Téléchargez le livre : Singular Spectrum Analysis for Time Series

Singular Spectrum Analysis for Time Series

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Éditeur :

Springer


Collection :

SpringerBriefs in Statistics

Paru le : 2013-01-19

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Description
Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA seeks to decompose the original series into a sum of a small number of interpretable components such as trend, oscillatory components and noise. It is based on the singular value decomposition of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity are assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability. The present book is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis.
Pages
120 pages
Collection
SpringerBriefs in Statistics
Parution
2013-01-19
Marque
Springer
EAN papier
9783642349126
EAN EPUB
9783642349133
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
12
Taille du fichier
2304 Ko
Prix
58,01 €

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