Wavelet Methods for Time Series Analysis

By: Donald B. Percival, Andrew T. Walden

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Paperback | 1 May 2006

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622 Pages

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24.41 x 16.99 x 3.18

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The analysis of time series data is essential to many areas of science, engineering, finance and economics. This introduction to wavelet analysis "from the ground level and up," and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises--with complete solutions provided in the Appendix--allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential. Author resource page: http://faculty.washington.edu/dbp/wmtsa.html

Industry Reviews

'In my opinion the book by Percival and Walden should be available in every university library, and every time-series analyst must read this book for an alternative (to Fourier) set of techniques.' T. Subba Rao, Publication of the International Statistical Institute '... would be an ideal text for a statistics doctoral student who is new to the field of wavelets ... the content, lay-out and consistency of the text mean that it should also be a valuable reference resource for the wavelet researcher.' Tim Downie, The Statistician 'The authors ... provide considerable background material, tell their story from scratch, proceed at a careful pace ... and work out detailed applications ... Recommended.' Choice

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Introduction to wavelets
Review of Fourier theory and filters
Orthonormal transforms of time series
The discrete wavelet transform
The maximal overlap discrete wavelet transform
The discrete wavelet packet transform
Random variables and stochastic processes
The wavelet variance
Analysis and synthesis of long memory processes
Wavelet-based signal estimation
Wavelet analysis of finite energy signals
Appendix. Answers to embedded exercises
References
Author index
Subject index
Table of Contents provided by Publisher. All Rights Reserved.

Wavelet Methods for Time Series Analysis

At a Glance

Paperback

Industry Reviews

Shipping

How to return your order

Defective items

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