{
  "abstract": "This paper,we consider semiparameter models defined by moments constraints,with unknown parameter,for righ censored data.We derives estimates and converges properties for the parameter of interest,by means of minimizing the robust density power divergence methodology of Basu, Harris, Hjort, and Jones (Biometrika, 85, 549-559, 1998) to the case of censored survival data between the considered model and the Kaplan and Meier (7) empirical measure.The coonsistency properties of the proposed estimates are studied.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "name": "Justin Moutsouka"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9abp6mzcx261q.bib",
  "cited_by": 0,
  "doi": null,
  "fulltext_url": null,
  "id": "9abp6mzcx261q",
  "issns": [],
  "landing_url": "https://hal.science/hal-05776804v1",
  "language": "en",
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.stat"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://hal.science/hal-05776804/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9abp6mzcx261q.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:47Z",
      "native_id": "hal-05776804",
      "source": "hal",
      "url": "https://hal.science/hal-05776804v1"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "hal:0.stat",
      "subfield": "statistics"
    }
  ],
  "title": "SMOOTH DIVERGENCES ESTIMATION FOR CENSORED SURVIVAL DATA",
  "title_text": "SMOOTH DIVERGENCES ESTIMATION FOR CENSORED SURVIVAL DATA",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:47Z",
  "url": "https://research.draconitic.com/paper/9abp6mzcx261q",
  "venue": "HAL",
  "versions": []
}