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Sprache: Englisch
Verlag: North Holland Publishing Company, 1983
ISBN 10: 0444867260 ISBN 13: 9780444867261
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In den WarenkorbZustand: Good. Volume 3. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1050grams, ISBN:0444867260.
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Zustand: Gut. Zustand: Gut | Seiten: 500 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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In den WarenkorbGebunden. Zustand: New. InhaltsverzeichnisWiener Filtering (with Emphasis on Frequency-Domain Approaches) (R.J. Bhansali, D. Karavellas). The Finite Fourier Transform of a Stationary Process (D.R. Brillinger). Seasonal and Calendar Adjustment (W.S. Cleveland). .
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Buch. Zustand: Neu. Handbook of Statistics Vol.3 HS 3 Time Series in the Frequency Domain | David R. Brillinger (u. a.) | Buch | Gebunden | Englisch | 1984 | Elsevier BV | EAN 9780444867261 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Elsevier Science & Technology Feb 1984, 1984
ISBN 10: 0444867260 ISBN 13: 9780444867261
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - This volume of the Handbook is concerned particularly with the frequency side, or spectrum, approach to time series analysis. This approach involves essential use of sinusoids and bands of (angular) frequency, with Fourier transforms playing an important role. A principal activity is thinking of systems, their inputs, outputs, and behavior in sinusoidal terms. In many cases, the frequency side approach turns out to be simpler with respect to computational, mathematical, and statistical aspects. In the frequency approach, an assumption of stationarity is commonly made. However, the essential roles played by the techniques of complex demodulation and seasonal adjustment show that stationarity is far from being a necessary condition. Assumptions of Gaussianity and linearity are also commonly made and yet, as a variety of the papers in this volume illustrate, these assumptions are not necessary.