Convergence of Markov Chain Monte Carlo in genetic evaluation
1997
Supat Farungsang (Kasetsart Univ. Kamphaengsaen Campus, Nakhon Pathom (Thailand). Faculty of Agriculture. Dept. of Animal Science)
Markov chain Monte Carlo (MCMC) is becoming a method of choice for today genetic evaluation. The advantage of MCMC over conventional method is its approaching true genetic model whereas the conventional method based on falsify assumption e.g. infinisimal number of loci. With MCMC, true Mendelian loci model become feasible. In this investigation, the convergent of MCMC for a specific structure of population is studied. It is found that number of warm-up of MCMC process is as short as 2-3 rounds.
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