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Parameter estimation in non-linear mixed effects models with SAEM algorithm: extension from ODE to PDE
- Source :
- ESAIM: Mathematical Modelling and Numerical Analysis, ESAIM: Mathematical Modelling and Numerical Analysis, 2014, 48 (5), pp.1303-1329. ⟨10.1051/m2an/2013140⟩, ESAIM: Mathematical Modelling and Numerical Analysis, EDP Sciences, 2014, 48 (5), pp.1303-1329. ⟨10.1051/m2an/2013140⟩
- Publication Year :
- 2014
- Publisher :
- EDP Sciences, 2014.
-
Abstract
- In this HAL v2: correction of a bibtex bug for the now duly referenced book [20] and special issue [9]. Added link to sample code (matlab - monolix); International audience; 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 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 parametrization of complex models, including partial differential equations models. We illustrate our method on the classical KPP equation.
- Subjects :
- Computation
MSC: 35Q62, 35Q92, 35R30, 65C40, 35K57
Population
SAEM algorithm
KPP equation
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Parameter estimation
[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
education
Mathematics
Numerical Analysis
education.field_of_study
Partial differential equation
Estimation theory
Applied Mathematics
Ode
[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]
Partial differential equations
Computational Mathematics
Nonlinear system
Modeling and Simulation
Ordinary differential equation
Parametrization
Algorithm
[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Analysis
Subjects
Details
- ISSN :
- 12903841 and 0764583X
- Volume :
- 48
- Database :
- OpenAIRE
- Journal :
- ESAIM: Mathematical Modelling and Numerical Analysis
- Accession number :
- edsair.doi.dedup.....3e1c9496449eadae4d35ac658b28e525
- Full Text :
- https://doi.org/10.1051/m2an/2013140