Transforming response values in small area prediction

Shonosuke Sugasawa, Tatsuya Kubokawa

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

In real applications of small area estimation, one often encounters data with positive response values. The use of a parametric transformation for positive response values in the Fay–Herriot model is proposed for such a case. An asymptotically unbiased small area predictor is derived and a second-order unbiased estimator of the mean squared error is established using the parametric bootstrap. Through simulation studies, a finite sample performance of the proposed predictor and the MSE estimator is investigated. The methodology is also successfully applied to Japanese survey data.

Original languageEnglish
Pages (from-to)47-60
Number of pages14
JournalComputational Statistics and Data Analysis
Volume114
DOIs
Publication statusPublished - 2017 Oct
Externally publishedYes

Keywords

  • Dual power transformation
  • Empirical Bayes estimation
  • Fay–Herriot model
  • Mean squared error
  • Positive-valued data
  • Small area estimation

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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