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Title: AMMI Bayesiano para dados ordinais
Other Titles: Bayesian AMMI for ordinal data
Authors: Balestre, Márcio
Silva, Carlos Pereira da
Bueno Filho, Júlio Sílvio de Sousa
Sáfadi, Thelma
Barroso, Camilla Marques
Corrêa, Fábio Mathias
Cassiano, Fernando Ribeiro
Keywords: AMMI-Bayesiano
Ensaios multi ambientais
Modelos de limiar
Variáveis ordinais
Multi environment trials
Ordinal variables
Threshold models
Issue Date: 5-Oct-2021
Publisher: Universidade Federal de Lavras
Citation: MENDES, C. T. E. AMMI Bayesiano para dados ordinais. 2021. 84 p. Tese (Doutorado em Estatística e Experimentação Agropecuária) – Universidade Federal de Lavras, Lavras, 2021.
Abstract: In this thesis we study the implementation of Bayesian AMMI for ordinal data. Initially we revisited theoretical aspects of Bayesian analysis, Multi Environment Trials (MET) and threshold models. In the last two sections are presented papers for scientific journals. The first is a review on Bayesian-AMMI literature folowed by a case study of the state of the art implementation. The model has shown flexibility to fit unbalanced, non-orthogonal and heteroscedastic data, but depends on continuous response in which Gaussian assumption is reasonable after scaling. The second deals with Bayesian AMMI to ordinal data. An ordinal data set on MET was artificially generated from continuous responses. This allows for a gold standard on ordinal data analysis, that is not available in actual ordinal data. A latent underlying continuous variable modeled with cumulative probit link allows for a suitable implementation of the analysis. This has shown to be efficient in telling stable from unstable genotypes. Using ordinal models interpretation is less powerful but more rigorous and consistent with continuous data analysis.
Appears in Collections:Estatística e Experimentação Agropecuária - Doutorado (Teses)

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