Počet záznamů: 1
Fractal approach towards power-law coherency to measure cross-correlations between time series
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SYSNO ASEP 0473066 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Fractal approach towards power-law coherency to measure cross-correlations between time series Tvůrce(i) Krištoufek, Ladislav (UTIA-B) RID, ORCID Celkový počet autorů 1 Zdroj.dok. Communications in Nonlinear Science and Numerical Simulation. - : Elsevier - ISSN 1007-5704
Roč. 50, č. 1 (2017), s. 193-200Poč.str. 8 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. NL - Nizozemsko Klíč. slova power-law coherency ; power-law cross-correlations ; correlations Vědní obor RIV AH - Ekonomie Obor OECD Applied Economics, Econometrics CEP GP14-11402P GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 UT WOS 000399513200015 EID SCOPUS 85014923760 DOI 10.1016/j.cnsns.2017.02.018 Anotace We focus on power-law coherency as an alternative approach towards studying power law cross-correlations between simultaneously recorded time series. To be able to study empirical data, we introduce three estimators of the power-law coherency parameter Hp based on popular techniques usually utilized for studying power-law cross-correlations detrended cross-correlation analysis (DCCA), detrending moving-average cross-correlation analysis (DMCA) and height cross-correlation analysis (HXA). In the finite sample properties study, we focus on the bias, variance and mean squared error of the estimators. We find that the DMCA-based method is the safest choice among the three. The HXA method is reasonable for long time series with at least 104 observations, which can be easily attainable in some disciplines but problematic in others. The DCCA-based method does not provide favorable properties which even deteriorate with an increasing time series length. The paper opens a new venue towards studying cross-correlations between time series. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2018
Počet záznamů: 1