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Estimation of PDE's parameters via mixed effects models. Application to KPP equation.

Paul Vigneaux 1, 2 
2 NUMED - Numerical Medicine
UMPA-ENSL - Unité de Mathématiques Pures et Appliquées, Inria Grenoble - Rhône-Alpes
Abstract : This is joint work with Emmanuel Grenier and Violaine Louvet. Parameter estimation in non linear mixed effects models requires a large number of evaluations of the model to study. For ordinary differential equations, the overall computation time remains reasonable. However when the model itself is more complex (for instance when it is a set of partial differential equations) it may be time consuming to evaluate it for a single set of parameters. The procedures of population parametrization (for instance using SAEM algorithms) are then very long and in some cases impossible to do within a reasonable time. We propose here a very simple methodology which may accelerate population approaches of complex models, including partial differential equations models. We illustrate our method on the classical KPP equation.
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Contributor : Paul Vigneaux Connect in order to contact the contributor
Submitted on : Thursday, July 25, 2013 - 10:24:39 AM
Last modification on : Thursday, May 26, 2022 - 7:16:02 PM


  • HAL Id : hal-00848024, version 1



Paul Vigneaux. Estimation of PDE's parameters via mixed effects models. Application to KPP equation.. CIMPA Research Summer School on "PDE methods in Biology and Medicine", Jun 2013, La Habana, Cuba. ⟨hal-00848024⟩



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