Forecasting the Trends of Covid-19 and Causal Impact of Vaccines Using Bayesian Structural time Series and ARIMA
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DOI: 10.1007/s40745-022-00418-4
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- Harvey,Andrew C., 1991.
"Forecasting, Structural Time Series Models and the Kalman Filter,"
Cambridge Books,
Cambridge University Press, number 9780521405737, October.
- Harvey,Andrew C., 1990. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521321969, October.
- Obryan Poyser, 2019. "Exploring the dynamics of Bitcoin’s price: a Bayesian structural time series approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 29-60, March.
- Sanjay Kumar, 2020. "Monitoring Novel Corona Virus (COVID-19) Infections in India by Cluster Analysis," Annals of Data Science, Springer, vol. 7(3), pages 417-425, September.
- Feroze, Navid, 2020. "Forecasting the patterns of COVID-19 and causal impacts of lockdown in top five affected countries using Bayesian Structural Time Series Models," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
- James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
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Keywords
BSTS; CausalImpact; MCMC; ARIMA;All these keywords.
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