匹配(统计)
计算机科学
差速器(机械装置)
系统动力学
数学优化
估计理论
功能(生物学)
微分方程
应用数学
反向
数学
特征(语言学)
估计
算法
人工智能
统计
数学分析
工程类
哲学
航空航天工程
经济
生物
进化生物学
管理
语言学
几何学
作者
Jianbin Tan,Guoyu Zhang,Xueqin Wang,Hui Huang,Fang Yao
标识
DOI:10.1093/jrsssb/qkae031
摘要
Parameters of differential equations are essential to characterize intrinsic behaviors of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex systems with general-order differential operators, such as motion dynamics. This article presents Green's matching, a computationally tractable and statistically efficient two-step method, which only needs to approximate trajectories in dynamic systems but not their derivatives due to the inverse of differential operators by Green's function. This yields a statistically optimal guarantee for parameter estimation in general-order equations, a feature not shared by existing methods, and provides an efficient framework for broad statistical inferences in complex dynamic systems.
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