HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

A review on asymptotic inference in stochastic differential equations with mixed-effects

Abstract : This paper is a survey of recent contributions on estimation in stochastic differential equations with mixed-effects. These models involve N stochastic differential equations with common drift and diffusion functions but random parameters that allow for differences between processes. The main objective is to estimate the distribution of the random effects and possibly other fixed parameters that are common to the N processes. While many algorithms have been proposed, the theoretical aspects related to estimation have been little studied. This review article focuses only on theoretical inference for stochastic differential equations with mixed-effects. It has so far only been considered in some very specific classes of mixed-effect diffusion models, observed without measurement error, where explicit estimators can be defined. Within this framework, the asymptotic properties of several estimators, either parametric or nonparametric, are discussed. Different schemes of observations are considered according to the approach, associating a large number of individuals with, in most cases, high-frequency observations of the trajectories.
Document type :
Journal articles
Complete list of metadata

Cited literature [35 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02938697
Contributor : Maud Delattre Connect in order to contact the contributor
Submitted on : Tuesday, September 15, 2020 - 9:44:57 AM
Last modification on : Tuesday, April 20, 2021 - 3:28:29 AM
Long-term archiving on: : Thursday, December 3, 2020 - 5:17:20 AM

Files

Hal_JSDS_Delattre.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02938697, version 1

Collections

Citation

Maud Delattre. A review on asymptotic inference in stochastic differential equations with mixed-effects. Japanese Journal of Statistics and Data Science , 2021. ⟨hal-02938697⟩

Share

Metrics

Record views

31

Files downloads

56