Detecting structural changes using wavelets
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Date
2015
Authors
Ozkan, Harun
Journal Title
Journal ISSN
Volume Title
Publisher
Academic Press Inc Elsevier Science
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Abstract
We propose a powerful wavelet method to identify structural breaks in the mean of a process. If there is a structural change in the mean the sum of the squared scaling coefficients absorbs more variation leading to unequal weights for the variances of the wavelet and scaling coefficients. We use this feature of wavelets to design a statistical test for changes in the mean of an independently distributed process. We establish the limiting null distribution of our test and demonstrate that our test has good empirical size and substantive power relative to the existing alternatives especially for multiple breaks. (C) 2014 Elsevier Inc. All rights reserved.
Description
Keywords
Structural change tests, Structural break tests, Wavelets, Maximum overlap discrete wavelet, Transformation
Turkish CoHE Thesis Center URL
Fields of Science
Citation
13
WoS Q
Q1
Scopus Q
Q1
Source
Volume
12
Issue
Start Page
23
End Page
37