On Bayesian Asymptotics in Stochastic Differential Equations with Random Effects
Statistics Theory
2016-05-12 v3 Statistics Theory
Abstract
Delattre et al. (2013) investigated asymptotic properties of the maximum likelihood estimator of the population parameters of the random effects associated with n independent stochastic differential equations (SDEs) assuming that the SDEs are independent and identical (iid). In this article, we consider the Bayesian approach to learning about the population parameters, and prove consistency and asymptotic normality of the corresponding posterior distribution in the iid set-up as well as when the SDEs are independent but non-identical.
Cite
@article{arxiv.1407.3971,
title = {On Bayesian Asymptotics in Stochastic Differential Equations with Random Effects},
author = {Trisha Maitra and Sourabh Bhattacharya},
journal= {arXiv preprint arXiv:1407.3971},
year = {2016}
}
Comments
This version appeared in Statistics and Probability Letters