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A Tutorial on Reversible Jump MCMC with a View toward Applications in QTL‐mapping
Author(s) -
Waagepetersen Rasmus,
Sorensen Daniel
Publication year - 2001
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2001.tb00479.x
Subject(s) - markov chain monte carlo , reversible jump markov chain monte carlo , jump , quantitative trait locus , posterior probability , statistical physics , dimension (graph theory) , computer science , algorithm , distribution (mathematics) , mathematics , monte carlo method , bayesian probability , statistics , artificial intelligence , biology , combinatorics , physics , genetics , mathematical analysis , quantum mechanics , gene
Summary 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.