Generalized approach to Hurst exponent estimating

Публікація:
Generalized approach to Hurst exponent estimating

dc.contributor.author	Булах, В. А.
dc.contributor.author	Кіріченко, Л. О.
dc.contributor.author	Радивилова, Т. А.
dc.date.accessioned	2018-06-05T18:57:03Z
dc.date.available	2018-06-05T18:57:03Z
dc.date.issued	2018
dc.description.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 selfsimilar time series of different nature	uk_UA
dc.identifier.citation	Bulakh V. Generalized approach to Hurst exponent estimating / V. Bulakh, L. Kirichenko, T. Radivilova // Informatyka, Automatyka, Pomiary w Gospodarcei Ochronie Środowiska (IAPGOŚ). – 2018. – №8 (1). – РР. 28-31.	uk_UA
dc.identifier.uri	http://openarchive.nure.ua/handle/document/5842
dc.language.iso	en	uk_UA
dc.publisher	IAPGOŚ	uk_UA
dc.subject	self-similar stochastic process	uk_UA
dc.subject	time series	uk_UA
dc.subject	Hurst exponent	uk_UA
dc.title	Generalized approach to Hurst exponent estimating	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication