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Spectral Analysis for Univariate Time Series (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51) - Hardcover
- PublisherCambridge University Press
- Publication date2020
- ISBN 10 1107028140
- ISBN 13 9781107028142
- BindingHardcover
- LanguageEnglish
- Edition number2
- Number of pages780
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Spectral Analysis for Univariate Time Series (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
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Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
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Spectral analysis for univariate time series - Donald B. Percival
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Spectral Analysis for Univariate Time Series
Published by
Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
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Spectral Analysis for Univariate Time Series (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
Published by
Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
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Hardcover
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Spectral Analysis for Univariate Time Series (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 51)
Published by
Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
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Hardcover
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Spectral Analysis for Univariate Time Series
Published by
Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
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Hardcover
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Spectral Analysis for Univariate Time Series (Hardcover)
Published by
Cambridge University Press, Cambridge, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
New
Hardcover
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
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Hardcover. Condition: new. Hardcover. Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website. Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781107028142
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Spectral Analysis for Univariate Time Series
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Hardcover. Condition: Brand New. 780 pages. 10.25x7.25x1.75 inches. In Stock. Seller Inventory # __1107028140
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Spectral Analysis for Univariate Time Series (Hardcover)
Published by
Cambridge University Press, Cambridge, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
New
Hardcover
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website. Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781107028142
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Spectral Analysis for Univariate Time Series
Published by
Cambridge University Press, 2020
ISBN 10: 1107028140
ISBN 13: 9781107028142
New
Hardcover
Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the ga. Seller Inventory # 289255543
Quantity: Over 20 available