Inferring probability densities from expert opinion

When experts are asked to assess a situation, they often express their opinions providing estimates of the probability of observing the occurrence of a random variable in given intervals, sometimes up to a range of values, rather than simply providing point estimates. The problem we face is how to t...

Full description

Autores:
Gzyl, Henryk
ter Horst, Enrique
Molina, Germán
Tipo de recurso:
Article of investigation
Fecha de publicación:
2017
Institución:
Colegio de Estudios Superiores de Administración
Repositorio:
Repositorio CESA
Idioma:
eng
OAI Identifier:
oai:repository.cesa.edu.co:10726/5102
Acceso en línea:
http://hdl.handle.net/10726/5102
https://doi.org/10.1016/j.apm.2016.11.006
Palabra clave:
Maximum entropy method
Maximum entropy with errors in the data
Probability elicitation with uncertainty
Rights
openAccess
License
Abierto (Texto Completo)
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network_acronym_str CESA2
network_name_str Repositorio CESA
repository_id_str
spelling Gzyl, Henryk169316a4-12f8-4afb-8213-5a74cbb8f41a600ter Horst, Enriquebb497a43-c019-48d2-8bff-b5b9172cf707600Molina, Germán1fa4e4bc-5890-49a2-aa16-7f5220145ef8600ter Horst, Enrique [0000-0001-5153-1475]Molina, Germán [0000-0003-4693-6907]Gzyl, Henryk [6701665186]ter Horst, Enrique [25655619900]Molina, Germán [15728099800]2023-06-21T22:23:08Z2023-06-21T22:23:08Z2017-030307-904Xhttp://hdl.handle.net/10726/5102instname:Colegio de Estudios Superiores de Administración – CESAreponame:Biblioteca Digital – CESArepourl:https://repository.cesa.edu.co/1872-8480https://doi.org/10.1016/j.apm.2016.11.006engElsevier Inc.Inferring probability densities from expert opinionarticlehttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_71e4c1898caa6e32info:eu-repo/semantics/openAccessAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2When experts are asked to assess a situation, they often express their opinions providing estimates of the probability of observing the occurrence of a random variable in given intervals, sometimes up to a range of values, rather than simply providing point estimates. The problem we face is how to translate that expert opinion into probability distributions. We examine a novel way of solving that problem by making use of the maximum entropy method in the data to deal with expert opinions expressed with or without uncertainty bands. Our method allows us to unveil underlying probability distributions driving expert opinions expressed with and without uncertainty.https://orcid.org/0000-0001-5153-1475https://orcid.org/0000-0003-4693-6907https://www.scopus.com/authid/detail.uri?authorId=6701665186https://www.scopus.com/authid/detail.uri?authorId=25655619900https://www.scopus.com/authid/detail.uri?authorId=1572809980043306320Applied Mathematical ModellingMaximum entropy methodMaximum entropy with errors in the dataProbability elicitation with uncertainty10726/5102oai:repository.cesa.edu.co:10726/51022023-09-30 13:00:01.534metadata only accessBiblioteca Digital - CESAbiblioteca@cesa.edu.co
dc.title.eng.fl_str_mv Inferring probability densities from expert opinion
title Inferring probability densities from expert opinion
spellingShingle Inferring probability densities from expert opinion
Maximum entropy method
Maximum entropy with errors in the data
Probability elicitation with uncertainty
title_short Inferring probability densities from expert opinion
title_full Inferring probability densities from expert opinion
title_fullStr Inferring probability densities from expert opinion
title_full_unstemmed Inferring probability densities from expert opinion
title_sort Inferring probability densities from expert opinion
dc.creator.fl_str_mv Gzyl, Henryk
ter Horst, Enrique
Molina, Germán
dc.contributor.author.spa.fl_str_mv Gzyl, Henryk
ter Horst, Enrique
Molina, Germán
dc.contributor.orcid.none.fl_str_mv ter Horst, Enrique [0000-0001-5153-1475]
Molina, Germán [0000-0003-4693-6907]
dc.contributor.scopus.none.fl_str_mv Gzyl, Henryk [6701665186]
ter Horst, Enrique [25655619900]
Molina, Germán [15728099800]
dc.subject.proposal.none.fl_str_mv Maximum entropy method
Maximum entropy with errors in the data
Probability elicitation with uncertainty
topic Maximum entropy method
Maximum entropy with errors in the data
Probability elicitation with uncertainty
description When experts are asked to assess a situation, they often express their opinions providing estimates of the probability of observing the occurrence of a random variable in given intervals, sometimes up to a range of values, rather than simply providing point estimates. The problem we face is how to translate that expert opinion into probability distributions. We examine a novel way of solving that problem by making use of the maximum entropy method in the data to deal with expert opinions expressed with or without uncertainty bands. Our method allows us to unveil underlying probability distributions driving expert opinions expressed with and without uncertainty.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017-03
dc.date.accessioned.none.fl_str_mv 2023-06-21T22:23:08Z
dc.date.available.none.fl_str_mv 2023-06-21T22:23:08Z
dc.type.none.fl_str_mv article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coar.none.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.none.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.coarversion.none.fl_str_mv http://purl.org/coar/version/c_71e4c1898caa6e32
format http://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.issn.none.fl_str_mv 0307-904X
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10726/5102
dc.identifier.instname.none.fl_str_mv instname:Colegio de Estudios Superiores de Administración – CESA
dc.identifier.reponame.none.fl_str_mv reponame:Biblioteca Digital – CESA
dc.identifier.repourl.none.fl_str_mv repourl:https://repository.cesa.edu.co/
dc.identifier.eissn.none.fl_str_mv 1872-8480
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.apm.2016.11.006
identifier_str_mv 0307-904X
instname:Colegio de Estudios Superiores de Administración – CESA
reponame:Biblioteca Digital – CESA
repourl:https://repository.cesa.edu.co/
1872-8480
url http://hdl.handle.net/10726/5102
https://doi.org/10.1016/j.apm.2016.11.006
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.citationvolume.none.fl_str_mv 43
dc.relation.citationstartpage.none.fl_str_mv 306
dc.relation.citationendpage.none.fl_str_mv 320
dc.relation.ispartofjournal.none.fl_str_mv Applied Mathematical Modelling
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.local.none.fl_str_mv Abierto (Texto Completo)
dc.rights.coar.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.publisher.none.fl_str_mv Elsevier Inc.
publisher.none.fl_str_mv Elsevier Inc.
institution Colegio de Estudios Superiores de Administración
repository.name.fl_str_mv Biblioteca Digital - CESA
repository.mail.fl_str_mv biblioteca@cesa.edu.co
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