{
  "abstract": "A quickest change detection problem is studied where the decision-maker has access to multiple experiments, but can choose only one experiment at a time to detect the change. The true post-change distribution under each experiment is unknown, but known to belong to a family of distributions. It is assumed that each of these families of distributions has an element that is least favorable in a well-defined sense. An algorithm is proposed that is designed using the least favorable distributions. It is shown that the algorithm is first-order asymptotically optimal, as the rate of false alarms goes to zero. This algorithm minimizes the worst-case average detection delay over all post-change distributions within the assumed families, subject to a constraint on the average run length to false alarm and constraints on the average fraction of time each experiment is performed before change.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.16055",
  "author_total": 2,
  "authors": [
    {
      "name": "Patrick Vincent Lubenia"
    },
    {
      "name": "Taposh Banerjee"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5tp9e4cb99rbz.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.16055",
  "fulltext_url": null,
  "id": "5tp9e4cb99rbz",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.16055",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.IT"
    ],
    [
      "arxiv",
      "eess.SP"
    ],
    [
      "arxiv",
      "math.IT"
    ],
    [
      "arxiv",
      "math.ST"
    ],
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      "arxiv",
      "stat.TH"
    ],
    [
      "openalex",
      "1804|Advanced Statistical Process Monitoring"
    ]
  ],
  "openalex": "W7221790942",
  "pdf_url": "https://arxiv.org/pdf/2610.16055",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5tp9e4cb99rbz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:15Z",
      "native_id": "2610.16055",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.16055"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.ST",
      "subfield": "statistics"
    }
  ],
  "title": "Robust Quickest Change Detection with Cost-Efficient Experiment Design and Unknown Post-Change Model",
  "title_text": "Robust Quickest Change Detection with Cost-Efficient Experiment Design and Unknown Post-Change Model",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:26Z",
  "url": "https://research.draconitic.com/paper/5tp9e4cb99rbz",
  "venue": "arXiv",
  "versions": []
}