Estimation of means in graphical Gaussian models with symmetries. (English) Zbl 1274.62366
Summary: 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.
Keywords:
conditional independence; invariance; maximum likelihood estimation; patterned mean vector; symmetrySoftware:
gRcReferences:
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