Bayesian statistics for fishery stock assessment and management: a synthesis

Detalhes bibliográficos
Autor(a) principal: Kinas, Paul Gerhard
Data de Publicação: 2007
Outros Autores: Andrade, Humber Agrelli
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FURG (RI FURG)
Texto Completo: http://repositorio.furg.br/handle/1/915
Resumo: Bayesian statistical analysis has become an important tool in modern fisheries sciences. We assert that this success is due to the ease in which uncertainty can be explicitly incorporated in inference and decision making. To appreciate the profound conceptual change implied by the switch from frequentist to Bayesian views, it is necessary to understand probability as a wider, more powerful concept: quantification of inductive logic. The advantages resulting for fisheries sciences are examined and illustrated with examples. Some alleged weaknesses of the Bayesian approach are questioned. The important ability and still under-explored potential of Bayesian decision analysis to keep facts and values apart, is also highlighted.
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spelling Bayesian statistics for fishery stock assessment and management: a synthesisEstatística Bayesiana em avaliação e manejo de estoques pesqueiros: uma sínteseUncertaintyPlausible reasoningPosterior probabilityDecision analysisPacific codIncertezaPlausibilidadeProbabilidade posterioriAnálise de decisãoBacalhau do PacíficoBayesian statistical analysis has become an important tool in modern fisheries sciences. We assert that this success is due to the ease in which uncertainty can be explicitly incorporated in inference and decision making. To appreciate the profound conceptual change implied by the switch from frequentist to Bayesian views, it is necessary to understand probability as a wider, more powerful concept: quantification of inductive logic. The advantages resulting for fisheries sciences are examined and illustrated with examples. Some alleged weaknesses of the Bayesian approach are questioned. The important ability and still under-explored potential of Bayesian decision analysis to keep facts and values apart, is also highlighted.A análise estatística Bayesiana tornou-se ferramenta importante na moderna ciência pesqueira. Nós propomos aqui que este sucesso se deve à simplicidade com que as incertezas podem ser explicitadas tanto em inferência quanto na tomada de decisão. Para perceber a profundidade da mudança conceitual envolvida na mudança do enfoque freqüentista ao Bayesiano, é necessário entender a sua concepção mais ampla e poderosa de probabilidade: quantificação de lógica indutiva. As vantagens que derivam disso para as ciências pesqueiras são examinadas e ilustradas com exemplos. Algumas alegadas fraquezas do enfoque Bayesiano são questionadas. A importante, porém ainda sub-explorada, habilidade da análise Bayesiana de decisão em distinguir os fatos científicos de valores e prioridades da sociedade é também destacada.2011-08-24T03:29:12Z2011-08-24T03:29:12Z2007info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfKINAS, Paul G. ; ANDRADE, Humber A. Bayesian statistics for fishery stock assessment and management: a synthesis. Pan-American Journal of Aquatic Sciences, v. 2, n. 2, p. 103-112, 2007. Disponível em: <http://www.panamjas.org/pdf_artigos/PANAMJAS_2%282%29_103-112.pdf> . Acesso em: 23 ago. 2011.http://repositorio.furg.br/handle/1/915engKinas, Paul GerhardAndrade, Humber Agrelliinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FURG (RI FURG)instname:Universidade Federal do Rio Grande (FURG)instacron:FURG2011-08-24T03:29:12Zoai:repositorio.furg.br:1/915Repositório InstitucionalPUBhttps://repositorio.furg.br/oai/request || http://200.19.254.174/oai/requestopendoar:2011-08-24T03:29:12Repositório Institucional da FURG (RI FURG) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv Bayesian statistics for fishery stock assessment and management: a synthesis
Estatística Bayesiana em avaliação e manejo de estoques pesqueiros: uma síntese
title Bayesian statistics for fishery stock assessment and management: a synthesis
spellingShingle Bayesian statistics for fishery stock assessment and management: a synthesis
Kinas, Paul Gerhard
Uncertainty
Plausible reasoning
Posterior probability
Decision analysis
Pacific cod
Incerteza
Plausibilidade
Probabilidade posteriori
Análise de decisão
Bacalhau do Pacífico
title_short Bayesian statistics for fishery stock assessment and management: a synthesis
title_full Bayesian statistics for fishery stock assessment and management: a synthesis
title_fullStr Bayesian statistics for fishery stock assessment and management: a synthesis
title_full_unstemmed Bayesian statistics for fishery stock assessment and management: a synthesis
title_sort Bayesian statistics for fishery stock assessment and management: a synthesis
author Kinas, Paul Gerhard
author_facet Kinas, Paul Gerhard
Andrade, Humber Agrelli
author_role author
author2 Andrade, Humber Agrelli
author2_role author
dc.contributor.author.fl_str_mv Kinas, Paul Gerhard
Andrade, Humber Agrelli
dc.subject.por.fl_str_mv Uncertainty
Plausible reasoning
Posterior probability
Decision analysis
Pacific cod
Incerteza
Plausibilidade
Probabilidade posteriori
Análise de decisão
Bacalhau do Pacífico
topic Uncertainty
Plausible reasoning
Posterior probability
Decision analysis
Pacific cod
Incerteza
Plausibilidade
Probabilidade posteriori
Análise de decisão
Bacalhau do Pacífico
description Bayesian statistical analysis has become an important tool in modern fisheries sciences. We assert that this success is due to the ease in which uncertainty can be explicitly incorporated in inference and decision making. To appreciate the profound conceptual change implied by the switch from frequentist to Bayesian views, it is necessary to understand probability as a wider, more powerful concept: quantification of inductive logic. The advantages resulting for fisheries sciences are examined and illustrated with examples. Some alleged weaknesses of the Bayesian approach are questioned. The important ability and still under-explored potential of Bayesian decision analysis to keep facts and values apart, is also highlighted.
publishDate 2007
dc.date.none.fl_str_mv 2007
2011-08-24T03:29:12Z
2011-08-24T03:29:12Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv KINAS, Paul G. ; ANDRADE, Humber A. Bayesian statistics for fishery stock assessment and management: a synthesis. Pan-American Journal of Aquatic Sciences, v. 2, n. 2, p. 103-112, 2007. Disponível em: <http://www.panamjas.org/pdf_artigos/PANAMJAS_2%282%29_103-112.pdf> . Acesso em: 23 ago. 2011.
http://repositorio.furg.br/handle/1/915
identifier_str_mv KINAS, Paul G. ; ANDRADE, Humber A. Bayesian statistics for fishery stock assessment and management: a synthesis. Pan-American Journal of Aquatic Sciences, v. 2, n. 2, p. 103-112, 2007. Disponível em: <http://www.panamjas.org/pdf_artigos/PANAMJAS_2%282%29_103-112.pdf> . Acesso em: 23 ago. 2011.
url http://repositorio.furg.br/handle/1/915
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da FURG (RI FURG)
instname:Universidade Federal do Rio Grande (FURG)
instacron:FURG
instname_str Universidade Federal do Rio Grande (FURG)
instacron_str FURG
institution FURG
reponame_str Repositório Institucional da FURG (RI FURG)
collection Repositório Institucional da FURG (RI FURG)
repository.name.fl_str_mv Repositório Institucional da FURG (RI FURG) - Universidade Federal do Rio Grande (FURG)
repository.mail.fl_str_mv
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