Estimating utility functions using generalized maximum entropy

Detalhes bibliográficos
Autor(a) principal: Pires, Cesaltina
Data de Publicação: 2013
Outros Autores: Dionísio, Andreia, Coelho, Luís
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/8946
https://doi.org/10.1080/02664763.2012.740625
Resumo: This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.
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spelling Estimating utility functions using generalized maximum entropygeneralized maximum entropyutility elicitationMorgenstern utilitymaximum entropy principleThis paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.Taylor and Francic2013-10-30T11:43:42Z2013-10-302013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/8946http://hdl.handle.net/10174/8946https://doi.org/10.1080/02664763.2012.740625engPires, C., A. Dionísio, L. Coelho (2013), "Estimating utility functions using GME", Journal of Applied Statistics, 40(1), 221-234.Departamento de Gestãocpires@uevora.ptandreia@uevora.ptlcoelho@uevora.pt637Pires, CesaltinaDionísio, AndreiaCoelho, Luísinfo: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:RCAAP2024-01-03T18:50:30Zoai:dspace.uevora.pt:10174/8946Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:03:07.910018Repositório 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 Estimating utility functions using generalized maximum entropy
title Estimating utility functions using generalized maximum entropy
spellingShingle Estimating utility functions using generalized maximum entropy
Pires, Cesaltina
generalized maximum entropy
utility elicitation
Morgenstern utility
maximum entropy principle
title_short Estimating utility functions using generalized maximum entropy
title_full Estimating utility functions using generalized maximum entropy
title_fullStr Estimating utility functions using generalized maximum entropy
title_full_unstemmed Estimating utility functions using generalized maximum entropy
title_sort Estimating utility functions using generalized maximum entropy
author Pires, Cesaltina
author_facet Pires, Cesaltina
Dionísio, Andreia
Coelho, Luís
author_role author
author2 Dionísio, Andreia
Coelho, Luís
author2_role author
author
dc.contributor.author.fl_str_mv Pires, Cesaltina
Dionísio, Andreia
Coelho, Luís
dc.subject.por.fl_str_mv generalized maximum entropy
utility elicitation
Morgenstern utility
maximum entropy principle
topic generalized maximum entropy
utility elicitation
Morgenstern utility
maximum entropy principle
description This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.
publishDate 2013
dc.date.none.fl_str_mv 2013-10-30T11:43:42Z
2013-10-30
2013-01-01T00:00:00Z
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 http://hdl.handle.net/10174/8946
http://hdl.handle.net/10174/8946
https://doi.org/10.1080/02664763.2012.740625
url http://hdl.handle.net/10174/8946
https://doi.org/10.1080/02664763.2012.740625
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pires, C., A. Dionísio, L. Coelho (2013), "Estimating utility functions using GME", Journal of Applied Statistics, 40(1), 221-234.
Departamento de Gestão
cpires@uevora.pt
andreia@uevora.pt
lcoelho@uevora.pt
637
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Taylor and Francic
publisher.none.fl_str_mv Taylor and Francic
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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