{
  "abstract": "The aim of change-point detection is to identify behavioral shifts within time series data. This article focuses on scenarios where the data are derived from a heterogeneous Poisson process or a marked Poisson process. We present a methodology for detecting multiple offline change-points using a minimum contrast estimator. Specifically, we address how to manage the continuous nature of the process given the available discrete observations. Additionally, we select the appropriate number of changes via a cross-validation procedure, which is particularly effective given the characteristics of the Poisson process. Lastly, we show how to use this methodology for self-exciting processes with changes in the intensity. Through experiments, with both simulated and real datasets, we showcase the advantages of the proposed method, which has been implemented in the R package.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2302.09103",
  "author_total": 4,
  "authors": [
    {
      "name": "Charlotte Dion-Blanc"
    },
    {
      "name": "Diala Hawat"
    },
    {
      "name": "Émilie Lebarbier"
    },
    {
      "name": "Stephane S. Robin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/esn4y173bp78r.bib",
  "cited_by": 0,
  "doi": "10.1016/j.csda.2026.108464",
  "fulltext_url": null,
  "id": "esn4y173bp78r",
  "issns": [
    "0167-9473"
  ],
  "landing_url": "https://hal.science/hal-05732909v1",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.stat"
    ],
    [
      "openalex",
      "1804|Advanced Statistical Process Monitoring"
    ]
  ],
  "openalex": "W7067457467",
  "pdf_url": "https://www.sciencedirect.com/science/article/pii/S0167947326001337/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-31",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/esn4y173bp78r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:21Z",
      "native_id": "hal-05732909",
      "source": "hal",
      "url": "https://hal.science/hal-05732909v1"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "hal:0.stat",
      "subfield": "statistics"
    }
  ],
  "title": "Multiple change-point detection for Poisson processes",
  "title_text": "Multiple change-point detection for Poisson processes",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:21Z",
  "url": "https://research.draconitic.com/paper/esn4y173bp78r",
  "venue": "Computational Statistics and Data Analysis",
  "versions": []
}