Asymptotic Theory of Bayes Factor in Stochastic Differential Equations with Random Effects
Trisha Maitra, Sourabh Bhattacharya · arXiv (Cornell University) · 2015
Research on model selection in the context of stochastic differential equations (SDE's) is almost non-existent in the literature. In particular, when a system of SDE's is considered, as in random effects models, the problem of model selection has not been hitherto investigated. In this article, we consider a system of SDE's for modeling random effects, and address the question of model selection using Bayes factors. Specifically, we develop the asymptotic theory of Bayes factors when the observed processes associated with the systems of SDE's are independently and identically distributed, as well as when they are independently but not identically distributed.