{
  "id": "1101.3709",
  "version": "v3",
  "published": "2011-01-19T15:42:33.000Z",
  "updated": "2012-07-23T09:23:00.000Z",
  "title": "Estimation of means in graphical Gaussian models with symmetries",
  "authors": [
    "Helene Gehrmann",
    "Steffen L. Lauritzen"
  ],
  "comment": "Published in at http://dx.doi.org/10.1214/12-AOS991 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)",
  "journal": "Annals of Statistics 2012, Vol. 40, No. 2, 1061-1073",
  "doi": "10.1214/12-AOS991",
  "categories": [
    "math.ST",
    "stat.TH"
  ],
  "abstract": "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.",
  "revisions": [
    {
      "version": "v3",
      "updated": "2012-07-23T09:23:00.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "estimation",
      "undirected graphical gaussian models",
      "symmetry restrictions",
      "sufficient condition",
      "ensure equality"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "publisher": "Institute of Mathematical Statistics",
      "journal": "Ann. Stat."
    },
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2011arXiv1101.3709G"
    }
  }
}