Svetlana Polukoshko, Janis Hofmanis


This paper deals with the Caterpillar»-SSA method, a novel and powerful model-free method of time series analysis and forecasting. Alongside with signal processing this method is successfully used to study the time series in many various areas: in meteorology, hydrology, sociology, economics, traffic analysis, wherever the trend or periodic behavior can present. Examples of application of the Caterpillar”-SSA technique for analysis of one-dimensional time series in Latvian economics are presented in this work. We solve the task of analysis and forecasting of following time series: agricultural crop yield, milk production and purchase, number of road traffic accidents and number of registered road vehicles, electricity consumption. The application of Caterpillar»-SSA approach in geotechnical investigation for processing of data of the static penetration test of soils are offered. This method combines the advantage of many other methods, in particular, Fourier analysis and regressive analysis. At the same time it is noted for simplicity and clearness.


time series; Singular Spectrum Analysis; sequential algorithm; singular value decomposition; forecast

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