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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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| Gepubliceerd in: | PLoS One |
|---|---|
| Hoofdauteurs: | , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Public Library of Science
2017
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5330461/ https://ncbi.nlm.nih.gov/pubmed/28245249 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0170920 |
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