Based on the 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 analysis program, written in Java, to accompany book "Applied Time Series Analysis", by Helmut Lutkepohl and Markus Kratzig.

Using novel tools such as singular spectrum analysis and multitaper method, time series can be decomposed into noise and predictable components - trends and oscillatory modes, which can be reconstructed and forecast.