Supervised network prediction for household statistics

Producing census-like household statistics is possible based on relevant data originated from the administrative sources. However, address registration errors generally cause biased results. Under the assumption that households can be identified by survey at a sample of addresses, we develop a supervised network prediction approach to households at the out-of-sample addresses. An application to real data from the Norwegian Household Register is used to demonstrate the advantages of the proposed modelling approach over the existing practical alternatives.

• Publication year

  2025

• Venue

  Journal of the Royal Statistical Society: Series A (Statistics in Society)

• Publication date

  2025-11-10

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1093/jrsssa/qnaf181
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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