Roberts, Gareth O. and Petrone, S. and Rosenthal, Jeffrey S. (2000) Rates of convergence for Markov chains associated with Dirichlet processes. Far East Journal of Theoretical Statistics, 4 (2). pp. 207-236. ISSN 0972-0863Full text not available from this repository.
We argue that Monte Carlo algorithms are ideally suited to parallel computing, and that “parallel Monte Carlo” should be more widely used. We consider a number of issues that arise, including dealing with slow or unreliable computers. We also discuss the possibilities of parallel Markov chain Monte Carlo. We illustrate our results with actual computer experiments.
|Journal or Publication Title:||Far East Journal of Theoretical Statistics|
|Uncontrolled Keywords:||parallel computing ; distributed computing ; parallel Monte Carlo ; Markov chain Monte Carlo ; Gibbs sampler ; Metropolis-Hastings algorithm ; estimation.|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Lancaster Environment Centre|
|Deposited On:||17 Nov 2008 17:00|
|Last Modified:||03 Nov 2015 14:17|
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