{
  "id": "2104.02717",
  "version": "v1",
  "published": "2021-04-06T17:27:36.000Z",
  "updated": "2021-04-06T17:27:36.000Z",
  "title": "Discussion of \"A Gibbs sampler for a class of random convex polytopes\"",
  "authors": [
    "Jonathan P Williams"
  ],
  "comment": "8 pages",
  "categories": [
    "stat.CO",
    "stat.ME"
  ],
  "abstract": "An exciting new algorithmic breakthrough has been advanced for how to carry out inferences in a Dempster-Shafer (DS) formulation of a categorical data generating model. The developed sampling mechanism, which draws on theory for directed graphs, is a clever and remarkable achievement, as this has been an open problem for many decades. In this discussion, I comment on important contributions, central questions, and prevailing matters of the article.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2021-04-06T17:27:36.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "random convex polytopes",
      "gibbs sampler",
      "discussion",
      "central questions",
      "algorithmic breakthrough"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 8,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}