Robust Estimation of Parameters in Nonlinear Ordinary Differential Equation Models

作     者：QIU Yanping HU Tao LIANG Baosheng CUI Hengjian 

作者机构：School of Mathematical SciencesBeijing Normal UniversityBeijing 100875China School of Mathematical Sciences and BCMIISCapital Normal UniversityBeijing 100048China 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2016年第29卷第1期

页      面：41-60页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：supported by the Natural Science Foundation of China under Grant Nos.11201317,11028103,11231010,11471223 Doctoral Fund of Ministry of Education of China under Grant No.20111108120002 the Beijing Municipal Education Commission Foundation under Grant No.KM201210028005 the Key project of Beijing Municipal Educational Commission 

主　　题：Asymptotic properties Huber parameter ordinary differential equation robust estimation 

摘      要：Ordinary differential equation(ODE) models are widely used to model dynamic processes in many scientific *** estimation is usually a challenging problem,especially in nonlinear ODE *** most popular method,nonlinear least square estimation,is shown to be strongly sensitive to *** this paper,robust estimation of parameters using M-estimators is proposed,and their asymptotic properties are obtained under some regular *** authors also provide a method to adjust Huber parameter automatically according to the ***,a method is presented to estimate the initial values of parameters and state *** efficiency and robustness are well balanced in Huber estimators,which is demonstrated via numerical simulations and chlorides data analysis.