ESTIMATION OF MEANS IN GRAPHICAL GAUSSIAN MODELS WITH SYMMETRIES

• 成果类型: Article
• 署名作者: Gehrmann, Helene; Lauritzen, Steffen L.
• 署名单位: University of Oxford
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/12-AOS991
• 发表日期: 2012
• 页码: 1061-1073
• 关键词: markov; hypotheses

摘要

We study the problem of estimability of means in undirected graphical Gaussian models with symmetry restrictions represented by a colored graph. Following on from previous studies, we partition the variables into sets of vertices whose corresponding means are restricted to being identical. We find a necessary and sufficient condition on the partition to ensure equality between the maximum likelihood and least-squares estimators of the mean.