The Multiset Sampler
- 1 September 2009
- journal article
- Published by Taylor & Francis in Journal of the American Statistical Association
- Vol. 104 (487) , 1029-1041
- https://doi.org/10.1198/jasa.2009.tm08047
Abstract
We introduce the multiset sampler (MSS), a new Metropolis–Hastings algorithm for drawing samples from a posterior distribution. The MSS is designed to be effective when the posterior has the feature that the parameters can be divided into two sets, X, the parameters of interest and Y, the nuisance parameters. We contemplate a sampler that iterates between X moves and Y moves. We consider the case where either (a) Y is discrete and lives on a finite set or (b) Y is continuous and lives on a bounded set. After presenting some background, we define a multiset and show how to construct a distribution on one. The construction may seem artificial and pointless at first, but several small examples illustrate its value. Finally, we demonstrate the MSS in several realistic examples and compare it with alternatives.Keywords
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