A maximum likelihood algorithm for the estimation and renormalization of exponential densities
统计理论
2009-11-10 v1 数值分析
统计理论
摘要
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.
引用
@article{arxiv.math/0409230,
title = {A maximum likelihood algorithm for the estimation and renormalization of exponential densities},
author = {Panagiotis Stinis},
journal= {arXiv preprint arXiv:math/0409230},
year = {2009}
}
备注
18 pages, 3 figures. Submitted to the Journal of Computational Physics