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This paper gives an algorithm for calculating posterior probabilities using thermodynamic integration. The thermodynamic integration calculations are accomplished by annealing an ensemble of Markov chains with an adaptive schedule. The algorithm includes a method for determining “good” starting positions for the chains at each new value of the annealing parameter.

Using Thermodynamic Integration to Calculate the Posterior Probability in Bayesian Model Selection Problems