Wavelet Methods for Time Series Analysis
Wavelet Methods for Time Series Analysis
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Summary
This introduction to wavelet analysis and 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. The book contains numerous exercises and a website offering access to the time series and wavelet software.
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Wavelet Methods for Time Series Analysis by Donald B Percival
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.
'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
'… 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
Walden, Andrew T.: - Andrew T. Walden has authored 100 refereed papers in scientific areas including statistics, signal processing, geophysics, astrophysics and neuroscience, with an emphasis on spectral analysis and time series methodology. He worked in geophysical exploration research before joining Imperial College London. He is co-author (with Donald B. Percival) of Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques (Cambridge,1993) and Wavelet Methods for Time Series Analysis (Cambridge, 2000). He has taught many courses including time series, spectral analysis, geophysical data analysis, applied probability and graphical modelling, primarily at Imperial College London, and also at the University of Washington.
| SKU | Unavailable |
| ISBN 13 | 9780521685085 |
| ISBN 10 | 0521685087 |
| Title | Wavelet Methods for Time Series Analysis |
| Author | Donald B Percival |
| Series | Cambridge Series In Statistical And Probabilistic Mathematics |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Cambridge University Press |
| Year published | 2006-02-27 |
| Number of pages | 622 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |