Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/37121
Authors: 
Willert, Juliane
Year of Publication: 
2010
Series/Report no.: 
Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät // Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover 437
Abstract: 
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.
Subjects: 
long memory
mean shift
regression tree
ART
BIC
JEL: 
C14
C22
Document Type: 
Working Paper

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