{
  "id": "1212.1379",
  "version": "v3",
  "published": "2012-12-06T16:59:58.000Z",
  "updated": "2013-06-09T14:09:56.000Z",
  "title": "Optimal On-Line Selection of an Alternating Subsequence: A Central Limit Theorem",
  "authors": [
    "Alessandro Arlotto",
    "J. Michael Steele"
  ],
  "comment": "24 pages, 1 figure",
  "journal": "Advances in Applied Probability, 42 (2), 2014, 536-559",
  "doi": "10.1239/aap/1401369706",
  "categories": [
    "math.PR",
    "math.OC"
  ],
  "abstract": "We analyze the optimal policy for the sequential selection of an alternating subsequence from a sequence of $n$ independent observations from a continuous distribution $F$, and we prove a central limit theorem for the number of selections made by that policy. The proof exploits the backward recursion of dynamic programming and assembles a detailed understanding of the associated value functions and selection rules.",
  "revisions": [
    {
      "version": "v3",
      "updated": "2013-06-09T14:09:56.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "60C05",
      "60G40",
      "90C40",
      "60F05",
      "90C27",
      "90C39"
    ],
    "keywords": [
      "central limit theorem",
      "optimal on-line selection",
      "alternating subsequence",
      "optimal policy",
      "sequential selection"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 24,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2012arXiv1212.1379A"
    }
  }
}