Computational and Applied Mathematics

, Volume 36, Issue 4, pp 1545–1558 | Cite as

Weighted moving averaging revisited: an algebraic approach

  • Mantas Landauskas
  • Zenonas Navickas
  • Alfonsas Vainoras
  • Minvydas Ragulskis
Article
First Online:
Received:
Revised:
Accepted:

Abstract

An algebraic approach for the selection of weight coefficients for weighted moving averaging is proposed in this paper. The algebraic complexity of the sequence transformed by weighted moving averaging is set as a target criterion for the optimization problem of weight coefficients. A special computational setup is constructed in order to tackle the inevitable additive noise for real-world time series. Computational experiments prove that the proposed approach can outperform time series predictors based on classical moving averaging.

Keywords

Moving average Time series prediction Weight coefficients 

Mathematics Subject Classification

37M10 11B37 37M99 
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Notes

Acknowledgments

This work was supported by the Lithuanian Science Council under project No. MIP-078/2015.

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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2016

Authors and Affiliations

  • Mantas Landauskas
    • 1
  • Zenonas Navickas
    • 2
  • Alfonsas Vainoras
    • 3
  • Minvydas Ragulskis
    • 1
  1. 1.Research Group for Mathematical and Numerical Analysis of Dynamical SystemsKaunas University of TechnologyKaunasLithuania
  2. 2.Department of Applied MathematicsKaunas University of TechnologyKaunasLithuania
  3. 3.Sport InstituteLithuanian University of Health SciencesKaunasLithuania

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