Incorporating prior knowledge into Bayesian models for genetic evaluation in soybean breeding

Incorporating prior knowledge into Bayesian models for genetic evaluation in soybean breeding

Abstract The objective of this work was to compare the use of noninformative and informative priors in Bayesian models, as well as to evaluate the viability of including informative priors in the estimation of variance components and genetic values in soybean breeding programs. The used phenotypic d...

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Bibliographic Details
Main Authors: Jeniffer Santana Pinto Coelho Evangelista, Igor Ferreira Coelho, Marco Antonio Peixoto, Rodrigo Silva Alves, Marcos Deon Vilela de Resende, Felipe Lopes da Silva, Leonardo Lopes Bhering
Format: Article
Language:English
Published: Embrapa Informação Tecnológica 2024-09-01
Series:Pesquisa Agropecuária Brasileira
Subjects:
Glycine max
Bayesian inference
Gibbs sampler
HPD
MCMC
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2024000104903&lng=en&tlng=en

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http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2024000104903&lng=en&tlng=en

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