[en] We give an overview of Bayesian inference methods applied to parameter estimation in models
specified by differential equations. The explored Bayesian methods go from the most basic MCMC
samplers to particle filtering when considering our model as a state-space model. Comparison with
frequentist estimating strategies are also made.
Disciplines :
Mathematics
Author, co-author :
Bonou, Wilfried ; Université de Liège > Faculté des sciences sociales > Méthodes quantitatives en sciences sociales
Lambert, Philippe; Université de Liège - ULiège > Faculté des sciences sociales > Méthodes quantitatives en sciences sociales
Frasso, Gianluca; Université de Liège - ULiège > Faculté des sciences sociales > Méthodes quantitatives en sciences sociales
Language :
English
Title :
State-of-the-Art of Bayesian Inference Methods in Differential Equations.
Publication date :
October 2015
Event name :
The 23rd annual meeting of the Belgian Statistical Society (BSS2015)