The EM algorithm for standard stochastic frontier models

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorAndrade, Bernardo Borba de-
Autor(es): dc.creatorSouza, Geraldo da Silva e-
Data de aceite: dc.date.accessioned2024-10-23T15:19:53Z-
Data de disponibilização: dc.date.available2024-10-23T15:19:53Z-
Data de envio: dc.date.issued2020-01-23-
Data de envio: dc.date.issued2020-01-23-
Data de envio: dc.date.issued2019-
Fonte completa do material: dc.identifierhttps://repositorio.unb.br/handle/10482/36305-
Fonte completa do material: dc.identifierhttps://doi.org/10.1590/0101-7438.2019.039.03.0361-
Fonte completa do material: dc.identifierhttp://orcid.org/0000-0003-4688-9733-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/880350-
Descrição: dc.descriptionThe Expectation-Maximization (EM) algorithm is developed for the stochastic frontier models most used in practice with cross-section data. The resulting algorithms can be easily programmed into a computer and are shown to be worthy alternatives to general-purpose optimization routines currently used. The algorithms for the half normal and the exponential models have closed-form expressions whereas those for the truncated normal and gamma models will require the numerical solution of a nonlinear equation. Implementations of the EM algorithm either as a stand-alone routine or in accelerated form and also combined with Newton-like methods are discussed. We provide illustrations, along with R tools, for cost and production frontiers.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherSociedade Brasileira de Pesquisa Operacional-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rights(CC BY) - © 2019 Brazilian Operations Research Society-
Palavras-chave: dc.subjectEficiência-
Palavras-chave: dc.subjectAceleração EM-
Palavras-chave: dc.subjectProbabilidades-
Palavras-chave: dc.subjectAlgoritmos-
Título: dc.titleThe EM algorithm for standard stochastic frontier models-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional – UNB

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