Abstract
In Chap. 4 the problem of simultaneous decomposition, reconstruction, and forecasting for a collection of time series is considered from the viewpoint of SSA; note that individual time series can have different length. The main method of this chapter is usually called either Multichannel SSA or Multivariate SSA, shortly MSSA. The principal idea of MSSA is the same as for the case of one-dimensional time with the difference lying in the way of constructing of the trajectory matrix. The aim of MSSA is to take into consideration the combined structure of a multivariate series to obtain more accurate results.
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Golyandina, N., Korobeynikov, A., Zhigljavsky, A. (2018). SSA for Multivariate Time Series. In: Singular Spectrum Analysis with R. Use R!. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57380-8_4
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DOI: https://doi.org/10.1007/978-3-662-57380-8_4
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