We introduce verifiable criteria for weak posterior consistency of
identifiable Bayesian nonparametric inference for jump diffusions with unit
diffusion coefficient and uniformly Lipschitz drift and jump coefficients in
arbitrary dimension. The criteria are expressed in terms of coefficients of the
SDEs describing the process, and do not depend on intractable quantities such
as transition densities. We also show that products of discrete net and
Dirichlet mixture model priors satisfy our conditions, again under an
identifiability assumption. This generalises known results by incorporating
jumps into previous work on unit diffusions with uniformly Lipschitz drift
coefficients.Comment: 20 page
