Fitting long-tailed distribution to empirical data-Reference-Cited by-同舟云学术

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Fitting long-tailed distribution to empirical data

Published:2017-07-28 Issue:24 Volume:29 Page:e4223
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat: Pract Exper

Author:

Gil Joseph Yossi¹,Monni Cristina²^ORCID

Affiliation:

1. Department of Computer Science; The Technion-Israel Institute of Technology; Haifa 32000 Israel

2. Università della Svizzera Italiana; 6900 Lugano Switzerland.

Funder

Israel Science Foundation

Regione Autonoma della Sardegna (RAS)

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference32 articles.

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2. Some statistics of evolution and geographical distribution in plants and animals, and their significance;Willis;Nature,1922

3. The pareto, zipf and other power laws;Reed;Econ Lett,2001

4. A replicated quantitative analysis of fault distributions in complex software systems;Andersson;IEEE Trans Softw Eng,2007

5. Gadepally V Kepner J Using a power law distribution to describe big data 2015 Waltham, MA, USA.

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