Four methods to distinguish between fractal dimensions in time series through 
recurrence quantification analysis

Tomashin, Alon; Leonardi, Giuseppe; Wallot, Sebastian

doi:10.3390/e24091314

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Four methods to distinguish between fractal dimensions in time series through recurrence quantification analysis

MPS-Authors

/persons/resource/persons187755

Wallot, Sebastian
Department of Language and Literature, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Institute for Sustainability Education and Psychology, Leuphana University of Lüneburg;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

lit-22-wal-04-four.pdf
(Publisher version), 6MB

Supplementary Material (public)

There is no public supplementary material available

Citation

Tomashin, A., Leonardi, G., & Wallot, S. (2022). Four methods to distinguish between fractal dimensions in time series through recurrence quantification analysis. Entropy, 24(9). doi:10.3390/e24091314.

Cite as: https://hdl.handle.net/21.11116/0000-000B-A840-F

Abstract

Fractal properties in time series of human behavior and physiology are quite ubiquitous, and several methods to capture such properties have been proposed in the past decades. Fractal properties are marked by similarities in statistical characteristics over time and space, and it has been suggested that such properties can be well-captured through recurrence quantification analysis. However, no methods to capture fractal fluctuations by means of recurrence-based methods have been developed yet. The present paper takes this suggestion as a point of departure to propose and test several approaches to quantifying fractal fluctuations in synthetic and empirical time-series data using recurrence-based analysis. We show that such measures can be extracted based on recurrence plots, and contrast the different approaches in terms of their accuracy and range of applicability.