随机广义逻辑微分方程的统计推断

IF 3.4 2区数学 Q1 MATHEMATICS, APPLIED

Communications in Nonlinear Science and Numerical Simulation Pub Date : 2024-08-07 DOI:10.1016/j.cnsns.2024.108261

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引用次数: 0

摘要

本研究旨在估算随机广义逻辑微分方程中的三个参数。我们假定固有增长率和形状参数是常数但未知的。为了估计这两个参数，我们使用了最大似然法，并确定这两个参数的估计值具有很强的一致性。我们使用二次变化过程来估计扩散参数。为了检验我们的结果，我们评估了完整和不完整两种数据情况，并为三个参数分配了固定值。在数据不完整的情况下，我们采用期望最大化算法。

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Statistical inference for a stochastic generalized logistic differential equation

In this research we aim to estimate three parameters in a stochastic generalized logistic differential equation. We assume the intrinsic growth rate and shape parameters are constant but unknown. To estimate these two parameters, we use the maximum likelihood method and establish that the estimators for these two parameters are strongly consistent. We estimate the diffusion parameter by using the quadratic variation processes. To test our results, we evaluate two data scenarios, complete and incomplete, with fixed values assigned to the three parameters. In the incomplete data scenario, we apply an Expectation Maximization algorithm.

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来源期刊

Communications in Nonlinear Science and Numerical Simulation MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

6.80

自引率

7.70%

发文量

378

审稿时长

78 days

期刊介绍： The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity. The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged. Topics of interest: Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity. No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.