Description: Singular spectrum analysis is a powerful method to study nonlinear time series data in recent years. A trajectory matrix is constructed according to the observed time series, and the trajectory matrix is decomposed and reconstructed, so that the signals representing different components of the original time series are extracted. Such as long-term trend signal, periodic signal, noise signal, and so on, so as to analyze the structure of time series and predict further.
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SingularSpectrum.m
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