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Activity Number: 513 - Topics in Monte Carlo Simulation
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #307165 Presentation
Title: Fast Spatial Inference in the Homogeneous Ising Model
Author(s): Ranjan Maitra* and Alejandro Murua
Companies: Iowa State University and University of Montreal
Keywords: fMRI; hypergeometric distribution; path sampling; Swendsen-Wang algorithm; Stirling's approximation; Wang-Landau algorithm

The Ising model is important in statistical modeling and inference in many applications, however its normalizing constant, mean number of active vertices and mean spin interaction are intractable. We provide accurate approximations that make it possible to numerically calculate these quantities in the homogeneous case. Simulation studies indicate good performance when compared to Markov Chain Monte Carlo methods and at a tiny fraction of the time. The methodology is also used to perform Bayesian inference in a functional Magnetic Resonance Imaging activation detection experiment.

Authors who are presenting talks have a * after their name.

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