Martingale problems for conditional distributions of Markov processes

Let X be a Markov process with generator A and let Y (t) = γ(X(t)). The conditional distribution πt of X(t) given σ(Y (s) : s ≤ t) is characterized as a solution of a filtered martingale problem. As a consequence, we obtain a generator/martingale problem version of a result of Rogers and Pitman on Markov functions. Applications include uniqueness of filtering equations, exchangeability of the state distribution of vector-valued processes, verification of quasireversibility, and uniqueness for martingale problems for measure-valued processes. New results on the uniqueness of forward equations, needed in the proof of uniqueness for the filtered martingale problem are also presented. AMS 1991 subject classifications: 60G35, 60J25, 60J35, 93E11, 60G09, 60G44