Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät // Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover 437
Atheoretical regression trees (ART) are applied to detect changes in the mean of a stationary long memory time series when location and number are unknown. It is shown that the BIC, which is almost always used as a pruning method, does not operate well in the long memory framework. A new method is developed to determine the number of mean shifts. A Monte Carlo Study and an application is given to show the performance of the method.