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Singular Spectrum Analysis : A New Tool in Time Series Analysis by James B. Elsner, Anastasios A. Tsonis is a nonfiction available to read on EtoBox.

What is Singular Spectrum Analysis : A New Tool in Time Series Analysis about?

The term singular spectrum comes from the spectral (eigenvalue) decomposition of a matrix A into its set (spectrum) of eigenvalues. These eigenvalues, A, are the numbers that make the matrix A -AI singular. The term singular spectrum analysis· is unfortunate since the traditional eigenvalue decomposition involving multivariate data is also an analysis of the singular spectrum. More properly, singular spectrum analysis (SSA) should be called the analysis of time series using the singular spectrum. Spectral decomposition of matrices is fundamental to much the ory of linear algebra and it has many applications to problems in the natural and related sciences. Its widespread use as a tool for time series analysis is fairly recent, however, emerging to a large extent from applications of dynamical systems theory (sometimes called chaos theory). SSA was introduced into chaos theory by Fraedrich (1986) and Broomhead and King (l986a). Prior to this, SSA was used in biological oceanography by Colebrook (1978). In the digi tal signal processing community, the approach is also known as the Karhunen-Loeve (K-L) expansion (Pike et aI., 1984). Like other techniques based on spectral decomposition

Who reads Singular Spectrum Analysis : A New Tool in Time Series Analysis?

Author

James B. Elsner, Anastasios A. Tsonis

Publisher

Springer-Verlag New York, LLC

Published

2010

Language

EN

ISBN

9781475725148

Category

nonfiction

Subjects

Science, Business, Political Science

Updated

2026-03-24