Abstract #300270

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JSM 2002 Abstract #300270
Activity Number: 238
Type: Invited
Date/Time: Tuesday, August 13, 2002 : 2:00 PM to 3:50 PM
Sponsor: Business & Economics Statistics Section*
Abstract - #300270
Title: Wavelet-Based Estimation for Seasonal Long-Memory Processes
Author(s): Brandon Whitcher*+
Affiliation(s): National Center for Atmospheric Research
Address: P.O. Box 3000, Boulder, Colorado, 80307-3000,
Keywords: discrete wavelet packet transform ; Gegenbauer process ; maximum likelihood estimation ; time series
Abstract:

We introduce the multiscale analysis of seasonal persistent processes; i.e., time series models with a singularity in their spectral density function at one or more frequencies in [0,1/2]. The discrete wavelet packet transform (DWPT) is introduced as an alternative method to spectral techniques for analyzing time series that exhibit seasonal long-memory. Approximate maximum likelihood estimation is performed by replacing the variance/covariance matrix with a diagonalized matrix based on the DWPT. From simulation studies, maximum likelihood estimation is found to be quite robust when using either the true spectral density function or the log-linear approximation. Applications of this methodology to atmospheric CO2 measurements and U.S. quarterly tourism revenue are presented.

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Revised March 2002