Wavelet Methods for Time Series Analysis

Nonfiction, Science & Nature, Mathematics, Statistics, Computers, General Computing
Cover of the book Wavelet Methods for Time Series Analysis by Donald B. Percival, Andrew T. Walden, Cambridge University Press
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Author: Donald B. Percival, Andrew T. Walden ISBN: 9781107713307
Publisher: Cambridge University Press Publication: February 27, 2006
Imprint: Cambridge University Press Language: English
Author: Donald B. Percival, Andrew T. Walden
ISBN: 9781107713307
Publisher: Cambridge University Press
Publication: February 27, 2006
Imprint: Cambridge University Press
Language: English

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.

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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.

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