Article
Fast spatial inference in the homogeneous Ising model
arXiv
Document Type
Article
Disciplines
Publication Version
Submitted Manuscript
Publication Date
1-1-2017
Abstract
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 calculate these quantities numerically. 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.
Copyright Owner
The Authors
Copyright Date
2017
Language
en
File Format
application/pdf
Citation Information
Alejandro Murua and Ranjan Maitra. "Fast spatial inference in the homogeneous Ising model" arXiv (2017) Available at: http://works.bepress.com/ranjan-maitra/29/
This is a pre-print of the article Murua, Alejandro, and Ranjan Maitra. "Fast spatial inference in the homogeneous Ising model." arXiv preprint arXiv:1712.02195 (2017). Posted with permission.