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A variant of the Metropolis algorithm is proposed that allows parallel processing. Rather than generating a single candidate point, as in the Metropolis algorithm, for each chain iteration a number of candidates are generated. Energy calculations for each of these candidates can be carried out in parallel. This algorithm would be advantageous in fitting model parameters to data in a Bayesian context, where the forward model calculations (the analog of the energy calculations), are time consuming.
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Guthrie Miller (2010) studied this question.
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