Singular Spectrum Analysis: Methodology and Comparison

Hossein Hassani

MPRA Paper from University Library of Munich, Germany

Abstract: In recent years Singular Spectrum Analysis (SSA), used as a powerful technique in time series analysis, has been developed and applied to many practical problems. In this paper, the performance of the SSA technique has been considered by applying it to a well-known time series data set, namely, monthly accidental deaths in the USA. The results are compared with those obtained using Box-Jenkins SARIMA models, the ARAR algorithm and the Holt-Winter algorithm (as described in Brockwell and Davis (2002)). The results show that the SSA technique gives a much more accurate forecast than the other methods indicated above.

Keywords: ARAR algorithm; Box-Jenkins SARIMA models; Holt-Winter algorithm; singular spectrum analysis (SSA); USA monthly accidental deaths series (search for similar items in EconPapers)
JEL-codes: C14 C53 C61 (search for similar items in EconPapers)
Date: 2007-04-01
New Economics Papers: this item is included in nep-ecm and nep-for
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Citations: View citations in EconPapers (59)

Published in Journal of Data Science 2.5(2007): pp. 239-257

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:4991

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