A cross horizontal visibility graph algorithm to explore associations between two time series

Jin-Long Liu, Zu-Guo Yu and Yu Zhou

Chaos, Solitons & Fractals, 2024, vol. 181, issue C

Abstract: We propose a cross horizontal visibility graph (CHVG) algorithm to explore associations between two time series. As a natural extension of the classic horizontal visibility graph algorithm, the proposed CHVG algorithm can preserve merits of the classic algorithm in construction and implementation. To verify the effectiveness of the CHVG algorithm, we design numerical simulations by generating paired time series with three experimental settings: namely independent autocorrelated series, cross-correlated series with no autocorrelation, and cross-correlated series with autocorrelation. The corresponding CHVGs can be accordingly constructed from these generated pairs of time series. Our results show that the degree distributions of all constructed CHVGs follow exponential distributions P(k)∼e−λk. Furthermore, the estimated exponent λ can reflect associations between two time series, mainly due to their cross correlation but also relevant to autocorrelation of individual series. We demonstrate the applicability of the proposed CHVG algorithm by investigating associations between the air pollutant PM10 and the meteorological factors (i.e., temperature and relative humidity) at two stations in Hong Kong. Our algorithm can effectively capture the negative cross correlations between all combinations pairing the pollutant PM10 and one of the two meteorological factors at both stations, which sheds light on understanding, modeling, and prediction of the air pollution process.

Keywords: Horizontal visibility graph; Cross correlation; Two time series (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077924002261
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002261

DOI: 10.1016/j.chaos.2024.114674

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().