{
  "id": "1301.5942",
  "version": "v2",
  "published": "2013-01-25T01:48:52.000Z",
  "updated": "2013-01-28T02:14:40.000Z",
  "title": "Confidence Intervals for the Mutual Information",
  "authors": [
    "A. G. Stefani",
    "J. B. Huber",
    "C. Jardin",
    "H. Sticht"
  ],
  "comment": "5 pages, 2 figure",
  "categories": [
    "cs.IT",
    "math.IT"
  ],
  "abstract": "By combining a bound on the absolute value of the difference of mutual information between two joint probablity distributions with a fixed variational distance, and a bound on the probability of a maximal deviation in variational distance between a true joint probability distribution and an empirical joint probability distribution, confidence intervals for the mutual information of two random variables with finite alphabets are established. Different from previous results, these intervals do not need any assumptions on the distribution and the sample size.",
  "revisions": [
    {
      "version": "v2",
      "updated": "2013-01-28T02:14:40.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "mutual information",
      "confidence intervals",
      "true joint probability distribution",
      "joint probablity distributions",
      "empirical joint probability distribution"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 5,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2013arXiv1301.5942S"
    }
  }
}