A Tutorial on Reversible Jump MCMC with a View toward Applications in QTL-mapping |
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| Authors: | Rasmus Waagepetersen Daniel Sorensen |
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| Affiliation: | Aalborg University, Department of Mathematical Sciences, DK-9220 Aalborg, Denmark, E-mail:;Section on Biometrical Genetics, Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, PB 50, DK-8830 Tjele, Denmark, E-mail: |
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| Abstract: | A tutorial derivation of the reversible jump Markov chain Monte Carlo (MCMC) algorithm is given. Various examples illustrate how reversible jump MCMC is a general framework for Metropolis-Hastings algorithms where the proposal and the target distribution may have densities on spaces of varying dimension. It is finally discussed how reversible jump MCMC can be applied in genetics to compute the posterior distribution of the number, locations, effects, and genotypes of putative quantitative trait loci. |
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| Keywords: | Markov chain Monte Carlo Metropolis-Hastings algorithm Reversible jump Quantitative trait loci mapping |
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