A review of power laws in real life phenomena

Detalhes bibliográficos
Autor(a) principal: Pinto, Carla M.A.
Data de Publicação: 2012
Outros Autores: Lopes, António M., Machado, J.A.Tenreiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/3814
Resumo: Power law distributions, also known as heavy tail distributions, model distinct real life phenomena in the areas of biology, demography, computer science, economics, information theory, language, and astronomy, amongst others. In this paper, it is presented a review of the literature having in mind applications and possible explanations for the use of power laws in real phenomena. We also unravel some controversies around power laws.
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spelling A review of power laws in real life phenomenaPower law behaviorParento lawZipf lawHeavy tail distributionsApplicationsPower law distributions, also known as heavy tail distributions, model distinct real life phenomena in the areas of biology, demography, computer science, economics, information theory, language, and astronomy, amongst others. In this paper, it is presented a review of the literature having in mind applications and possible explanations for the use of power laws in real phenomena. We also unravel some controversies around power laws.ElsevierRepositório Científico do Instituto Politécnico do PortoPinto, Carla M.A.Lopes, António M.Machado, J.A.Tenreiro2014-02-07T15:30:10Z20122012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/3814eng1007-570410.1016/j.cnsns.2012.01.013info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:43:38Zoai:recipp.ipp.pt:10400.22/3814Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:24:46.640411Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A review of power laws in real life phenomena
title A review of power laws in real life phenomena
spellingShingle A review of power laws in real life phenomena
Pinto, Carla M.A.
Power law behavior
Parento law
Zipf law
Heavy tail distributions
Applications
title_short A review of power laws in real life phenomena
title_full A review of power laws in real life phenomena
title_fullStr A review of power laws in real life phenomena
title_full_unstemmed A review of power laws in real life phenomena
title_sort A review of power laws in real life phenomena
author Pinto, Carla M.A.
author_facet Pinto, Carla M.A.
Lopes, António M.
Machado, J.A.Tenreiro
author_role author
author2 Lopes, António M.
Machado, J.A.Tenreiro
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Pinto, Carla M.A.
Lopes, António M.
Machado, J.A.Tenreiro
dc.subject.por.fl_str_mv Power law behavior
Parento law
Zipf law
Heavy tail distributions
Applications
topic Power law behavior
Parento law
Zipf law
Heavy tail distributions
Applications
description Power law distributions, also known as heavy tail distributions, model distinct real life phenomena in the areas of biology, demography, computer science, economics, information theory, language, and astronomy, amongst others. In this paper, it is presented a review of the literature having in mind applications and possible explanations for the use of power laws in real phenomena. We also unravel some controversies around power laws.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01T00:00:00Z
2014-02-07T15:30:10Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/3814
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1007-5704
10.1016/j.cnsns.2012.01.013
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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