a fractal approach to dynamic inference and distribution analysis
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2013
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Abstract
Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution’s shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods.
| Reference Key |
rooij2013frontiersa
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|---|---|
| Authors | ;Marieke M.J.W. van Rooij;Bertha eNash;Srinivasan eRajaraman;John G. Holden |
| Journal | Journal of clinical and experimental dentistry |
| Year | 2013 |
| DOI |
10.3389/fphys.2013.00001
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| URL | |
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