离散马尔可夫随机场的统计推断方法综述
A review on statistical inference methods for discrete Markov random fields
摘要：
发展令人满意的马尔可夫随机场分析方法是一项非常具有挑战性的任务。事实上，由于马尔可夫依赖结构，场的归一化常数不能使用标准的分析或数值方法计算。这是任何统计方法的核心问题，因为可能性是该程序的组成部分。此外，这样的未观察到的领域不能被整合出来的可能性评估成为一个双重棘手的问题。本报告概述了文献中用于分析此类观察到或未观察到的随机场的一些方法。
英文摘要：
Developing satisfactory methodology for the analysis of Markov random field is a very challenging task. Indeed, due to the Markovian dependence structure, the normalizing constant of the fields cannot be computed using standard analytical or numerical methods. This forms a central issue for any statistical approach as the likelihood is an integral part of the procedure. Furthermore, such unobserved fields cannot be integrated out and the likelihood evaluation becomes a doubly intractable problem. This report gives an overview of some of the methods used in the literature to analyse such observed or unobserved random fields.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
