Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/33648
Title: Componentes de efeitos de safras representados em biplots corrigidos por predições de modelos GEE na classificação granulométrica de cafés
Other Titles: Components of crop effects represented in biplots corrected by predictions of gee models in the granulometric classification of coffee beans
Authors: Cirillo, Marcelo Ângelo
Brighenti, Carla Regina Guimarães
Góis, Evelise Roman Corbalan
Oliveira, Izabela Regina Cardoso de
Giarola, Luciane Teixeira Passos
Keywords: Granulometria
Complemento log log
Café - Classificação granulométrica
Técnica biplots
Granulometry
Complementary log log
Coffee - Granulometric grading
Issue Date: 16-Apr-2019
Publisher: Universidade Federal de Lavras
Citation: FERREIRA, H. A. Componentes de efeitos de safras representados em biplots corrigidos por predições de modelos GEE na classificação granulométrica de cafés. 2019. 55 p. Dissertação (Mestrado em Estatística e Experimentação Agropecuária)-Universidade Federal de Lavras, Lavras, 2019.
Abstract: In a granulometric analysis of coffee beans with different defect categories, the data can be organized in contingency tables and, considering discrimination by crops, they might present a structure that suggests a more complex model when it comes to the interaction of crop effects with the defect classifications and percentage of sieve beans. In view of the foregoing, the hypothesis that correlation structures may be incorporated to a model in order to improve multidimensional graphic analysis (such as the biplots technique) arises. Therefore, this work has as its objective to propose the use of biplots corrected by predictions of GEE models in the granulometric classification of coffee beans, discriminated by components of crop effects. To validate the proposal, Monte Carlo realizations were performed in different contingency table structures in scenarios with different degrees of correlation. It was concluded that the use of GEE models with the biplot technique corrected by the predictions is applicable in the granulometric analysis of defective coffee beans, with an efficient discrimination of crop effects.
URI: http://repositorio.ufla.br/jspui/handle/1/33648
Appears in Collections:DES - Estatística e Experimentação Agropecuária - Mestrado (Dissertações)



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