Parametric inference for discrete observations of diffusion processes with mixed effects

Maud Delattre, Valentine Genon-Catalot and Catherine Larédo

Stochastic Processes and their Applications, 2018, vol. 128, issue 6, 1929-1957

Abstract: Stochastic differential equations with mixed effects provide means to model intra-individual and inter-individual variability in repeated experiments leading to longitudinal data. We consider N i.i.d. stochastic processes defined by a stochastic differential equation with linear mixed effects which are discretely observed. We study a parametric framework with distributions leading to explicit approximate likelihood functions and investigate the asymptotic behavior of estimators under the asymptotic framework : the number N of individuals (trajectories) and the number n of observations per individual tend to infinity within a fixed time interval. The estimation method is assessed on simulated data for various models.

Keywords: Discrete observations; Estimating equations; Mixed-effects models; Parametric inference; Stochastic differential equations (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.spa.2017.08.016

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