Singular Spectrum Analysis for Time Series is popular PDF and ePub book, written by Nina Golyandina in 2013-01-19, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Singular Spectrum Analysis for Time Series can be Read Online from any device for your convenience.
Singular Spectrum Analysis for Time Series Book PDF Summary
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.
Detail Book of Singular Spectrum Analysis for Time Series PDF
- Author : Nina Golyandina
- Release : 19 January 2013
- Publisher : Springer Science & Business Media
- ISBN : 9783642349133
- Genre : Mathematics
- Total Page : 120 pages
- Language : English
- PDF File Size : 11,7 Mb
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