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

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

<p>Abstract</p> <p>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 structured variance heterogeneity. A particu...

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Bibliographic Details
Main Authors: Sorensen Daniel, Ibánẽz-Escriche Noelia, Waagepetersen Rasmus
Format: Article
Language:deu
Published: BMC 2008-03-01
Series:Genetics Selection Evolution
Subjects:
Langevin-Hastings
Markov chain Monte Carlo
normal approximation
proposal distributions
reparameterization
Online Access:http://www.gsejournal.org/content/40/2/161

Internet

http://www.gsejournal.org/content/40/2/161

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