariate INAR(1) model. J Time Ser Anal 34(2):206–220
Pedeli X, Karlis D (2013b) On estimation of the bivariate Poisson INAR process. Commun Stat Simul Comput 42(3):514–533
Quoreshi AS (2006) Bivariate time series modeling of financial count data. Commun Stat Theory Methods 35(7):1343–1358
Wang C, Liu H, Yao JF, Davis RA, Li WK (2014) Self-excited threshold Poisson autoregression. J Am Stat Assoc 109(506):777–787
Weiß CH (2008) Thinning operations for modeling time series of counts-a survey. AStA Adv Stat Anal 92(3):319–341
Acknowledgements
We thank the Editor and the two anonymous referees for their careful reading and valuable comments to improve the quality of the paper. Sangyeol Lee’s research is supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning (No. 2015R1A2A2A010003894).
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Lee, Y., Lee, S. & Tjøstheim, D. Asymptotic normality and parameter change test for bivariate Poisson INGARCH models. TEST 27, 52–69 (2018). https://doi.org/10.1007/s11749-016-0510-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11749-016-0510-6