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

DOI10.1051/ps/2015006zbMath1392.62249OpenAlexW2095138591MaRDI QIDQ2786499

Valentine Genon-Catalot, Maud Delattre, Adeline Samson

Publication date: 12 February 2016

Published in: ESAIM: Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1051/ps/2015006

zbMATH Keywords

consistencyasymptotic normalitystochastic differential equationsrandom effects modelsestimating equationsapproximate maximum likelihood estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Markov processes: estimation; hidden Markov models (62M05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items (4)

A review on asymptotic inference in stochastic differential equations with mixed effects ⋮ Estimation for stochastic differential equations with mixed effects ⋮ Parametric estimation from approximate data: non-Gaussian diffusions ⋮ Nonparametric estimation in a mixed-effect Ornstein-Uhlenbeck model

Uses Software

• MsdeParEst

Cites Work

• Coupling the SAEM algorithm and the extended Kalman filter for maximum likelihood estimation in mixed-effects diffusion models
• Practical estimation of high dimensional stochastic differential mixed-effects models
• Uniform asymptotic normality of the maximum likelihood estimator
• On the estimation of the diffusion coefficient for multi-dimensional diffusion processes
• Parameter estimation for discretely observed stochastic volatility models
• Information quantities in non-classical settings
• Strong consistency of the maximum likelihood estimator in generalized linear and nonlinear mixed-effects models
• Stochastic Differential Mixed-Effects Models
• Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects
• Parametric inference for mixed models defined by stochastic differential equations

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