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International Journal of Nonlinear Analysis and Applications، جلد ۱۲، شماره ۲، صفحات ۱۹۹۷-۲۰۰۷
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عنوان انگلیسی Time series analysis of the number of Covid-19 deaths in Iraq
چکیده انگلیسی مقاله In this paper, the time series data for the number of deaths from Coronavirus (COVID-19) patients in Iraq were analyzed for the period from 4/3/2020 to 18/2/2021. ARCH, GARCH, and TGARCH models were applied due to the changing volatility of the series leading to a heteroscedastic variance. The appropriate models for the series were diagnosed and the best model was chosen and used for forecasting by the exponential smoothing methods. The comparison criterion used was the Root Mean Squared Error and the Sum of Squared Residuals. The most appropriate model for modeling and forecasting the Coronavirus deaths series in Iraq was diagnosed as TGARCH (1,1). Finally, the method of Holt-winter-additive forecasting was the best method among the
کلیدواژه‌های انگلیسی مقاله COVID-19, time series, Volatility, heteroscedastic variance, Garch, ARCH, TGARCH
نویسندگان مقاله Sarab D. Shukur |
Department of Mathematics, College of Science, University of Baghdad, Iraq

Tasnim Hasan Kadhim |
Department of Mathematics, College of Science, University of Baghdad, Iraq

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_5331_ad1b945fc7d1acc2c6cfeb8486e3d21e.pdf
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