  Given a heterogeneous time-series sample, the objective is to find points in
time (called change points) where the probability distribution generating the
data has changed. The data are assumed to have been generated by arbitrary
unknown stationary ergodic distributions. No modelling, independence or mixing
assumptions are made. A novel, computationally efficient, nonparametric method
is proposed, and is shown to be asymptotically consistent in this general
framework. The theoretical results are complemented with experimental
evaluations.
