ArticleComputational and mathematical methods in medicine2019
Biases in the Simulation and Analysis of Fractal Processes.
Article in Computational and mathematical methods in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Subtle to significant: Enhancing heaviness perception with stochastic resonance.Journal of experimental psychology. Human perception and performance · 2026Article
- Precision in Brief: The Bayesian Hurst-Kolmogorov Method for the Assessment of Long-Range Temporal Correlations in Short Behavioral Time Series.Entropy (Basel, Switzerland) · 2025Article
- Validity of Linear and Nonlinear Measures of Gait Variability to Characterize Aging Gait with a Single Lower Back Accelerometer.Sensors (Basel, Switzerland) · 2024Article
- Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets.Entropy (Basel, Switzerland) · 2023Article
- Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences.ArXiv · 2023Article
- A guide to Whittle maximum likelihood estimator in MATLAB.Frontiers in network physiology · 2023Article
- Self-potential time series reveal emergent behavior in soil organic matter dynamics.Scientific reports · 2022Article
- Temperature and precipitation in the US states: long memory, persistence, and time trend.Theoretical and applied climatology · 2022Article
- Fast Hand Movements Unveil Multifractal Roots of Adaptation in the Visuomotor Cognitive System.Frontiers in physiology · 2021Article
- Multifractal Dynamics in Executive Control When Adapting to Concurrent Motor Tasks.Frontiers in physiology · 2021Article
- Fractal Analysis of Human Gait Variability via Stride Interval Time Series.Frontiers in physiology · 2020Article
- Immersive Virtual Reality to Restore Natural Long-Range Autocorrelations in Parkinson's Disease Patients' Gait During Treadmill Walking.Frontiers in physiology · 2020Article
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Authors and funding
4 authors.
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Abstract
Fractal processes have recently received a growing interest, especially in the domain of rehabilitation. More precisely, the evolution of fractality with aging and disease, suggesting a loss of complexity, has inspired a number of studies that tried, for example, to entrain patients with fractal rhythms. This kind of study requires relevant methods for generating fractal signals and for assessing the fractality of the series produced by participants. In the present work, we engaged a cross validation of three methods of generation and three methods of analysis. We generated exact fractal series with the Davies-Harte (DH) algorithm, the spectral synthesis method (SSM), and the ARFIMA simulation method. The series were analyzed by detrended fluctuation analysis (DFA), power spectral density (PSD) method, and ARFIMA modeling. Results show that some methods of generation present systematic biases: DH presented a strong bias toward white noise in fBm series close to the 1/
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