  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.
