Time Series in the Frequency Domain

P. R. Krishnaiah

ISBN 10: 0444867260 / ISBN 13: 9780444867261

Edité par Elsevier Science & Technology Feb 1984, 1984

A propos de cet article

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.

N° de réf. du vendeur 9780444867261

Détails bibliographiques

• Titre: Time Series in the Frequency Domain
• Éditeur: Elsevier Science & Technology Feb 1984
• Date de parution: 1984
• Langue: anglais
• ISBN à 10 chiffres: 0444867260
• ISBN à 13 chiffres: 9780444867261
• Reliure: Buch
• État de l'article: Neu
• Poids: 1080 grammes

A propos de ce titre

Synopsis

Hardbound. 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 illustrate, these assumptions are not necessary. This volume complements Handbook of Statistics 5: Time Series in the