Determining the background driving process of the Ornstein-Uhlenbeck model

IF 0.8 4区 数学 Q2 MATHEMATICS
M. Mariani, Peter K. Asante, William Kubin, Osei K. Tweneboah, Maria P. Beccar-Varela
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引用次数: 0

Abstract

In this work, we determine appropriate background driving processes for the 3-component superposed Ornstein-Uhlenbeck model by analyzing the fractal characteristics of the data sets using the rescaled range analysis (R/S), the detrended fluctuation analysis (DFA), and the diffusion entropy analysis (DEA). See also https://ejde.math.txstate.edu/special/02/m1/abstr.html
确定Ornstein-Uhlenbeck模型的背景驱动过程
在这项工作中,我们通过使用重标度范围分析(R/S)、去趋势波动分析(DFA)和扩散熵分析(DEA)分析数据集的分形特征,确定适合三分量叠加Ornstein-Uhlenbeck模型的背景驱动过程。参见https://ejde.math.txstate.edu/special/02/m1/abstr.html
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Electronic Journal of Differential Equations
Electronic Journal of Differential Equations MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
1.50
自引率
14.30%
发文量
1
审稿时长
3 months
期刊介绍: All topics on differential equations and their applications (ODEs, PDEs, integral equations, delay equations, functional differential equations, etc.) will be considered for publication in Electronic Journal of Differential Equations.
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