Count Time Series: A Methodological Review
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DOI: 10.1080/01621459.2021.1904957
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Cited by:
- Sunhe, Flor, 2021. "A Bayesian Spatio-temporal model for predicting passengers' occupancy at Beijing Metro," DES - Working Papers. Statistics and Econometrics. WS 33787, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
- Yuhyeong Jang & Raanju R. Sundararajan & Wagner Barreto-Souza & Elizabeth Wheaton-Paramo, 2024. "Determining economic factors for sex trafficking in the United States using count time series regression," Empirical Economics, Springer, vol. 67(1), pages 337-354, July.
- Huaping Chen & Qi Li & Fukang Zhu, 2023. "A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 805-826, October.
- Jiajie Kong & Robert Lund, 2023. "Seasonal count time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 93-124, January.
- Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
- Zhonghao Su & Fukang Zhu & Shuangzhe Liu, 2024. "Local influence analysis in the softplus INGARCH model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(3), pages 951-985, September.
- Christian Francq & Jean‐Michel Zakoïan, 2023. "Optimal estimating function for weak location‐scale dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(5-6), pages 533-555, September.
- Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
- Sun, He, 2023. "Deep Learning and Bayesian Calibration Approach to Hourly Passenger Occupancy Prediction in Beijing Metro: A Study Exploiting Cellular Data and Metro Conditions," DES - Working Papers. Statistics and Econometrics. WS 38783, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Stefano Cabras, 2021. "A Bayesian-Deep Learning Model for Estimating COVID-19 Evolution in Spain," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
- Karmakar, Sayar & Gupta, Rangan & Cepni, Oguzhan & Rognone, Lavinia, 2023.
"Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model,"
Resources Policy, Elsevier, vol. 82(C).
- Sayar Karmakar & Rangan Gupta & Oguzhan Cepni & Lavinia Rognone, 2022. "Climate Risks and Predictability of the Trading Volume of Gold: Evidence from an INGARCH Model," Working Papers 202241, University of Pretoria, Department of Economics.
- Huaping Chen & Fukang Zhu & Xiufang Liu, 2022. "A New Bivariate INAR(1) Model with Time-Dependent Innovation Vectors," Stats, MDPI, vol. 5(3), pages 1-22, August.
- Rostami-Tabar, Bahman & Disney, Stephen M., 2023. "On the order-up-to policy with intermittent integer demand and logically consistent forecasts," International Journal of Production Economics, Elsevier, vol. 257(C).
- Younghoon Kim & Marie-Christine Duker & Zachary F. Fisher & Vladas Pipiras, 2023. "Latent Gaussian dynamic factor modeling and forecasting for multivariate count time series," Papers 2307.10454, arXiv.org, revised Jul 2024.
- Mirko Armillotta & Konstantinos Fokianos, 2024. "Count network autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(4), pages 584-612, July.
- Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2024. "Volatility models versus intensity models: analogy and differences," MPRA Paper 122528, University Library of Munich, Germany.
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