A noninformative bayesian approach to interval estimation in finite population sampling

Glen Meeden, Stephen Vardeman

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

A noninformative Bayesian approach to interval estimation in finite population sampling is discussed. Given the sample, this method introduces the Polya distribution as a pseudo posterior distribution over the unobserved members of the population. In many cases this distribution yields interval estimates similar to those of standard frequentist theory. In addition, it can be used in situations where the standard methods are difficult to apply, for example, in producing an interval estimate for the ratio of two medians. We also consider related point estimation problems and observe that estimators derived from the pseudo posterior often perform better than classical alternatives. © 1991 Taylor & Francis Group, LLC.

Original languageEnglish (US)
Pages (from-to)972-980
Number of pages9
JournalJournal of the American Statistical Association
Volume86
Issue number416
DOIs
StatePublished - 1991

Keywords

  • Bayesian statistics
  • Finite population sampling
  • Noninformative prior
  • Polya distribution
  • Set estimation
  • Stepwise Bayes

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