Singular Spectrum Analysis for Time Series als eBook von
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Preise | 2013 | 2014 | 2018 |
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Schnitt | € 28,50 | € 41,64 | € 37,54 |
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1
Singular Spectrum Analysis for Time Series
DE NW
ISBN: 9783642349133 bzw. 3642349137, in Deutsch, Springer Berlin, neu.
Lieferung aus: Deutschland, sofort lieferbar.
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 sig.
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 sig.
2
Singular Spectrum Analysis for Time Series
DE NW EB DL
ISBN: 9783642349133 bzw. 3642349137, in Deutsch, Springer Berlin, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Versandkostenfrei.
Singular Spectrum Analysis for Time Series: 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. Englisch, Ebook.
Singular Spectrum Analysis for Time Series: 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. Englisch, Ebook.
3
Singular Spectrum Analysis for Time Series (SpringerBriefs in Statistics) (2013)
EN NW EB DL
ISBN: 9783642349133 bzw. 3642349137, in Englisch, 125 Seiten, 2013. Ausgabe, Springer, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, E-Book zum Download.
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. Kindle Edition, Ausgabe: 2013, Format: Kindle eBook, Label: Springer, Springer, Produktgruppe: eBooks, Publiziert: 2013-01-19, Freigegeben: 2013-01-19, Studio: Springer, Verkaufsrang: 114214.
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. Kindle Edition, Ausgabe: 2013, Format: Kindle eBook, Label: Springer, Springer, Produktgruppe: eBooks, Publiziert: 2013-01-19, Freigegeben: 2013-01-19, Studio: Springer, Verkaufsrang: 114214.
4
Singular Spectrum Analysis for Time Series (2013)
DE NW
ISBN: 9783642349133 bzw. 3642349137, in Deutsch, Springer, Berlin/Heidelberg/New York, NY, Deutschland, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
5
Singular Spectrum Analysis for Time Series als eBook von Nina Golyandina, Anatoly Zhigljavsky, Nina Golyandina, Anatoly Zhigljavsky (2013)
DE NW
ISBN: 9783642349133 bzw. 3642349137, in Deutsch, Springer Berlin Heidelberg, neu.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, Versandkostenfrei.
Singular Spectrum Analysis for Time Series ab 35.49 EURO Auflage 2013.
Singular Spectrum Analysis for Time Series ab 35.49 EURO Auflage 2013.
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