{
  "id": "1510.03679",
  "version": "v1",
  "published": "2015-10-13T14:06:50.000Z",
  "updated": "2015-10-13T14:06:50.000Z",
  "title": "Bounds for the multivariate normal approximation of the maximum likelihood estimator",
  "authors": [
    "Andreas Anastasiou"
  ],
  "comment": "29 pages",
  "categories": [
    "math.ST",
    "stat.TH"
  ],
  "abstract": "The asymptotic normality of the maximum likelihood estimator (MLE) under regularity conditions is a cornerstone of statistical theory. In this paper, we give explicit upper bounds on the distributional distance between the distribution of the MLE of a possibly-high dimensional parameter, and the multivariate normal. An explicit analytical expression of the MLE is not required and the random vectors are independent but not necessarily identically distributed.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2015-10-13T14:06:50.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "62F12"
    ],
    "keywords": [
      "maximum likelihood estimator",
      "multivariate normal approximation",
      "explicit upper bounds",
      "possibly-high dimensional parameter",
      "regularity conditions"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 29,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2015arXiv151003679A"
    }
  }
}