http://repositorio.unb.br/handle/10482/36305
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ARTIGO_AlgorithmStandardStochastic.pdf | 267,43 kB | Adobe PDF | Voir/Ouvrir |
Titre: | The EM algorithm for standard stochastic frontier models |
Auteur(s): | Andrade, Bernardo Borba de Souza, Geraldo da Silva e |
metadata.dc.identifier.orcid: | http://orcid.org/0000-0003-4688-9733 |
Assunto:: | Eficiência Aceleração EM Probabilidades Algoritmos |
Date de publication: | 2019 |
Editeur: | Sociedade Brasileira de Pesquisa Operacional |
Référence bibliographique: | ANDRADE, Bernardo B. de; SOUZA, Geraldo S. The EM algorithm for standard stochastic frontier models. Pesquisa Operacional, v. 39, n. 3, p. 361-378, 2019. DOI: https://doi.org/10.1590/0101-7438.2019.039.03.0361. Disponível em: http://scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382019000300361. Acesso em: 23 jan. 2020. |
Abstract: | The 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. |
Licença:: | (CC BY) - © 2019 Brazilian Operations Research Society |
DOI: | https://doi.org/10.1590/0101-7438.2019.039.03.0361 |
Collection(s) : | Artigos publicados em periódicos e afins |
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