Cho, Haeran and Fryzlewicz, Piotr 
ORCID: 0000-0002-9676-902X
(2012)
Multiscale and multilevel technique for consistent segmentation of nonstationary time series.
Statistica Sinica, 22 (1).
pp. 207-229.
ISSN 1017-0405
Abstract
In this paper, we propose a fast, well-performing, and consistent method for segmenting a piecewise-stationary, linear time series with an unknown number of breakpoints. The time series model we use is the nonparametric Locally Stationary Wavelet model, in which a complete description of the piecewise-stationary second-order structure is provided by wavelet periodograms computed at multiple scales and locations. The initial stage of our method is a new binary segmentation procedure, with a theoretically justified and rapidly computable test criterion that detects breakpoints in wavelet periodograms separately at each scale. This is followed by within-scale and across-scales post-processing steps, leading to consistent estimation of the number and locations of breakpoints in the second-order structure of the original process. An extensive simulation study demonstrates good performance of our method.
| Item Type: | Article |
|---|---|
| Official URL: | http://www3.stat.sinica.edu.tw/statistica/ |
| Additional Information: | © 2012 Institute of Statistical Science, Academia Sinica |
| Divisions: | Statistics |
| Subjects: | H Social Sciences > HA Statistics |
| Date Deposited: | 16 Apr 2012 11:49 |
| Last Modified: | 12 Dec 2024 00:07 |
| URI: | http://eprints.lse.ac.uk/id/eprint/43104 |
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