73 citations · 131 across the 13 of their papers we have counts for
13 papers
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…
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…
Multifractal nonlinearity as a robust estimator of multiplicative cascade dynamics
Madhur Mangalam, Aaron D Likens, Damian G Kelty-Stephen
Multifractal formalisms provide an apt framework to study random cascades in which multifractal spectrum width fluctuates depending on the number of estimable power-law relati…
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…
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…
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…
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…
In search for an alternative to the computer metaphor of the mind and brain
Damian G. Kelty-Stephen, Paul E. Cisek, Benjamin De Bari +8
The brain-as-computer metaphor has anchored the professed computational nature of the mind, wresting it down from the intangible logic of Platonic philosophy to a material basis fo…
Turing's cascade instability supports the coordination of the mind, brain, and behavior
Damian G. Kelty-Stephen, Madhur Mangalam
Turing inspired a computer metaphor of the mind and brain that has been handy and has spawned decades of empirical investigation, but he did much more and offered behavioral and co…
Fractal and multifractal descriptors restore ergodicity broken by non-Gaussianity in time series
Damian G. Kelty-Stephen, Madhur Mangalam
Ergodicity breaking is a challenge for biological and psychological sciences. Ergodicity is a necessary condition for linear causal modeling. Long-range correlations and non-Gaussi…
Ergodic descriptors of nonergodic stochastic processes
Madhur Mangalam, Damian G. Kelty-Stephen
The stochastic processes underlying the growth and stability of biological and psychological systems reveal themselves when far from equilibrium. Far from equilibrium, nonergodicit…
Multifractal test for nonlinear changes in time series
Damian G. Kelty-Stephen, Elizabeth Lane, Madhur Mangalam
The creativity and emergence of biological and psychological behavior are nonlinear. However, that does not necessarily mean only that the measurements of the behaviors are curvili…
Point estimates, Simpson's paradox and nonergodicity in biological sciences
Madhur Mangalam, Damian G. Kelty-Stephen
Modern biomedical, behavioral and psychological inference about cause-effect relationships respects an ergodic assumption, that is, that mean response of representative samples all…