IDEAS: a Matlab Toolbox for Parameter Identificationwith Symbolic Analysis of Uncertainty
IDEAS is a Matlab® toolbox for parameter identification of ordinary differential equation (ODE) models. The parameter estimation is performed in the maximum-likelihood (ML) sense. IDEAS offers several options for the optimal criterion, depending on the hypothesis on the covariance matrix of the measurement errors.
The toolbox is an open source. All the functions generated are accessible and can be utilized in other user-defined routines, and modified if needed.
The main feature of IDEAS is the assessment of the uncertainty of the estimates, based on the symbolic computation of sensitivity functions to evaluate the Fisher information matrix.
The current version v1.1 tackles the estimation problem for the case of synchronous observations.
Requirements: Matlab 7.0 and the Optimization and Symbolic toolboxes
Rafael Muñoz-Tamayo1,2,3, Béatrice Laroche1, Eric Walter3, Marion Leclerc2
(2) UR910 INRA Jouy-en-Josas, Unité d'Ecologie et Physiologie du Système Digestif
(3) UMR8506 Univ Paris Sud-CNRS-SUPÉLEC, Laboratoire des Signaux et Systèmes
References: IDEAS was presented in the 15th IFAC Symposium on System Identification, SYSID 2009. If you publish results using this toolbox, please cite the respective reference:
Muñoz-Tamayo, R., B. Laroche, M. Leclerc and E. Walter. 2009. IDEAS: a parameter identification toolbox with symbolic analysis of uncertainty and its application to biological modelling. In Proc. 15th Symposium on System Identification, Saint-Malo, France. 1271-1276.
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