{
  "abstract": "Interval localization in multiple change-point detection aims to identify intervals containing true change-points while controlling false discoveries. We formulate this task as a multiple testing problem over detector-reported intervals and develop an algorithm-agnostic and distribution-free framework that controls the interval-level FDR, the expected proportion of retained intervals containing no true change-points. The proposed permutation-based order-preserving interval selection (POIS) uses order-preserving sample splitting to separate detection from permutation testing. To improve power, POIS+ reuses the detection-side evidence and introduces detection-conditional $e$-values as unnormalized weights for permutation $p$-values. Both procedures achieve finite-sample FDR control. Under the stated conditions, POIS attains asymptotically full power while POIS+ has asymptotically no lower power than POIS. Simulation results show that POIS maintains high power and POIS+ further improves power with empirical FDR below the nominal level for both procedures. Two real data applications demonstrate the practical effectiveness of the proposed methods.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.10271",
  "author_total": 4,
  "authors": [
    {
      "name": "Zijian Wei"
    },
    {
      "name": "Yajie Bao"
    },
    {
      "name": "Haojie Ren"
    },
    {
      "name": "Nan Chen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5wejxrd71e0g7.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.10271",
  "fulltext_url": null,
  "id": "5wejxrd71e0g7",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.10271",
  "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",
      "stat.ME"
    ],
    [
      "openalex",
      "1804|Advanced Statistical Process Monitoring"
    ]
  ],
  "openalex": "W7220923164",
  "pdf_url": "https://arxiv.org/pdf/2610.10271",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-07",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5wejxrd71e0g7.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:48Z",
      "native_id": "2610.10271",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.10271"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Interval Localization for Multiple Change-points with Error Rate Control",
  "title_text": "Interval Localization for Multiple Change-points with Error Rate Control",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:48Z",
  "url": "https://research.draconitic.com/paper/5wejxrd71e0g7",
  "venue": "arXiv",
  "versions": []
}