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Perfect slice samplers
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DOI：10.1111/1467-9868.00301.png)
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Abstract
En 中文
Perfect sampling allows the exact simulation of random variables from the stationary measure of a Markov chain. By exploiting monotonicity properties of the slice sampler we show that a perfect version of the algorithm can be easily implemented, at least when the target distribution is bounded. Various extensions, including perfect product slice samplers, and examples of applications are discussed.
Keywords:
automodels
auxiliary variables
coupling from the past
ising model
perfect simulation
random fields
Swendsen-Wang algorithm
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