Cyclocopula Technique to Study the Relationship Between Two Cyclostationary Time Series with Fractional Brownian Motion Errors
Methodology
2022-06-17 v1 Machine Learning
Abstract
Detection of the relationship between two time series is so important in environmental and hydrological studies. Several parametric and non-parametric approaches can be applied to detect relationships. These techniques are usually sensitive to stationarity assumptions. In this research, a new copula-based method is introduced to detect the relationship between two cylostationary time series with fractional Brownian motion (fBm) errors. The numerical studies verify the performance of the introduced approach.
Keywords
Cite
@article{arxiv.2206.07976,
title = {Cyclocopula Technique to Study the Relationship Between Two Cyclostationary Time Series with Fractional Brownian Motion Errors},
author = {Mohammadreza Mahmoudi and Amir Mosavi},
journal= {arXiv preprint arXiv:2206.07976},
year = {2022}
}
Comments
16 pages, t tables