Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10356398 | Journal of Computational Physics | 2005 | 13 Pages |
Abstract
We present an algorithm based on maximum likelihood for the estimation and renormalization (marginalization) of exponential densities. The moment-matching problem resulting from the maximization of the likelihood is solved as an optimization problem using the Levenberg-Marquardt algorithm. In the case of renormalization, the moments needed to set up the moment-matching problem are evaluated using Swendsen's renormalization method. We focus on the renormalization version of the algorithm, where we demonstrate its use by computing the critical temperature of the two-dimensional Ising model. Possible applications of the algorithm are discussed.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Panagiotis Stinis,