Parallel multivariate slice sampling

8 years 10 months ago
Parallel multivariate slice sampling
Slice sampling provides an easily implemented method for constructing a Markov chain Monte Carlo (MCMC) algorithm. However, slice sampling has two major drawbacks: (i) it requires repeated evaluation of likelihoods for each update, which can make it impractical when evaluations are expensive or as the number of evaluations grows (geometrically) with the dimension of the slice sampler, and (ii) since it can be challenging to construct multivariate updates, the updates are typically univariate, which often results in slow mixing samplers. We propose an approach to multivariate slice sampling that naturally lends itself to a parallel implementation. Our approach takes advantage of recent advances in computer architectures, for instance, the newest generation of graphics cards can execute roughly 30, 000 threads simultaneously. We demonstrate that it is possible to construct a multivariate slice sampler that has good mixing properties and is efficient in terms of computing time. The contr...
Matthew M. Tibbits, Murali Haran, John C. Liechty
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SAC
Authors Matthew M. Tibbits, Murali Haran, John C. Liechty
Comments (0)