Observed best prediction for small area counts

Senke Chen, Jiming Jiang, Thuan Nguyen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We extend the observed best prediction (OBP; Jiang, Nguyen, and Rao 2011) method to small area estimation when the responses are counts at the area level. We show via a simulation study that the OBP outperforms the empirical best prediction method when the underlying model is mis-specified. A bootstrap method is proposed for estimating the area-specific mean squared prediction error of the OBP conditioning on the small area mean counts. Two real data examples are considered.

Original languageEnglish (US)
Pages (from-to)136-161
Number of pages26
JournalJournal of Survey Statistics and Methodology
Volume3
Issue number2
DOIs
StatePublished - 2015

Fingerprint

Count
Prediction
Small Area Estimation
Bootstrap Method
Prediction Error
Mean Squared Error
Conditioning
conditioning
Simulation Study
simulation
Model
Bootstrap method
Simulation study
Small area estimation
Prediction error

Keywords

  • Area-specific MSPE
  • Bootstrap
  • OBP
  • Poisson mixed model
  • Small area estimation

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics
  • Statistics, Probability and Uncertainty
  • Social Sciences (miscellaneous)

Cite this

Observed best prediction for small area counts. / Chen, Senke; Jiang, Jiming; Nguyen, Thuan.

In: Journal of Survey Statistics and Methodology, Vol. 3, No. 2, 2015, p. 136-161.

Research output: Contribution to journalArticle

Chen, Senke ; Jiang, Jiming ; Nguyen, Thuan. / Observed best prediction for small area counts. In: Journal of Survey Statistics and Methodology. 2015 ; Vol. 3, No. 2. pp. 136-161.
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