{
  "id": "1301.6607",
  "version": "v2",
  "published": "2013-01-28T17:02:59.000Z",
  "updated": "2013-12-05T19:09:21.000Z",
  "title": "Estimating the covariance of random matrices",
  "authors": [
    "Pierre Youssef"
  ],
  "comment": "29 pages",
  "categories": [
    "math.PR"
  ],
  "abstract": "We extend to the matrix setting a recent result of Srivastava-Vershynin about estimating the covariance matrix of a random vector. The result can be in- terpreted as a quantified version of the law of large numbers for positive semi-definite matrices which verify some regularity assumption. Beside giving examples, we dis- cuss the notion of log-concave matrices and give estimates on the smallest and largest eigenvalues of a sum of such matrices.",
  "revisions": [
    {
      "version": "v2",
      "updated": "2013-12-05T19:09:21.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "random matrices",
      "estimating",
      "covariance matrix",
      "largest eigenvalues",
      "large numbers"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 29,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2013arXiv1301.6607Y"
    }
  }
}