A distribution input-output polynomial approach for estimating parameters in nonlinear models. Application to a chikungunya model

DOI10.1016/j.cam.2017.09.044zbMath1376.92070OpenAlexW2761180486MaRDI QIDQ1678119

Shousheng Zhu, Nathalie Verdière, Lilianne Denis-Vidal

Publication date: 14 November 2017

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2017.09.044

zbMATH Keywords

parameter estimationnonlinear modelsepidemiological modelchikungunya virusdistribution approach

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15)

Uses Software

• Maple
• DIFFALG
• DifferentialAlgebra

Cites Work

• Additive normal forms and integration of differential fractions
• A new method for estimating derivatives based on a distribution approach
• The chikungunya disease: modeling, vector and transmission global dynamics
• Identification of parametric models from experimental data. Transl. from an upd. French version by the authors, with the help of John Norton
• On global identifiability for arbitrary model parametrizations
• Optimal control of chikungunya disease: larvae reduction, treatment and prevention
• An Algorithm for Converting Nonlinear Differential Equations to Integral Equations with an Application to Parameter Estimation from Noisy Data
• Algebraic Identification and Estimation Methods in Feedback Control Systems
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