Pregled bibliografske jedinice broj: 750968
Scaling properties of the empirical structure function of linear fractional stable motion and estimation of its parameters
Scaling properties of the empirical structure function of linear fractional stable motion and estimation of its parameters // Journal of statistical physics, 158 (2015), 1; 105-119 doi:10.1007/s10955-014-1126-4 (međunarodna recenzija, članak, znanstveni)
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Naslov
Scaling properties of the empirical structure function of linear fractional stable motion and estimation of its parameters
Autori
Grahovac, Danijel ; Leonenko, Nikolai ; Taqqu, Murad
Izvornik
Journal of statistical physics (0022-4715) 158
(2015), 1;
105-119
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Hurst parameter; tail index; self-similarity; stable index
Sažetak
Linear fractional stable motion is an example of a self-similar stationary increments stochastic process exhibiting both long-range dependence and heavy-tails. In this paper we propose methods that are able to estimate simultaneously the self-similarity parameter and the tail parameter. These methods are based on the asymptotic behavior of the so-called ``empirical structure function'', a statistic which resembles a sample moment of the process. We show and use the fact that the rate of growth of the empirical structure function is determined by the Hurst parameter and the tail index. We test the methods on simulated data and apply them to network traffic and solar flares data.
Izvorni jezik
Engleski
Znanstvena područja
Matematika
POVEZANOST RADA
Projekti:
235-2352818-1039 - Statistički aspekti problema procjene u nelinearnim parametarskim modelima (Benšić, Mirta, MZOS ) ( CroRIS)
Ustanove:
Sveučilište u Osijeku, Odjel za matematiku
Profili:
Danijel Grahovac
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- INSPEC
- MathSciNet
- Zentrallblatt für Mathematik/Mathematical Abstracts
- Journal Citation Reports/Science Edition
- Scopus
- Mathematical Reviews
- EBSCO