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dc.contributor.authorGarcía Cortés, Luis Alberto
dc.contributor.authorCabrillo, Carlos
dc.contributor.authorMoreno, Carlos
dc.contributor.authorVarona Aguado, Luís
dc.description.abstractThe testing of Bayesian point null hypotheses on variance component models have resulted in a tough assigmment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding approach to such a task. It is based on a simple reparameterization of the model in terms of the total variance and the proportion of the additive genetic variance with respect to it, as well as on the explicit inclusion on the prior probability of a discrete component at origin. The reparameterization was used to bypass an arbitrariness related to the impropriety of uninformative priors onto unbounded variables while the discrete component was necessary to overcome the zero probability assigned to sets of null measure by the usual continuous variable models. The method was tested against computer simulations with appealing results.ca_ES
dc.publisherBioMed Centralca_ES
dc.relation.isformatofReproducció del document publicat a
dc.relation.ispartofGenetics Selection Evolution, 2001, vol. 33, núm. 1, p. 3-16ca_ES
dc.rightscc-by (c) García Cortés et al., 2001ca_ES
dc.subjectAnimal breedingca_ES
dc.subjectPrior distributionca_ES
dc.subjectBayes factorca_ES
dc.titleHypothesis testing for the genetic background of quantitative traitsca_ES

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