{
  "id": "1009.2260",
  "version": "v3",
  "published": "2010-09-12T19:22:10.000Z",
  "updated": "2011-12-22T17:37:48.000Z",
  "title": "Computing the confidence levels for a root-mean-square test of goodness-of-fit, II",
  "authors": [
    "William Perkins",
    "Mark Tygert",
    "Rachel Ward"
  ],
  "comment": "14 pages, 3 figures (each with two parts), 4 tables",
  "categories": [
    "stat.CO",
    "stat.ME"
  ],
  "abstract": "This paper extends our earlier article, \"Computing the confidence levels for a root-mean-square test of goodness-of-fit;\" unlike in the earlier article, the models in the present paper involve parameter estimation -- both the null and alternative hypotheses in the associated tests are composite. We provide efficient black-box algorithms for calculating the asymptotic confidence levels of a variant on the classic chi-squared test. In some circumstances, it is also feasible to compute the exact confidence levels via Monte Carlo simulation.",
  "revisions": [
    {
      "version": "v3",
      "updated": "2011-12-22T17:37:48.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "root-mean-square test",
      "goodness-of-fit",
      "earlier article",
      "efficient black-box algorithms",
      "asymptotic confidence levels"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 14,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2010arXiv1009.2260P"
    }
  }
}