Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/43167
Title: Abordagem bayesiana para avaliação da adaptabilidade e estabilidade de genótipos de alfafa
Other Titles: Bayesian approach for the evaluation of adaptability and stability of alfalfa genotypes
Keywords: Medicago sativa
Fator de Bayes
Priori informativa
Interação genótipo x ambiente
MCMC
Markov chain Monte Carlo (MCMC)
Bayes factor
Informative prior
Genotype x Environment interaction
Issue Date: Jan-2011
Publisher: Empresa Brasileira de Pesquisa Agropecuária (Embrapa), Secretaria de Pesquisa e Desenvolvimento (SPD)
Citation: NASCIMENTO, M. et al. Abordagem bayesiana para avaliação da adaptabilidade e da estabilidade de genótipos de alfafa. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 46, n. 1, p. 26-32, Jan. 2011. DOI: 10.1590/S0100-204X2011000100004.
Abstract: The objective of this work was to propose a Bayesian approach for the Eberhart & Russell method to evaluate the phenotypic adaptability and stability of alfafa (Medicago sativa) genotypes, as well as to evaluate the efficiency of the use of prior informative and noninformative distributions. Data from a randomized block design experiment evaluating the forage dry weight of 92 genotypes were used. The Bayesian methodology proposed was implemented in the free software R by the MCMCregress function of the MCMCpack package. To represent the noninformative prior distributions, a probability distribution with high variance was used; and, to represent the informative prior, a meta-analysis concept was adopted, characterized by the use of information provided by previous studies. The comparison between the prior distributions was done using the Bayes Factor, with the BayesFactor function of the MCMCpack package, which indicated that an informative prior is more appropriate under the conditions of this study.
URI: http://repositorio.ufla.br/jspui/handle/1/43167
Appears in Collections:DEX - Artigos publicados em periódicos



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