A new tool to derive simultaneously exponent and extremes of power-law distributions
S. Pezzuto, A. Coletta, R. S. Klessen, E. Schisano, M. Benedettini, D., Elia, S. Molinari, J. D. Soler, A. Traficante

TL;DR
This paper introduces a novel tool for simultaneously estimating the exponent and the data range of power-law distributions, improving accuracy over traditional methods, with applications in astrophysics and gamma-ray spectra analysis.
Contribution
The paper presents a new non-linear least-squares fitting tool that derives the power-law exponent and data bounds simultaneously, outperforming existing maximum likelihood estimators.
Findings
The tool reliably estimates parameters with varying sample sizes.
Application to astrophysical data yields specific power-law slopes.
Method performs well compared to traditional estimators.
Abstract
Many experimental quantities show a power-law distribution . In astrophysics, examples are: size distribution of dust grains or luminosity function of galaxies. Such distributions are characterized by the exponent and by the extremes where the distribution extends. There are no mathematical tools that derive the three unknowns at the same time. In general, one estimates a set of corresponding to different guesses of . Then, the best set of values describing the observed data is selected a posteriori. In this paper, we present a tool that finds contextually the three parameters based on simple assumptions on how the observed values populate the unknown range between and for a given . Our tool, freely downloadable, finds the best values through…
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Taxonomy
TopicsAstrophysics and Cosmic Phenomena · Scientific Research and Discoveries · Earthquake Detection and Analysis
