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随机幂律逻辑模型的累积量逼近。

Approximations of Cumulants of the Stochastic Power Law Logistic Model.

机构信息

Department of Mathematics, The Royal Institute of Technology, 100 44, Stockholm, Sweden.

出版信息

Bull Math Biol. 2020 Jan 22;82(2):19. doi: 10.1007/s11538-019-00687-w.

Abstract

Asymptotic approximations of the first three cumulants of the quasi-stationary distribution of the stochastic power law logistic model are derived. The results are based on a system of ODEs for the first three cumulants. We deviate from the classical moment closure approach by determining approximations without closing the system of equations. The approximations are explicit in the model's parameters, conditions for validity of the approximations are given, magnitudes of approximation errors are given, and spurious solutions are easily detected and eliminated. In these ways, we provide improvements on previous results for this model.

摘要

推导出随机幂律逻辑模型的拟平稳分布的前三个累积量的渐近逼近。该结果基于前三个累积量的 ODE 系统。我们通过不封闭方程组来确定逼近而偏离经典矩闭合方法。逼近在模型参数中是显式的,给出了逼近的有效性条件,给出了逼近误差的大小,并容易检测和消除伪解。通过这些方法,我们对该模型的先前结果进行了改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6976556/45b230aa51fa/11538_2019_687_Fig1_HTML.jpg

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