Abstract
This study proposes a class of nonlinear hysteretic integer-valued GARCH models in order to describe the occurrence of weekly dengue hemorrhagic fever cases via three meteorological covariates: precipitation, average temperature, and relative humidity. The proposed model adopts the hysteretic three-regime switching mechanism with a buffer zone that are able to explain various characteristics. This allows for having consecutive zeros in the lower regime and large counts to appear up in the upper regime. These nonlinear hysteretic integer-valued GARCH models include Poisson, negative binomial, and log-linked forms. We utilize adaptive Markov chain Monte Carlo simulations for making inferences and prediction and employ two Bayesian criteria for model comparisons and the relative root mean squared prediction error for evaluation. Simulation and analytic results emphasize that the hysteretic negative binomial integer-valued GARCH model is superior to other models and successfully offers an alternative nonlinear integer-valued GARCH model to better describe larger values of counts.
Similar content being viewed by others
References
Ando T (2011) Predictive Bayesian model selection. Am J Math Manag Sci 31:13–38
Chen CWS, Khamthong K (2019) Bayesian modelling of nonlinear negative binomial integer-valued GARCHX models. Stat Model. https://doi.org/10.1177/1471082X19845541
Chen CWS, Lee S (2016) Generalized Poisson autoregressive models for time series of counts. Comput Stat Data Anal 99:51–67
Chen CWS, Lee S (2017) Bayesian causality test for integer-valued time series models with applications to climate and crime data. J R Stat Soc Ser C 66:797–814
Chen CWS, So MKP (2006) On a threshold heteroscedastic model. Int J Forecast 22:73–89
Chen CWS, Truong BC (2016) On double hysteretic heteroskedastic model. J Stat Comput Simul 86:2684–2705
Chen CWS, Gerlach R, Lin AMH (2010) Fallingand explosive, dormant and rising markets via multiple regime financial time series models. Appl Stoch Model Bus 26:28–49
Chen CWS, Khamthong K, Lee S (2019) Markov switching integer-valued GARCH models for dengue counts. J R Stat Soc Ser C 68:963–983
Chen CWS, So MKP, Gerlach RH (2005) Asymmetric response and interaction of US and local markets news in financial markets. Appl Stoch Models Bus Ind 21:273–288
Chen CWS, So MKP, Liu FC (2011) A review of threshold time series models in finance. Stat Interface 4:167–182
Chen CWS, So MKP, Li J, Sriboonchitta S (2016) Autoregressive conditional negative binomial model applied to over-dispersed time series of counts. Stat Methodol 31:73–90
Ferland R, Latour A, Oraichi D (2006) Integer-valued GARCH processes. J Time Ser Anal 27:923–942
Fokianos K, Tjøstheim D (2011) Log-linear Poisson autoregression. J Multivariate Anal 102:563–578
Gelman A, Roberts GO, Gilks WR (1996) Efficient metropolis jumping rules. In: Bernardo JM, Berger JO, Dawid AP, Smith AFM (eds) Bayesian statistics, vol 5. Oxford University Press, Oxford, pp 599–607
Hii YL, Zhu H, Ng N, Ng LC, Rocklöv J (2012) Forecast of dengue incidence using temperature and rainfall. PLOS Negl Trop Dis 6:e1908
Hyndman R, Koehler AB (2006) Another look at measures of forecast accuracy. Int J Forecast 22:679–688
Jazi MA, Jones G, Lai C (2012) First-order integer-valued AR processes with zero inflated poisson innovations. J Time Ser Anal 33:954–96
Jung RC, Kukuk M, Liesenfeld R (2006) Time series of count data: modelling and estimation and diagnostics. Comput Stat Data Anal 51:2350–2364
Lambert D (1992) Zero-inflated Poisson regression with an application to defects in manufacturing. Technometrics 34:1–14
Lee S, Lee Y, Chen CWS (2016) Parameter change test for zero-inflated generalized Poisson autoregressive models. Statistics 50:540–557
Li G, Guan B, Li WK, Yu PLH (2015) Hysteretic autoregressive time series models. Biometrika 102:717–723
Spiegelhalter D, Best NG, Carlin BP, Van der Linde A (2002) Bayesian measures of model complexity and fit (with discussion). J R Stat Soc Ser B 64:583–616
Tong H (1978) On a threshold model. In: Chen CH (ed) Pattern recognition and signal processing. Sijthoff & Noordhoff, Amsterdam, pp 575–586
Tong H (1983) Threshold models in nonlinear time series analysis. Lecture notes in statistics. Springer, New York
Truong BC, Chen CWS, Sriboonchitta S (2017) Hysteretic Poisson INGARCH model for integer-valued time series. Stat Model 17:401–422
Wang C, Liu H, Yao JF, Davis RA, Li WK (2014) Self-excited threshold Poisson autoregression. J Am Stat Assoc 109:777–787
Wasserman L (2000) Asymptotic inference for mixture models using data-dependent priors. J R Stat Soc B 62:159–80
Xu H-Y, Xie M, Goh TN, Fu X (2012) A model for integer-valued time series with conditional overdispersion. Comput Stat Data Anal 56:4229–4242
Zhu F (2011) A negative binomial integer-valued GARCH model. J Time Ser Anal 32:54–67
Zhu F (2012) Zero-inflated Poisson and negative binomial integer-valued GARCH models. J Stat Plan Inference 42:826–839
Zhu K, Li WK, Yu PLH (2017) Buffered autoregressive models with conditional heteroscedasticity: an application to exchange rates. J Bus Econ Stat 35:528–542
Acknowledgements
We thank the Editor, the Associate Editor, and anonymous referees for their valuable time and careful comments, which have helped improve this paper. Cathy W.S. Chen’s research is funded by the Ministry of Science and Technology, Taiwan (MOST107-2118-M-035-005-MY2). 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. 2018R1A2A2A05019433).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Chen, C.W.S., Lee, S. & Khamthong, K. Bayesian inference of nonlinear hysteretic integer-valued GARCH models for disease counts. Comput Stat 36, 261–281 (2021). https://doi.org/10.1007/s00180-020-01018-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00180-020-01018-7