Practical estimation of high dimensional stochastic differential mixed-effects models

DOI10.1016/j.csda.2010.10.003zbMath1328.65014arXiv1004.3871OpenAlexW2060092748WikidataQ55940919 ScholiaQ55940919MaRDI QIDQ901512

Susanne Ditlevsen, Umberto Picchini

Publication date: 12 January 2016

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1004.3871

zbMATH Keywords

stochastic differential equationmaximum likelihood estimationautomatic differentiationCox-Ingersoll-Ross processpopulation estimationclosed form transition density expansion

Mathematics Subject Classification ID

Point estimation (62F10) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Numerical solutions to stochastic differential and integral equations (65C30)

Related Items (19)

A review on asymptotic inference in stochastic differential equations with mixed effects ⋮ Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms ⋮ Generalized fixed-effects and mixed-effects parameters height–diameter models with diffusion processes ⋮ Parametric inference for stochastic differential equations driven by a mixed fractional Brownian motion with random effects based on discrete observations ⋮ Estimation for stochastic differential equations with mixed effects ⋮ Nadaraya–Watson estimator for I.I.D. paths of diffusion processes ⋮ Maximum likelihood estimation for stochastic differential equations driven by a mixed fractional Brownian motion with random effects ⋮ Nonparametric estimation for SDE with sparsely sampled paths: an FDA perspective ⋮ On a projection least squares estimator for jump diffusion processes ⋮ Nonparametric estimation for stochastic differential equations with random effects ⋮ Non parametric estimation for fractional diffusion processes with random effects ⋮ Nonparametric estimation in a mixed-effect Ornstein-Uhlenbeck model ⋮ Nonparametric estimation for i.i.d. paths of fractional SDE ⋮ Nonparametric drift estimation for i.i.d. paths of stochastic differential equations ⋮ Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects ⋮ Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient ⋮ Estimating reducible stochastic differential equations by conversion to a least-squares problem ⋮ Nonparametric estimation for stochastic differential equations driven by mixed fractional Brownian motion with random effects ⋮ Particle methods for stochastic differential equation mixed effects models

Uses Software

• S-PLUS
• nlme
• AD Model Builder
• MEMSS
• PSM

Cites Work

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