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A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

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A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

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Waagepetersen, R.; Ibáñez-Escriche, N.; Sorensen, D. (2008). A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics. Genetics Selection Evolution. 40(2):161-176. https://doi.org/10.1051/gse:2007042

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/134686

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Title: A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal
Issued date:
Abstract:
[EN] In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically ...[+]
Subjects: Langevin-Hastings , Markov chain Monte Carlo , Normal approximation , Proposal distributions , Reparameterization
Copyrigths: Reconocimiento (by)
Source:
Genetics Selection Evolution. (issn: 0999-193X )
DOI: 10.1051/gse:2007042
Publisher:
Springer (Biomed Central Ltd.)
Publisher version: https://doi.org/10.1051/gse:2007042
Type: Artículo

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