Singular Spectrum Analysis: Methodology and Comparison

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 tech-nique has been considered by applying it to a well-known time series data set, namely, monthly accidental deaths in the USA. The results are com-pared 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.