A Review on Singular Spectrum Analysis

Abstract

Singular Spectrum Analysis (SSA), a relatively new but effective approach in time series analysis, has been devised and widely used in various of practical problems in the recent years. It is regarded as PCA for time series how-ever has huge advantages over it. SSA will surely become a principal time series analysis method in the future. The aim of this paper is to aware scientific com-munities with the knowledge of various advances and extensions of SSA. This paper begins with brief history of SSA. The paper also discusses the Basic SSA algorithm and its stages. Here, in this paper, recent advances in the conceptual and algorithmic aspects of the SSA are studied upon and reviewed. These include the recent developments and extension of the Basic SSA. This paper also com-pares the Basic SSA with other classical methods, their similarities and differences from one and other.