Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient

3 SAM - Statistique Apprentissage Machine
LJK - Laboratoire Jean Kuntzmann
Abstract : We consider $N$ independent stochastic processes $(X_i(t), t\in [0,T_i])$, $i=1,\ldots, N$, defined by a stochastic differential equation with diffusion coefficients depending on a random variable $\phi_i$. The distribution of the random effect $\phi_i$ depends on unknown population parameters which are to be estimated from a discrete observation of the processes $(X_i)$. The likelihood generally does not have any closed form expression. Two estimation methods are proposed: one based on the Euler approximation of the likelihood and another based on estimations of the random effects. When the distribution of the random effects is Gamma, the asymptotic properties of the estimators are derived when both $N$ and the number of observations per subject tend to infinity. The estimators are computed on simulated data for several models and show good performances.
Type de document :
Article dans une revue
ESAIM: Probability and Statistics, EDP Sciences, 2015, 19, pp.671-688. 〈10.1051/ps/2015006 〉
Domaine :
Liste complète des métadonnées

Littérature citée [5 références]

https://hal.archives-ouvertes.fr/hal-01056917
Contributeur : Adeline Samson <>
Soumis le : samedi 6 décembre 2014 - 14:25:26
Dernière modification le : jeudi 7 février 2019 - 14:53:16
Document(s) archivé(s) le : lundi 9 mars 2015 - 06:07:21

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revision_Delattreetal.pdf
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Maud Delattre, Valentine Genon-Catalot, Adeline Samson. Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient. ESAIM: Probability and Statistics, EDP Sciences, 2015, 19, pp.671-688. 〈10.1051/ps/2015006 〉. 〈hal-01056917v2〉

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