%0 Journal Article
%T Modelling covid-19 data using double geometric stochastic process
%J International Journal of Nonlinear Analysis and Applications
%I Semnan University
%Z 2008-6822
%A Jasim, Omar R.
%A Nauef, Qutaiba N.
%D 2021
%\ 11/01/2021
%V 12
%N 2
%P 1243-1254
%! Modelling covid-19 data using double geometric stochastic process
%K double geometric stochastic process
%K geometric stochastic process
%K Parameter estimation
%K chicken swarm optimization algorithm
%K multiple monotone trends
%K root mean square criteria
%R 10.22075/ijnaa.2021.5224
%X 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.
%U https://ijnaa.semnan.ac.ir/article_5224_02e9a1bfe58a51b45b35967b11edc6fc.pdf