JSM 2005 - Toronto

Abstract #302300

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 336
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #302300
Title: Wavelet SiZer Analysis of Internet Traffic
Author(s): James Marron*+
Companies: University of North Carolina, Chapel Hill
Address: Department of Statistics & OR, Chapel Hill, NC, 27599-3260, United States
Keywords: Internet Traffic ; Long--range dependence ; Nonstationarity ; Scale-space ; time series ; wavelets
Abstract:

SiZer is a scale-space-based visualization tool for statistical inference. It is used to discover meaningful structure in data through exploratory analysis involving statistical smoothing techniques. Wavelet methods have been successfully used to analyze various types of time series. In this paper, we propose a new time series analysis approach, which combines the wavelet analysis with the visualization tool SiZer. We use certain functions of wavelet coefficients at different scales as inputs, and then apply SiZer to highlight potential nonstationarities. We show that this new methodology can reveal hidden, local, nonstationary behavior of time series that are otherwise difficult to detect.

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