Abstract #302342

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JSM 2003 Abstract #302342
Activity Number: 310
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #302342
Title: Auxiliary Variables Algorithms for Continuum Random-Cluster Processes
Author(s): Rafaela Guidi*+ and Ranjan Maitra
Companies: Bank of Brazil and University of Maryland, Baltimore County
Address: SQN 210 Bloco D, Apt. 403, Brasilia-DF, , 70.862-040, Brazil
Keywords: continuum random-cluster process ; cluster process ; birth-and-death process ; auxiliary variables ; partial decoupling
Abstract:

Spatial point processes model objects that may be identified by a map of points showing galaxies, plants, towns, or stores in a two-dimensional region and have been used by scientists in disciplines such as astronomy, ecology, geography, and urban planning. Continuum random-cluster processes are a special case where the point patterns to be represented have an affinity for being close to each other. Analytical inference in such models are intractable, because in many cases, the likelihood function is known only up to a normalizing constant. Stochastic methods of inference are then the only hope. Single-point simulation schemes, such as Metropolis-Hastings algorithm, are slow in the presence of clustering preferences. Augmenting the point process distribution with partially decoupled auxiliary variables, which we present in this talk, while also maintaining the marginal distribution of the cluster process, performs well.

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