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Robust Estimation of Parameters in Nonlinear Ordinary Differential Equation Models 被引量:1

Robust Estimation of Parameters in Nonlinear Ordinary Differential Equation Models
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摘要 Ordinary differential equation(ODE) models are widely used to model dynamic processes in many scientific fields.Parameter estimation is usually a challenging problem,especially in nonlinear ODE models.The most popular method,nonlinear least square estimation,is shown to be strongly sensitive to outliers.In this paper,robust estimation of parameters using M-estimators is proposed,and their asymptotic properties are obtained under some regular conditions.The authors also provide a method to adjust Huber parameter automatically according to the observations.Moreover,a method is presented to estimate the initial values of parameters and state variables.The efficiency and robustness are well balanced in Huber estimators,which is demonstrated via numerical simulations and chlorides data analysis.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2016年第1期41-60,共20页 系统科学与复杂性学报(英文版)
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
关键词 Asymptotic properties Huber parameter ordinary differential equation robust estimation 系统科学 系统学 系统工程 理论
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  • 1Mattheij R and Molenaar J, Ordinary Differential Equations in Theory and Practice, SIAM, Philadelphia, 2002. 被引量:1
  • 2Xue H, Miao H, and Wu H, Sieve estimation of constant and time-varying coefficients in nonlinear ordinary differential equation models by considering both numerical error and measurement error, Annals of Statistics, 2010, 38(4): 2351-2387. 被引量:1
  • 3Wu H, Xue, H, and Kumar A, Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical re- search, Biometrics, 2012, 68(2): 344-352. 被引量:1
  • 4Hemker P W, Numerical methods for differential equations in system simulation and in parameter estimation, Analysis and Simulation of Biochemical Systems, Eds. by Hemker H C and Hess B, Amsterdam, North Holland, 1972, 59-80. 被引量:1
  • 5Stortelder W J H, Parameter estimation in dynamic systems, Mathematics and Computers in Simulation, 1996, 42: 135-142. 被引量:1
  • 6Gugushvili S and Klaassen C A J, √n-eonsistent parameter estimation for systems of ordinary differential equations: Bypassing numerical integration via smoothing, Bernoulli, 2002, 18:1061- 1098. 被引量:1
  • 7Cao J, Wang L, and Xu J, Robust estimation for ordinary differential equation models, Biomet- rics, 2011, 67(4): 1305-1313. 被引量:1
  • 8Ramsay J O, Hooker G, Campbell D, and Cao J, Parameter estimation for differential equations: A generalized smoothing approach (with discussion), Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2007, 69: 741-796. 被引量:1
  • 9Cui H J, Asymptotic normality of M-estimates in the EV model, Systems Science and Mathe- matical Sciences, 1997, 10(3): 225-236. 被引量:1
  • 10Huber P J and Ronchetti E M, Robust Statistics, 2nd Edtion, Wiley, 2009. 被引量:1

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