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Fast genomic prediction of breeding values using parallel Markov chain Monte Carlo with convergence diagnosis
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Running multiple-chain Markov Chain Monte Carlo (MCMC) provides an efficient parallel computing method for complex Bayesian models, although the efficiency of the approach critically depends on the length of the non-parallelizable burn-in period, for which all simulated data are discarded.
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