Fitting power-laws in empirical data with estimators that work for all exponents

Most standard methods based on maximum likelihood (ML) estimates of power-law exponents can only be reliably used to identify exponents smaller than minus one. The argument that power laws are otherwise not normalizable, depends on the underlying sample space the data is drawn from, and is true only...

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Detalles Bibliográficos
Autores principales: Hanel, Rudolf, Corominas-Murtra, Bernat, Liu, Bo, Thurner, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330461/
https://www.ncbi.nlm.nih.gov/pubmed/28245249
http://dx.doi.org/10.1371/journal.pone.0170920

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5330461/
https://www.ncbi.nlm.nih.gov/pubmed/28245249
http://dx.doi.org/10.1371/journal.pone.0170920

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