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| Registros recuperados : 238 | |
| 103. |  | PEREIRA, J. E.; SILVA, J. F. V.; DIAS, W. P.; SOUZA, G. da S. e. Intervalo de confiança "Bootstrap" como ferramenta para classificar raças do nematóide de cisto da soja. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 35, n. 2, p. 271-275, fev. 2000. Título em inglês: Bootstrap confidence intervals as tool to classify races of soybean's cyst nematode.| Biblioteca(s): Embrapa Soja; Embrapa Unidades Centrais. |
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| 115. | | LOPES, M. de R.; SOUZA, G. da S. e; LOPES, I. V.; HONCZAR, G. O problemas do acesso ao capital na agricultura brasileira. Revista de Política Agrícola, Brasília, DF, ano 10, n. 4, p. 16-25, Out./Nov./Dez. 2001.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 118. | | SOUZA, G. da S. e; SOUZA, M. O. de; MARQUES, D. V.; GAZZOLA, R.; MARRA, R. Previsões para o mercado de carnes. In: Revista de Economia e Sociologia Rural. Piracicaba, SP, vol. 49, nº 02, p. 473-492, abr/jun 2011.| Biblioteca(s): Embrapa Unidades Centrais. |
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| Registros recuperados : 238 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Unidades Centrais. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
10/12/2021 |
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Data da última atualização: |
10/12/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SOUZA, G. da S. e; GOMES, E. G.; ALVES, E. R. de A. |
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Afiliação: |
GERALDO DA SILVA E SOUZA, SIRE; ELIANE GONCALVES GOMES, SIRE; ELISEU ROBERTO DE ANDRADE ALVES, DE/PR. |
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Título: |
Two-part fractional regression model with conditional FDH responses: an application to Brazilian agriculture. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Annals of Operations Research, 2020. |
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DOI: |
https://doi.org/10.1007/s10479-020-03752-z |
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Idioma: |
Inglês |
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Notas: |
Published online: 10 August 2020. |
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Conteúdo: |
We extend the notion of a two-part fractional regression model with conditional free disposal hull efciency responses to accommodate two-stage regression analysis. The twopart regression model includes the binomial model with a nonlinear specifcation for the expected response in (0,1] and is a more general formulation in the context of fractional regressions. We use nonlinear least squares to assess the efect of covariates in the conditional efciency response. The approach is applied to Brazilian agricultural county data, as reported in the Brazilian agricultural census of 2006. The efciency measure is output oriented and assumes variable returns to scale. Output is rural gross income and inputs are land expenses, labor expenses and expenses on other technological inputs. The covariates afecting production are credit, technical assistance, a rural development index, income concentration, measured by the Gini index, and regional dummies. Overall Brazilian rural production performance responds positively to all covariates |
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Thesagro: |
Agricultura. |
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Categoria do assunto: |
-- |
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Marc: |
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008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s10479-020-03752-z$2DOI
100 1 $aSOUZA, G. da S. e
245 $aTwo-part fractional regression model with conditional FDH responses$ban application to Brazilian agriculture.$h[electronic resource]
260 $c2020
500 $aPublished online: 10 August 2020.
520 $aWe extend the notion of a two-part fractional regression model with conditional free disposal hull efciency responses to accommodate two-stage regression analysis. The twopart regression model includes the binomial model with a nonlinear specifcation for the expected response in (0,1] and is a more general formulation in the context of fractional regressions. We use nonlinear least squares to assess the efect of covariates in the conditional efciency response. The approach is applied to Brazilian agricultural county data, as reported in the Brazilian agricultural census of 2006. The efciency measure is output oriented and assumes variable returns to scale. Output is rural gross income and inputs are land expenses, labor expenses and expenses on other technological inputs. The covariates afecting production are credit, technical assistance, a rural development index, income concentration, measured by the Gini index, and regional dummies. Overall Brazilian rural production performance responds positively to all covariates
650 $aAgricultura
700 1 $aGOMES, E. G.
700 1 $aALVES, E. R. de A.
773 $tAnnals of Operations Research, 2020.
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