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Fitting Heavy Tailed Distributions: The poweRlaw Package


  • Gillespie, Colin S.


Over the last few years, the power law distribution has been used as the data generating mechanism in many disparate fields. However, at times the techniques used to fit the power law distribution have been inappropriate. This paper describes the poweRlaw R package, which makes fitting power laws and other heavy-tailed distributions straightforward. This package contains R functions for fitting, comparing and visualizing heavy tailed distributions. Overall, it provides a principled approach to power law fitting.

Suggested Citation

  • Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
  • Handle: RePEc:jss:jstsof:v:064:i02

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    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Johannes Van Der Pol, 2015. "Structural dynamics of the French aerospace sector: A network analysis," Working Papers hal-01284993, HAL.
    2. Weili Chen & Jun Wu & Zibin Zheng & Chuan Chen & Yuren Zhou, 2019. "Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network," Papers 1902.01941,
    3. repec:eee:phsmap:v:523:y:2019:i:c:p:858-875 is not listed on IDEAS
    4. Cura, Robin & Cottineau, Clémentine & Swerts, Elfie & Ignazzi, Cosmo Antonio & Bretagnolle, Anne & Vacchiani-Marcuzzo, Celine & Pumain, Denise, 2017. "The Old and the New: Qualifying City Systems in the World with Classical Models and New Data," SocArXiv pbzn6, Center for Open Science.
    5. Thelwall, Mike, 2016. "Are there too many uncited articles? Zero inflated variants of the discretised lognormal and hooked power law distributions," Journal of Informetrics, Elsevier, vol. 10(2), pages 622-633.
    6. repec:wsi:acsxxx:v:21:y:2018:i:08:n:s0219525918500194 is not listed on IDEAS
    7. Thelwall, Mike, 2016. "Are the discretised lognormal and hooked power law distributions plausible for citation data?," Journal of Informetrics, Elsevier, vol. 10(2), pages 454-470.
    8. Kei Katahira & Yu Chen, 2019. "Heterogeneous wealth distribution, round-trip trading and the emergence of volatility clustering in Speculation Game," Papers 1909.03185,
    9. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040,
    10. Thelwall, Mike, 2016. "Citation count distributions for large monodisciplinary journals," Journal of Informetrics, Elsevier, vol. 10(3), pages 863-874.
    11. repec:eee:phsmap:v:490:y:2018:i:c:p:1125-1137 is not listed on IDEAS
    12. repec:eee:phsmap:v:508:y:2018:i:c:p:501-505 is not listed on IDEAS
    13. da Gama Batista, João & Massaro, Domenico & Bouchaud, Jean-Philippe & Challet, Damien & Hommes, Cars, 2017. "Do investors trade too much? A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 18-34.
    14. Damien Challet & R'emy Chicheportiche & Mehdi Lallouache & Serge Kassibrakis, 2016. "Statistically validated lead-lag networks and inventory prediction in the foreign exchange market," Papers 1609.04640,, revised Jul 2018.
    15. repec:eee:phsmap:v:484:y:2017:i:c:p:506-515 is not listed on IDEAS
    16. Thelwall, Mike, 2016. "The precision of the arithmetic mean, geometric mean and percentiles for citation data: An experimental simulation modelling approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 110-123.
    17. A. Q. Barbi & G. A. Prataviera, 2017. "Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees," Papers 1711.06185,, revised May 2019.
    18. repec:eee:phsmap:v:523:y:2019:i:c:p:876-885 is not listed on IDEAS
    19. Mike Thelwall, 2016. "Interpreting correlations between citation counts and other indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 337-347, July.
    20. Antonio Zinilli, 2016. "Competitive project funding and dynamic complex networks: evidence from Projects of National Interest (PRIN)," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 633-652, August.

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