The change-point problem for dependent observations

We consider the change-point problem for the marginal distribution function of a strictly stationary time series. Asymptotic behavior of Kolmogorov-Smimov type tests and estimators of the change point is studied under the null hypothesis and converging alternatives, The discussion is based on a general empirical process approach which enables a unified treatment of both short-memory (weakly dependent) and long-memory time series. In particular, the case of long-memory moving-average process X(j) = Sigma(s less than or equal to j)b(j-s)xi(s) is studied, using the recent results of Giraitis and Surgailis (1994).