Comment on “On the Metropolis-Hastings Acceptance Probability to Add or Drop a Quantitative Trait Locus in Markov Chain Monte Carlo-Based Bayesian Analyses” | Zendy

Mikko J. Sillanpää | Zendy; Dario Gasbarra | Zendy; Elja Arjas | Zendy

Open Access

Comment on “On the Metropolis-Hastings Acceptance Probability to Add or Drop a Quantitative Trait Locus in Markov Chain Monte Carlo-Based Bayesian Analyses”

Author(s) -

Mikko J. Sillanpää,

Dario Gasbarra,

Elja Arjas

Publication year - 2004

Publication title -

genetics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.792

H-Index - 246

eISSN - 1943-2631

pISSN - 0016-6731

DOI - 10.1534/genetics.103.025320

Subject(s) - markov chain monte carlo , metropolis–hastings algorithm , markov chain , quantitative trait locus , bayesian probability , monte carlo method , trait , locus (genetics) , statistical physics , statistics , mathematics , biology , computer science , genetics , physics , gene , programming language

AS Jean-Luc Jannink and Rohan L. Fernando ([Jannink and Fernando 2004][1]) nicely illustrated, when applying Markov chain Monte Carlo methods in a form where the dimension [the number of quantitative trait loci (QTL)] is not fixed, it can sometimes be hard to establish the correct form of the

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