Numerical discretization-based kernel type estimation methods for ordinary differential equation models

Verfasser / Beitragende:
[Tao Hu, Yan Qiu, Heng Cui, Li Chen]
Ort, Verlag, Jahr:
2015
Enthalten in:
Acta Mathematica Sinica, English Series, 31/8(2015-08-01), 1233-1254
Format:
Artikel (online)
ID: 605461937
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024 7 0 |a 10.1007/s10114-015-4256-y  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s10114-015-4256-y 
245 0 0 |a Numerical discretization-based kernel type estimation methods for ordinary differential equation models  |h [Elektronische Daten]  |c [Tao Hu, Yan Qiu, Heng Cui, Li Chen] 
520 3 |a We consider the problem of parameter estimation in both linear and nonlinear ordinary differential equation (ODE) models. Nonlinear ODE models are widely used in applications. But their analytic solutions are usually not available. Thus regular methods usually depend on repetitive use of numerical solutions which bring huge computational cost. We proposed a new two-stage approach which includes a smoothing method (kernel smoothing or local polynomial fitting) in the first stage, and a numerical discretization method (Eulers discretization method, the trapezoidal discretization method, or the Runge-Kutta discretization method) in the second stage. Through numerical simulations, we find the proposed method gains a proper balance between estimation accuracy and computational cost. Asymptotic properties are also presented, which show the consistency and asymptotic normality of estimators under some mild conditions. The proposed method is compared to existing methods in term of accuracy and computational cost. The simulation results show that the estimators with local linear smoothing in the first stage and trapezoidal discretization in the second stage have the lowest average relative errors. We apply the proposed method to HIV dynamics data to illustrate the practicability of the estimator. 
540 |a Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Chinese Mathematical Society and Springer-Verlag Berlin Heidelberg, 2015 
690 7 |a Nonparametric regression  |2 nationallicence 
690 7 |a kernel smoothing  |2 nationallicence 
690 7 |a local polynomial fitting  |2 nationallicence 
690 7 |a parametric identification  |2 nationallicence 
690 7 |a ordinary differential equation  |2 nationallicence 
690 7 |a numerical discretization  |2 nationallicence 
690 7 |a two-stage method  |2 nationallicence 
700 1 |a Hu  |D Tao  |u School of Mathematical Sciences & BCMIIS, Capital Normal University, 100048, Beijing, P. R. China  |4 aut 
700 1 |a Qiu  |D Yan  |u School of Mathematical Sciences, Beijing Normal University, 100875, Beijing, P. R. China  |4 aut 
700 1 |a Cui  |D Heng  |u School of Mathematical Sciences & BCMIIS, Capital Normal University, 100048, Beijing, P. R. China  |4 aut 
700 1 |a Chen  |D Li  |u Fujian College of Water Conservancy and Eletric Power, 366000, Fujian, P. R. China  |4 aut 
773 0 |t Acta Mathematica Sinica, English Series  |d Institute of Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society  |g 31/8(2015-08-01), 1233-1254  |x 1439-8516  |q 31:8<1233  |1 2015  |2 31  |o 10114 
856 4 0 |u https://doi.org/10.1007/s10114-015-4256-y  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s10114-015-4256-y  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Hu  |D Tao  |u School of Mathematical Sciences & BCMIIS, Capital Normal University, 100048, Beijing, P. R. China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Qiu  |D Yan  |u School of Mathematical Sciences, Beijing Normal University, 100875, Beijing, P. R. China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Cui  |D Heng  |u School of Mathematical Sciences & BCMIIS, Capital Normal University, 100048, Beijing, P. R. China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Chen  |D Li  |u Fujian College of Water Conservancy and Eletric Power, 366000, Fujian, P. R. China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Acta Mathematica Sinica, English Series  |d Institute of Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society  |g 31/8(2015-08-01), 1233-1254  |x 1439-8516  |q 31:8<1233  |1 2015  |2 31  |o 10114