CYCLOCOPULA TECHNIQUE TO STUDY THE RELATIONSHIP BETWEEN TWO CYCLOSTATIONARY TIME SERIES WITH FRACTIONAL BROWNIAN MOTION ERRORS

Mohammad Reza Mahmoudi and Amir Mosavi
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Mohammad Reza Mahmoudi: Department of Statistics, Faculty of Science, Fasa University, Fasa, Fars, Iran
Amir Mosavi: ��Faculty of Civil Engineering, Technische, Universität Dresden, 01069 Dresden, Germany‡Institute of Software Design and Development, Óbuda University, 1034 Budapest, Hungary§Institute of Information Society, University of Public Service, 1083 Budapest, Hungary¶Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, Bratislava, Slovakia

FRACTALS (fractals), 2022, vol. 30, issue 05, 1-9

Abstract: Detection of relationship between two time series is so important in different scientific fields. Most common techniques are usually sensitive to stationarity or normality assumptions. In this research, a new copula-based method (cyclocopula) is introduced to detect the relationship between two cylostationary time series with fractional Brownian motion (fBm) errors. The performance of the proposed method is studied by employing numerous simulated datasets. The applicability of the introduced approach is also investigated in real-world problems. The numerical and applied studies verify the performance of the introduced technique.

Keywords: Time Series; Fractional Brownian Motion; Cyclostationary; Copula; Regression; Time Series Analysis; Time Series Analysis; Time Series Forecasting (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0218348X22401375

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