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One-stop-shop for artificial intelligence and machine learning for official statistics / by Francesca Kay.: CS11-522/2024-1-27E-PDF

"Several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020 are identified. They include locational accuracy, person coverage and its consistency over time, filtering out non-residents and people not alive on the reference date, uncovering missing links across person and address records, and predicting demographic characteristics. Several ways to address these issues are discussed. Regression results illustrate how the challenges and solutions affect the AR-based county population estimates"--Abstract, page [2].

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.966895&sl=0

Publication information
Department/Agency
  • Statistics Canada, issuing body.
TitleOne-stop-shop for artificial intelligence and machine learning for official statistics / by Francesca Kay.
Variant title
  • At head of title: Proceedings of Statistics Canada Symposium 2024 : the future of official statistics
Series title
  • [Statistics Canada international symposium series : proceedings], 1709-8211
Publication typeMonograph - View Master Record
Language[English]
Other language editions[French]
FormatDigital text
Electronic document
Note(s)
  • Issued also in French under title: Boutique multiservice d’intelligence artificielle et d’apprentissage automatique pour les statistiques officielles.
Publishing information
  • [Ottawa] : Statistics Canada = Statistique Canada, September 8, 2025.
Author / Contributor
  • Kay, Francesca, author.
Description1 online resource (8 unnumbered pages).
Catalogue number
  • CS11-522/2024-1-27E-PDF
Departmental catalogue number11-522-X
Subject terms
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