APPROXIMATION OF TIME SERIES WITH MULTIPLE SWITCHING POINTS
Journal Title: Новітні технології - Year 2019, Vol 1, Issue 8
Abstract
This paper deals with the problem of building and selecting the best mathematical model for describing the dynamics of oil imports in the United States of America from 1973 to 2016. The time-series that was investigated is non-stationary and has a changing geometrical structure, therefore, for its description multi-segmented linear regression was proposed. Two algorithms for approximation of this time series are considered. The first algorithm is based on a four-dimensional optimization paraboloid usage. Second algorithm corresponds to the moving angle method. Analytical expressions for the optimal equations of multi-segmented linear regressions are obtained. The general equation of four-segmented regression was obtained using Heaviside function. The optimization of the switching points abscissa was performed by minimizing the standard deviation. The obtained optimal models can be used to solve prediction tasks.
Authors and Affiliations
V. M. Kuzmyn, M. Yu. Zaliskyi, O. V. Kozhokhina, Ye. O. Kaminskyi
Keywords
Related Articles
- EP ID EP492477
- DOI 10.31180/2524-0102/2019.1.08.01
- Views 140
- Downloads 0
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