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dc.contributor.authorRESENDE, M. D. V. de
dc.contributor.authorFERNANDES, J. S. C.
dc.contributor.authorBERTOLUCCI, F. DE L. G
dc.contributor.authorDUDA, L. L.
dc.date.accessioned2025-07-18T19:48:06Z-
dc.date.available2025-07-18T19:48:06Z-
dc.date.created2002-02-21
dc.date.issued2000
dc.identifier.citationIn: FOREST GENETICS FOR THE NEXT MILLENNIUM, 2000, Durban. Proceedings... Scottsville: Institute for Commercial Forestry Research, 2000.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/303935-
dc.descriptionThis paper describes some efforts made in Brazil in the framework of breeding (additive genetic) and genotypic (additive + dominance) values prediction and variance components estimation in a tree breeding context. Emphasis is given to the use of the mixed linear models techniques including both, frequentist and Bayesian approaches. For growth traits, which are associated to growth trajectories or curves through the ages, alternative models like repeatability, multivariate and random regression models were'compared. Using data from a Eucalyptus urophy!ta progeny test, evaluated at several ages (1,2......7 years), the random regression or covariance functions model has performed successfully. The application (using data from unbalanced diallel mating designs of Pinus caribaea var. hondurensis) of Bayesian techniques, implemented trough stochastic simulation (Gibbs sampling), showed that additional results in relation to frequentist approach are obtained.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectRandom regression
dc.subjectBayesian statistics
dc.subjectMixed model equations
dc.subjectIndividual BLUP
dc.subjectREML
dc.titleBayesian and frequentist statistical analysis in quantitative genetics applied to fores trees breeding in Brazil.
dc.typeArtigo em anais e proceedings
dc.subject.thesagroPinus Caribaea
dc.description.notesIUFRO Working Party 2.08.01. Tropical Species Breeding and Genetic Resources.
riaa.ainfo.id303935
riaa.ainfo.lastupdate2025-07-18
dc.contributor.institutionMARCOS DEON VILELA DE RESENDE, CNPF.
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