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Modelling covid-19 data using double geometric stochastic process | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، شماره 2، بهمن 2021، صفحه 1243-1254 اصل مقاله (489.08 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5224 | ||
| نویسندگان | ||
| Omar R. Jasim* 1؛ Qutaiba N. Nauef2 | ||
| 1College of Administration and Economics, University of Al-Hamdaniya, Iraq | ||
| 2College of Administration and Economics, University of Bagdad, Iraq | ||
| تاریخ دریافت: 27 فروردین 1400، تاریخ بازنگری: 30 اردیبهشت 1400، تاریخ پذیرش: 07 خرداد 1400 | ||
| چکیده | ||
| Some properties of the geometric stochastic process (GSP) are studied along with those of a related process which we propose to call the Double geometric stochastic process (DGSP), under certain conditions. This process also has the same advantages of tractability as the geometric stochastic process; it exhibits some properties which may make it a useful complement to the multiple Trends geometric stochastic process. Also, it may be fit to observed data as easily as the geometric stochastic process. As a first attempt, the proposed model was applied to model the data and the Coronavirus epidemic in Iraq to reach the best model that represents the data under study. A chicken swarm optimization algorithm is proposed to choose the best model representing the data, in addition to estimating the parameters a, b, \(\mu\), and \(\sigma^{2}\) of the double geometric stochastic process, where \(\mu\) and \(\sigma^{2}\) are the mean and variance of \(X_{1}\), respectively. | ||
| کلیدواژه‌ها | ||
| double geometric stochastic process؛ geometric stochastic process؛ parameter estimation؛ chicken swarm optimization algorithm؛ multiple monotone trends؛ root mean square criteria | ||
| مراجع | ||
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