Multifractal analysis of coronavirus sequences

Correia, J.P.; Lima, Maxsuel Marcos Fernandes de; Silva, R.; Anselmo, D.H.A.L.; Vasconcelos, M.S.; Viswanathan, G. M.

doi:10.1016/j.chaos.2023.113843

Chaos, Solitons & Fractals

2023

DOI: 10.1016/j.chaos.2023.113843

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Multifractal analysis of coronavirus sequences

J.P. Correia

Maxsuel Marcos Fernandes de Lima

R. Silva

et al.

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2024

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Cited by 2 publications

References 37 publications

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Crossover detection based on variances of slope differences for multi-fractal detrended fluctuation analysis (MF-DFA)

Moreno-Pulido,

de la Torre,

Ruiz

et al. 2024

Nonlinear Dyn

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Multi-fractal detrended fluctuation analysis (MF-DFA) describes long-range correlations across scales in time series in terms of the linear fittings of the fluctuation functions $$F_q(s)$$ F q ( s ) for every moment q considered. It is relatively common to find time scales, also called crossovers, where different linearities are found at each side of the $$F_q(s)$$ F q ( s ) , leading to different (multi-)fractal properties. Generally, crossovers are manually identified by experts, subject then to their skills and possible bias. In this work, a novel methodology based on the variances of the slope differences (CDV-A) is proposed to automatically detect crossovers. A set of synthetic fluctuation functions with different mono-fractal and multi-fractal features, different noise levels and known crossovers is generated to assess the CDV-A. Moreover, the proposed methodology is also applied to state of the art fluctuation functions in order to compare the proposed manual and automated locations of the crossovers. Results show the proposed methodology is highly accurate, specially in low noise synthetic fluctuation functions and in most of the real cases.

show abstract

Crossover detection based on variances of slope differences for multi-fractal detrended fluctuation analysis (MF-DFA)

Moreno-Pulido,

de la Torre,

Ruiz

et al. 2024

Nonlinear Dyn

View full text Add to dashboard Cite

show abstract

Elite women's soccer match demand can be described using complexity-based analyses and multifractals

Babault,

Rodot,

Cometti

et al. 2024

Chaos, Solitons & Fractals

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Multifractal analysis of coronavirus sequences

Cited by 2 publications

References 37 publications

Crossover detection based on variances of slope differences for multi-fractal detrended fluctuation analysis (MF-DFA)

Crossover detection based on variances of slope differences for multi-fractal detrended fluctuation analysis (MF-DFA)

Elite women's soccer match demand can be described using complexity-based analyses and multifractals

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