Singular Spectrum Analysis for time series: Introduction to this special issue
نویسندگان
چکیده
منابع مشابه
Singular Spectrum Analysis for time series: Introduction to this special issue
General. Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. From the algorithmic point of view, SSA can be considered as a typical subspace-based method of signal processing. SSA aims at decomposing the original se...
متن کاملSingular Spectrum Analysis for Time Series
Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA aims at decomposing the original series into a sum of a small number of interpretable components such as a slowly varying trend, oscillatory components and a ‘...
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We propose a novel approach for constructing Singular Spectrum Analysis (SSA) forecast based on estimating new coefficients of Linear Recurrent Formula. The results indicate that the proposed method is more reliable in comparison to the widely used approaches that were proposed along with SSA. We conduct simulation studies to compare the relative performance of the new method with the existing ...
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This paper is a study of continuous time Singular Spectrum Analysis (SSA). We show that the principal eigenfunctions are solutions to a set of linear ODEs with constant coefficients. We also introduce a natural generalization of SSA, constructed using local (Lie-) transformation groups. The time translations used in standard SSA is a special case. The eigenfunctions then satisfy a simple type o...
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ژورنال
عنوان ژورنال: Statistics and Its Interface
سال: 2010
ISSN: 1938-7989,1938-7997
DOI: 10.4310/sii.2010.v3.n3.a1