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Wavelets in Time Series Analysis (1999)
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| Venue: | Phil. Trans. R. Soc. Lond. A |
| Citations: | 35 - 7 self |
BibTeX
@ARTICLE{Nason99waveletsin,
author = {Guy P. Nason and Rainer von Sachs},
title = {Wavelets in Time Series Analysis},
journal = {Phil. Trans. R. Soc. Lond. A},
year = {1999},
volume = {357},
pages = {2511--2526}
}
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Abstract
This article reviews the role of wavelets in statistical time series analysis. We survey work that emphasises scale such as estimation of variance and the scale exponent of a process with a specific scale behaviour such as 1/f processes. We present some of our own work on locally stationary wavelet (lsw) processes which model both stationary and some kinds of non-stationary processes. Analysis of time series assuming the lsw model permits identification of an evolutionary wavelet spectrum (ews) that quantifies the variation in a time series over a particular scale and at a particular time. We address estimation of the ews and show how our methodology reveals phenomena of interest in an infant electrocardiogram series.
Keyphrases
time series analysis time series infant electrocardiogram series stationary wavelet evolutionary wavelet spectrum survey work specific scale behaviour particular scale lsw model non-stationary process particular time address estimation methodology reveals phenomenon scale exponent statistical time series analysis
