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The program is based on the powerful model-free method of time series analysis Caterpillar-SSA (Singular Spectrum Analysis). The result of the Caterpillar-SSA processing is identification, analysis and forecast of additive components of time series (trends, periodicities, noise). The program can be applied to multivariate analysis/forecasting and change-point detection.
time series forecast analysis trend periodicities seasonalities statistics ssa software principal component decomposition singular value svd reconstruction approximation spectrum
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