most citedBetter than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences

6 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

nlin.AO2024

Multifractal-spectral features enhance classification of anomalous diffusion

Henrik Seckler, Ralf Metzler, Damian G. Kelty-Stephen +1

Anomalous diffusion processes pose a unique challenge in classification and characterization. Previously (Mangalam et al., 2023, Physical Review Research 5, 023144), we established…

nlin.AO2024

Multifractal emergent processes: Multiplicative interactions override nonlinear component properties

Madhur Mangalam, Damian G Kelty-Stephen

Among the statistical models employed to approximate nonlinear interactions in biological and psychological processes, one prominent framework is that of cascades. Despite decades…

q-bio.QM2023

Reproducible biomarkers: Leveraging nonlinear descriptors in the face of non-ergodicity

Madhur Mangalam, Arash Sadri, Junichiro Hayano +3

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health state…

q-bio.QM20231 cited

Ergodic characterization of non-ergodic anomalous diffusion processes

Madhur Mangalam, Ralf Metzler, Damian G. Kelty-Stephen

Canonical characterization techniques that rely upon mean squared displacement () break down for non-ergodic processes, making it challenging to characterize anomalou…

q-bio.QM20231 cited

Optimizing a Bayesian method for estimating the Hurst exponent in behavioral sciences

Madhur Mangalam, Taylor Wilson, Joel Sommerfeld +1

The Bayesian Hurst-Kolmogorov (HK) method estimates the Hurst exponent of a time series more accurately than the age-old detrended fluctuation analysis (DFA), especially when the t…

q-bio.QM20236 cited

Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences

Aaron D. Likens, Madhur Mangalam, Aaron Y. Wong +2

Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of…