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Nonparametric estimation for stochastic differential equations with random effects

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  • Comte, F.
  • Genon-Catalot, V.
  • Samson, A.

Abstract

We consider N independent stochastic processes (Xj(t),t∈[0,T]), j=1,…,N, defined by a one-dimensional stochastic differential equation with coefficients depending on a random variable ϕj and study the nonparametric estimation of the density of the random effect ϕj in two kinds of mixed models. A multiplicative random effect and an additive random effect are successively considered. In each case, we build kernel and deconvolution estimators and study their L2-risk. Asymptotic properties are evaluated as N tends to infinity for fixed T or for T=T(N) tending to infinity with N. For T(N)=N2, adaptive estimators are built. Estimators are implemented on simulated data for several examples.

Suggested Citation

  • Comte, F. & Genon-Catalot, V. & Samson, A., 2013. "Nonparametric estimation for stochastic differential equations with random effects," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2522-2551.
    • Handle: RePEc:eee:spapps:v:123:y:2013:i:7:p:2522-2551
    DOI: 10.1016/j.spa.2013.04.009
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    References listed on IDEAS

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    1. L. Nie, 2006. "Strong Consistency of the Maximum Likelihood Estimator in Generalized Linear and Nonlinear Mixed-Effects Models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 63(2), pages 123-143, April.
    2. Antic, J. & Laffont, C.M. & Chafaï, D. & Concordet, D., 2009. "Comparison of nonparametric methods in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 642-656, January.
    3. Picchini, Umberto & Ditlevsen, Susanne, 2011. "Practical estimation of high dimensional stochastic differential mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1426-1444, March.
    4. Fabienne Comte & Adeline Samson, 2012. "Nonparametric estimation of random-effects densities in linear mixed-effects model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 951-975, December.
    5. Umberto Picchini & Andrea De Gaetano & Susanne Ditlevsen, 2010. "Stochastic Differential Mixed‐Effects Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 67-90, March.
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    Cited by:

    1. Delattre, Maud & Genon-Catalot, Valentine & Larédo, Catherine, 2018. "Parametric inference for discrete observations of diffusion processes with mixed effects," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 1929-1957.
    2. Mohammadi, Neda & Santoro, Leonardo V. & Panaretos, Victor M., 2024. "Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective," Stochastic Processes and their Applications, Elsevier, vol. 167(C).
    3. Dai, Min & Duan, Jinqiao & Liao, Junjun & Wang, Xiangjun, 2021. "Maximum likelihood estimation of stochastic differential equations with random effects driven by fractional Brownian motion," Applied Mathematics and Computation, Elsevier, vol. 397(C).

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