\textit{Independent approximates} enable closed-form estimation of heavy-tailed distributions

DOI10.1016/j.physa.2022.127574zbMath1489.62076arXiv2012.11026OpenAlexW3114090128MaRDI QIDQ2145030

Kenric P. Nelson

Publication date: 17 June 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2012.11026

zbMATH Keywords

heavy-tailed distributionsstatistical estimationcomplex adaptive systems

Mathematics Subject Classification ID

Point estimation (62F10)

Uses Software

• GitHub
• plfit

Cites Work

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• Power-Law Distributions in Empirical Data
• Multivariate T-Distributions and Their Applications
• Extensive Numerical Results for Integrable Case of Standard Map
• Cramer-Rao Lower Bound and Information Geometry
• Estimating Heavy-Tail Exponents Through Max Self–Similarity
• Heavy-Tail Phenomena

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