ESTIMATION OF MEANS IN GRAPHICAL GAUSSIAN MODELS WITH SYMMETRIES
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...
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| Veröffentlicht in: | The Annals of statistics 2012-04, Vol.40 (2), p.1061-1073 |
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| container_end_page | 1073 |
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| container_issue | 2 |
| container_start_page | 1061 |
| container_title | The Annals of statistics |
| container_volume | 40 |
| creator | Gehrmann, Helene Lauritzen, Steffen L. |
| description | 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. |
| doi_str_mv | 10.1214/12-AOS991 |
| format | Article |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; JSTOR Mathematics & Statistics; Jstor Complete Legacy; Project Euclid Complete |
| subjects | 62F99 62H12 Conditional independence Covariance Estimating techniques Estimators invariance Least squares Mathematical vectors Maximum likelihood estimation Maximum likelihood estimators Normal distribution patterned mean vector Statistics Studies Sufficient conditions Symmetry Vertices |
| title | ESTIMATION OF MEANS IN GRAPHICAL GAUSSIAN MODELS WITH SYMMETRIES |
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