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Discriminating between Light- and Heavy-Tailed Distributions with Limit Theorem
In this paper we propose an algorithm to distinguish between light- and heavy-tailed probability laws underlying random datasets. The idea of the algorithm, which is visual and easy to implement, is to check whether the underlying law belongs to the domain of attraction of the Gaussian or non-Gaussi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4689533/ https://www.ncbi.nlm.nih.gov/pubmed/26698863 http://dx.doi.org/10.1371/journal.pone.0145604 |