A wavelet-based approach for detecting changes in second order structure within nonstationary time series

Killick, Rebecca and Eckley, Idris and Jonathan, Philip (2013) A wavelet-based approach for detecting changes in second order structure within nonstationary time series. Electronic Journal of Statistics, 7. pp. 1167-1183. ISSN 1935-7524

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Abstract

This article proposes a test to detect changes in general autocovariance structure in nonstationary time series. Our approach is founded on the locally stationary wavelet (LSW) process model for time series which has previously been used for classification and segmentation of time series. Using this framework we form a likelihood-based hypothesis test and demonstrate its performance against existing methods on various simulated examples as well as applying it to a problem arising from ocean engineering.

Item Type:
Journal Article
Journal or Publication Title:
Electronic Journal of Statistics
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa
Subjects:
ID Code:
66237
Deposited By:
Deposited On:
17 Sep 2013 07:55
Refereed?:
Yes
Published?:
Published
Last Modified:
08 Jul 2020 03:38