Using TPA for Bayesian inference — Discussion
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چکیده
Skilling (2007) previously identified that the number of steps required to reach a given set is Poisson distributed. Huber and Schott suggest making this special case central, recasting all computations as finding the mass of a distribution on a set. Additional contributions are a theoretical analysis, two general ways of reducing problems to the required form and a link to annealing. The resulting TPA methods are different from a straight application of Nested Sampling. For example, in both variants the initial sampling distribution is set to the posterior of an inference problem rather than the prior.
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تاریخ انتشار 2010