Abstract
We analyze the eigenstructure of count-data Markov chains. Our main focus is on so-called CLAR(1) models, which are characterized by having a linear conditional mean, and also on the case of a finite range, where the second largest eigenvalue determines the speed of convergence of the forecasting distributions. We derive a lower bound for the second largest eigenvalue, which often (but not always) even equals this eigenvalue. This becomes clear by deriving the complete set of eigenvalues for several specific cases of CLAR(1) models.
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References
Al-Osh MA, Alzaid AA (1987) First-order integer-valued autoregressive (INAR(1)) process. J Time Ser Anal 8(3):261–275
Ferland R, Latour A, Oraichi D (2006) Integer-valued GARCH processes. J Time Ser Anal 27(6):923–942
Grunwald G, Hyndman RJ, Tedesco L, Tweedie RL (2000) Non-Gaussian conditional linear AR(1) models. Aus New Z J Stat 42(4):479–495
Heinen A (2003) Modelling time series count data: an autoregressive conditional Poisson model CORE Discussion Paper 2003/62. University of Louvain, Belgium
Johnson NL, Kemp AW, Kotz S (2005) Univariate discrete distributions, 3rd edn. Wiley, Hoboken
McKenzie E (1985) Some simple models for discrete variate time series. Water Resour Bull 21(4):645–650
Rydberg TH, Shephard N (2000) BIN models for trade-by-trade data. Modelling the number of trades in a fixed interval of time. Econometric Society World Congress 2000, Contributed Papers No 0740, Econometric Society
Seneta E (1983) Non-negative matrices and Markov chains, 2nd edn. Springer Verlag, New York
Steutel F W, van Harn K (1979) Discrete analogues of self-decomposability and stability. Ann Probab 7(5):893–899
Weiß CH (2009) Monitoring correlated processes with binomial marginals. J Appl Stat 36(4):399–414
Weiß CH (2010) The INARCH(1) model for overdispersed time series of counts. Commun Stat Simul Comput 39(6):1269–1291
Weiß CH, Kim H-Y (2014) Diagnosing and modeling extra-binomial variation for time-dependent counts. Appl Stoch Model Bus Ind 30(5):588–608
Weiß CH, Pollett PK (2014) Binomial autoregressive processes with density dependent thinning. J Time Ser Anal 35(2):115–132
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The author thanks the referee for useful comments on an earlier draft of this article.
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Weiß, C.H. On Eigenvalues of the Transition Matrix of Some Count-Data Markov Chains. Methodol Comput Appl Probab 19, 997–1007 (2017). https://doi.org/10.1007/s11009-017-9560-9
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DOI: https://doi.org/10.1007/s11009-017-9560-9