Fractal analyses for `short' time series: A re-assessment of classical methods

DOI10.1016/J.JMP.2006.07.004zbMath1105.62085OpenAlexW2081438405WikidataQ98839669 ScholiaQ98839669MaRDI QIDQ867994

Sofiane Ramdani, Grégory Ninot, Loïc Lemoine, Kjerstin Torre, Marina Fortes, Didier Delignieres

Publication date: 19 February 2007

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmp.2006.07.004

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Time series analysis of dynamical systems (37M10) Fractals (28A80)

Related Items (11)

Variance-mediated multifractal analysis of group participation in chasing a single dangerous prey ⋮ Correlation properties of (discrete) fractional Gaussian noise and fractional Brownian motion ⋮ Wavelet Fisher's information measure of \(1/f^\alpha\) signals ⋮ Wavelet \(q\)-Fisher information for scaling signal analysis ⋮ The influence of power law distributions on long-range trial dependency of response times ⋮ Distinguishing stationary/nonstationary scaling processes using wavelet Tsallis \(q\)-entropies ⋮ THE ROBUST FRACTAL ANALYSIS OF TIME SERIES: CONCERNING SIGNAL CLASS AND DATA LENGTH ⋮ Machine learning techniques applied to the determination of osteoporosis incidence in post-menopausal women ⋮ Probabilistic analysis of recurrence plots generated by fractional Gaussian noise ⋮ Biases in the simulation and analysis of fractal processes ⋮ Unraveling the finding of \(1/f ^{\beta }\) noise in self-paced and synchronized tapping: a unifying mechanistic model

Cites Work

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• Fractal modeling of human isochronous serial interval production
• A comparsion of estimators for \(1/f\) noise
• Tests for Hurst effect
• Maximum likelihood estimation of the parameters of discrete fractionally differenced Gaussian noise process
• Fractional Brownian Motions, Fractional Noises and Applications

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