in my opinion, you can use markov chain concepts. by this concepts you are now dealing with the transitive probabilities from one step to another. for a fixed time t=t0, your system states on a probability field , such that each probability of the states is determined by your eigenfunctions, and then you wish to know the probability of the system being the next step (or state) at time t=t1 where t1>t0.