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Model-based threshold selection for agricultural linkages / by Christian Arsenault.: CS11-522/2024-1-21E-PDF

"Optimal threshold selection is a critical challenge in probabilistic linkage, with significant implications for the accuracy and reliability of linked datasets. This paper analyzes the performance of the neighbour model, a recently proposed error model which models linkage errors by the number of links from each record. Three threshold selection algorithms utilizing the neighbour model were assessed, highlighting the strengths and limitations of each. Their performance was assessed through simulation studies, which demonstrated that methods using the neighbour model achieved lower relative bias compared to two established methods for threshold selection. Additionally, the practical utility was validated through goodness-of-fit tests conducted on four agricultural datasets, showing the potential of the model for use in the real-world applications"--Abstract, page [2].

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.966673&sl=0

Publication information
Department/Agency
  • Statistics Canada, issuing body.
TitleModel-based threshold selection for agricultural linkages / by Christian Arsenault.
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)
  • Title from cover.
  • Issued also in French under title: Sélection de seuils basée sur le modèle pour effectuer des couplages dans le domaine agricole.
  • Includes bibliographical references.
Publishing information
  • [Ottawa] : Statistics Canada = Statistique Canada, September 8, 2025.
Author / Contributor
  • Arsenault, Christian, 1959- author.
Description1 online resource (8 unnumbered pages) : illustrations.
Catalogue number
  • CS11-522/2024-1-21E-PDF
Departmental catalogue number11-522-X
Subject terms
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