Numerical comparison between different empirical prediction intervals under the fay-herriot model

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Recently, an empirical best linear unbiased predictor is widely used as a practical approach to small area inference. It is also of interest to construct empirical prediction intervals. However, we do not know which method should be used from among the several existing prediction intervals. In this article, we first obtain an empirical prediction interval by using the residual maximum likelihood method for estimating unknown model variance parameters. Then we compare the later with other intervals with the residual maximum likelihood method. Additionally, some different parametric bootstrap methods for constructing empirical prediction intervals are also compared in a simulation study.

Original languageEnglish
Pages (from-to)1158-1170
Number of pages13
JournalCommunications in Statistics: Simulation and Computation
Volume44
Issue number5
DOIs
Publication statusPublished - May 7 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation

Fingerprint Dive into the research topics of 'Numerical comparison between different empirical prediction intervals under the fay-herriot model'. Together they form a unique fingerprint.

  • Cite this