Small area estimation with mixed models: a review

Shonosuke Sugasawa, Tatsuya Kubokawa

研究成果: Article査読

11 被引用数 (Scopus)

抄録

Small area estimation is recognized as an important tool for producing reliable estimates under limited sample information. This paper reviews techniques of small area estimation using mixed models, covering from basic to recently proposed advanced ones. We first introduce basic mixed models for small area estimation, and provide several methods for computing mean squared errors and confidence intervals which are important for measuring uncertainty of small area estimators. Then we provide reviews of recent development and techniques in small area estimation. This paper could be useful not only for researchers who are interested in details on the methodological research in small area estimation, but also for practitioners who might be interested in the application of the basic and new methods.

本文言語English
ページ(範囲)693-720
ページ数28
ジャーナルJapanese Journal of Statistics and Data Science
3
2
DOI
出版ステータスPublished - 2020 12月
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 計算理論と計算数学

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