ESTIMATION IN MULTI-PATH CHANGE-POINT PROBLEMS

The current literature deals with the change-point problem only in the context of the observation of a single sequence. In this paper, inference will be based on the observation of N sequences of random variables, each sequence containing one change-point. This extension allows the effective use of bootstrap and empirical Bayes methods, both of which are not feasible in the single-path context. Two classes of these "multi-path" change-point problems are considered. If the change-point is assumed to occur at the same position in each sequence, then the terminology "fixed-tau multi-path change-point" will be used. In other cases, one may expect the change-point to occur at random positions in each sequence, according to some distribution, a "random-tau multi-path change-point" problem. Examples and simulations are given.