Lima Leonardo Dos Santos
Federal Center for Technological Education of Minas Gerais, Belo Horizonte 30510-000, MG, Brazil.
Entropy (Basel). 2022 May 17;24(5):719. doi: 10.3390/e24050719.
The nonlinear fractional stochastic differential equation approach with Hurst parameter within interval H∈(0,1) to study the time evolution of the number of those infected by the coronavirus in countries where the number of cases is large as Brazil is studied. The rises and falls of novel cases daily or the fluctuations in the official data are treated as a random term in the stochastic differential equation for the fractional Brownian motion. The projection of novel cases in the future is treated as quadratic mean deviation in the official data of novel cases daily since the beginning of the pandemic up to the present. Moreover, the rescaled range analysis (RS) is employed to determine the Hurst index for the time series of novel cases and some statistical tests are performed with the aim to determine the shape of the probability density of novel cases in the future.
研究了在区间(H\in(0,1))内具有赫斯特参数的非线性分数阶随机微分方程方法，以研究像巴西这样病例数众多的国家中感染冠状病毒人数的时间演变。每日新增病例的起伏或官方数据中的波动被视为分数布朗运动随机微分方程中的随机项。自疫情开始至今，未来新增病例的预测被视为每日新增病例官方数据中的二次平均偏差。此外，采用重标极差分析（RS）来确定新增病例时间序列的赫斯特指数，并进行了一些统计测试，旨在确定未来新增病例概率密度的形状。
