Using wavelets for data smoothing: A simulation study

Graham Horgan

Journal of Applied Statistics, 1999, vol. 26, issue 8, 923-932

Abstract: Wavelet shrinkage has been proposed as a highly adaptable approach to signal smoothing, which can produce optimum results in some senses. This paper examines the performance of the method as a function of its parameters, by simulation for time series showing gradual, rapid and discontinuous variations, for a range of signal-to-noise ratios. Some general conclusions are drawn. The effects of the choice of wavelet, choice of threshold and choice of resolution cut-off are considered. The use of the residual autocorrelation as a diagnostic tool is suggested.

Date: 1999
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DOI: 10.1080/02664769921936

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