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Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this paper, we develop a new method to measure the nonlinear interactions between nonstationary time series based on the detrended cross-correlation coefficient analysis.
We describe how a nonlinear interaction may be obtained by eliminating the influence of other variables on two simultaneous time series.
By applying two artificially generated signals, we show that the new method is working reliably for determining the cross-correlation behavior of two signals.
We also illustrate the application of this method in finance and aeroengine systems.
These analyses suggest that the proposed measure, derived from the detrended cross-correlation coefficient analysis, may be used to remove the influence of other variables on the cross-correlation between two simultaneous time series.
American Psychological Association (APA)
Dong, Keqiang& Gao, Xiaojie. 2020. Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143752
Modern Language Association (MLA)
Dong, Keqiang& Gao, Xiaojie. Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1143752
American Medical Association (AMA)
Dong, Keqiang& Gao, Xiaojie. Higher-Order Multifractal Detrended Partial Cross-Correlation Analysis for the Correlation Estimator. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143752
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143752