GENERALIZED APPROACH TO HURST EXPONENT ESTIMATING BY TIME SERIES

Abstract

This paper presents a generalized approach to the fractal analysis of self-similar random processes by short time series. Several stages of the fractal analysis are proposed. Preliminary time series analysis includes the removal of short-term dependence, the identification of true long-term dependence and hypothesis test on the existence of a self-similarity property. Methods of unbiased interval estimation of the Hurst exponent in cases of stationary and non-stationary time series are discussed. Methods of estimate refinement are proposed. This approach is applicable to the study of self-similar time series of different nature.

Authors and Affiliations

Lyudmyla Kirichenko, Tamara Radivilova, Vitalii Bulakh

Keywords

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  • EP ID EP261987
  • DOI 10.5604/01.3001.0010.8639
  • Views 106
  • Downloads 0

How To Cite

Lyudmyla Kirichenko, Tamara Radivilova, Vitalii Bulakh (2018). GENERALIZED APPROACH TO HURST EXPONENT ESTIMATING BY TIME SERIES. Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska, 8(1), 28-31. https://europub.co.uk/articles/-A-261987