References
- Ali M, Debes AK, Luquero FJ, et al. (2016). Potential for controlling cholera using a ring vaccination strategy: re-analysis of data from a cluster-randomized clinical trial, PLoS Medicien, 13, e1002120. https://doi.org/10.1371/journal.pmed.1002120
- Al-Osh MA and Alzaid AA (1988). Integer-valued moving average (INMA) process, Statistical Papers, 29, 281-300. https://doi.org/10.1007/BF02924535
- Alzaid AA and Al-Osh M (1990). An integer-valued pth-order autoregressive structure INAR(p) process, Journal of Applied Probability, 27, 314-324. https://doi.org/10.2307/3214650
- Azman AS, Rudolph KE, Cummings DAT, and Lessler J (2013). The incubation period of cholera: a systematic review, The Journal of Infection, 66, 432-438. https://doi.org/10.1016/j.jinf.2012.11.013
- Bartlett A and McCormick WP (2017). Estimation for a first-order bifurcating autoregressive process with heavy-tail innovations, Stochastic Models, 33, 210-228. https://doi.org/10.1080/15326349.2016.1236695
- Cardinal M, Roy R, and Lambert J (1999). On the application of integer-valued time series models for the analysis of disease incidence, Statistics in Medicine, 18, 2025-2039. https://doi.org/10.1002/(SICI)1097-0258(19990815)18:15<2025::AID-SIM163>3.0.CO;2-D
- Ferland R, Latour A, and Oraichi D (2006). Integer-valued GARCH process, Journal of Time Series Analysis, 27, 923-942. https://doi.org/10.1111/j.1467-9892.2006.00496.x
- Fokianos K and Fried R (2010). Interventions in INGARCH processes, Journal of Time Series Analysis, 31, 210-225. https://doi.org/10.1111/j.1467-9892.2010.00657.x
- Freeland R and McCabe B (2004). Analysis of low count time series data by Poisson autoregression, Journal of Time Series Analysis, 25, 701-722. https://doi.org/10.1111/j.1467-9892.2004.01885.x
- McCabe BPM and Martin GM (2005). Bayesian prediction of low count time series, International Journal of Forecasting, 21, 315-330. https://doi.org/10.1016/j.ijforecast.2004.11.001
- McKenzie E (1985). Some simple models for discrete variate time series, Water Resources Bulletin, 21, 635-644. https://doi.org/10.1111/j.1752-1688.1985.tb05378.x
- McKenzie E (1988). Some ARMA models for dependent sequences of Poisson counts, Advances in Applied Probability, 20, 822-835. https://doi.org/10.2307/1427362
- Pavlopoulos H and Karlis D (2008). INAR(1) modeling of overdispersed count series with an environmental application, Environmetrics, 190, 369-393. https://doi.org/10.1002/env.883
- Puig P and Valero J (2006). Count data distributions, Journal of the American Statistical Association, 101, 332-340. https://doi.org/10.1198/016214505000000718
- Quoreshi AMMS (2014). A long-memory integer-valued time series model, INARFIMA, for financial application, Quantitative Finance, 14, 2225-2235. https://doi.org/10.1080/14697688.2012.711911
- Ridout M, Hinde J, and Demetrio CGB (2001). A score test for testing a zero-inflated Poisson regression model against zero-inflated negative binomial alternatives, Biometrics, 57, 219-223. https://doi.org/10.1111/j.0006-341X.2001.00219.x
- Self SG and Liang KY (1987). Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions, Journal of American Statistical Association, 82, 605-610. https://doi.org/10.1080/01621459.1987.10478472
- Thyregod P, Carstensen J, Madsen H, and Arnbjerg-Nielsen K (1999). Integer valued autoregressive models for tipping bucket rainfall measurements, Environmetrics, 10, 395-411. https://doi.org/10.1002/(SICI)1099-095X(199907/08)10:4<395::AID-ENV364>3.0.CO;2-M
- Truong BC, Chen CW, and Sriboonchitta S (2017). Hysteretic Poisson INGARCH model for integer-valued time series, Statistical Modelling, 17, 401-422. https://doi.org/10.1177/1471082X17703855
- Wang C, Liu H, Yao JF, Davis RA, and Li WK (2014). Self-excited threshold Poisson autoregression, Journal of the American Statistical Association, 109, 777-787. https://doi.org/10.1080/01621459.2013.872994
- WeiB CH (2010). The INARCH(1) model for overdispersed time series of counts, Communications in Statistics: Simulation and Computation, 39, 1269-1291. https://doi.org/10.1080/03610918.2010.490317
- Wu S and Chen R (2007). Threshold variable determination and threshold variable driven switching autoregressive models, Statistica Sinica, 17, 241-264.
- Yoon JE and Hwang SY (2015a). Integer-valued GARCH models for count time series: case study, Korean Journal of Applied Statistics, 28, 115-122. https://doi.org/10.5351/KJAS.2015.28.1.115
- Yoon JE and Hwang SY (2015b). Zero-inflated INGARCH using conditional Poisson and negative binomial: data application, Korean Journal of Applied Statistics, 28, 583-592. https://doi.org/10.5351/KJAS.2015.28.3.583
- Zhou J and Basawa IV (2005). Least-squared estimation for bifurcation autoregressive processes, Statistics & Probability Letters, 74, 77-88. https://doi.org/10.1016/j.spl.2005.04.024
- Zhu F (2011). A negative binomial integer-valued GARCH model, Journal of Time Series Analysis, 32, 54-67. https://doi.org/10.1111/j.1467-9892.2010.00684.x
- Zhu F (2012a). Zero-inflated Poisson and negative binomial integer-valued GARCH models, Journal of Statistical Planning and Inference, 142, 826-839. https://doi.org/10.1016/j.jspi.2011.10.002
- Zhu F (2012b). Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued GARCH models, Journal of Mathematical Analysis and Applications, 389, 58-71. https://doi.org/10.1016/j.jmaa.2011.11.042
- Zhu F and Wang D (2010). Diagnostic checking integer-valued ARCH(p) models using conditional residual autocorrelations, Computational Statistics and Data Analysis, 54, 496-508. https://doi.org/10.1016/j.csda.2009.09.019