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Wavelets in Time Series Analysis

Listed author(s):
  • Nason, G.P.
  • von Sachs, R.
Registered author(s):

    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 particualr state 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.

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    Paper provided by Catholique de Louvain - Institut de statistique in its series Papers with number 9901.

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    Length: 16 pages
    Date of creation: 1999
    Handle: RePEc:fth:louvis:9901
    Contact details of provider: Postal:
    Universite Catholique de Louvain, Institut de Statistique, Voie du Roman Pays, 34 B-1348 Louvain- La-Neuve, Belgique.

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