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On Bayesian inference for the M/G/1 queue with efficient MCMC sampling

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arxiv 1401.5548 v1 pith:5X22FPSW submitted 2014-01-22 stat.CO

Alexander Y. Shestopaloff , Radford M. Neal This is my paper · ORCID
classification stat.CO
keywords samplingmcmcupdatesbayesianefficientinferencenovelscheme
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We introduce an efficient MCMC sampling scheme to perform Bayesian inference in the M/G/1 queueing model given only observations of interdeparture times. Our MCMC scheme uses a combination of Gibbs sampling and simple Metropolis updates together with three novel "shift" and "scale" updates. We show that our novel updates improve the speed of sampling considerably, by factors of about 60 to about 180 on a variety of simulated data sets.

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Cited by 1 Pith paper

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