Abstract
When multiple time series are observed, we are usually interested in the internal structure of each, and at the same time their joint structure, or the dependency among series. Accordingly, the second chapter of this book is dedicated to this vital concept. In this chapter, the basic univariate Singular Spectrum Analysis (SSA) is extended in a fairly obvious way to the multivariate case and transition from univariate SSA to multivariate with emphasis on intuition and applications are deliberated. The related multivariate SSA codes along with several practical examples are also presented.
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Hassani, H., Mahmoudvand, R. (2018). Multivariate Singular Spectrum Analysis. In: Singular Spectrum Analysis. Palgrave Advanced Texts in Econometrics. Palgrave Pivot, London. https://doi.org/10.1057/978-1-137-40951-5_2
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DOI: https://doi.org/10.1057/978-1-137-40951-5_2
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Publisher Name: Palgrave Pivot, London
Print ISBN: 978-1-137-40950-8
Online ISBN: 978-1-137-40951-5
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