Noninformative nonparametric quantile estimation for simple random samples

David Nelson, Glen Meeden

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


For noninformative nonparametric estimation of finite population quantiles under simple random sampling, estimation based on the Polya posterior is similar to estimation based on the Bayesian approach developed by Ericson (J. Roy. Statist. Soc. Ser. B 31 (1969) 195) in that the Polya posterior distribution is the limit of Ericson's posterior distributions as the weight placed on the prior distribution diminishes. Furthermore, Polya posterior quantile estimates can be shown to be admissible under certain conditions. We demonstrate the admissibility of the sample median as an estimate of the population median under such a set of conditions. As with Ericson's Bayesian approach, Polya posterior-based interval estimates for population quantiles are asymptotically equivalent to the interval estimates obtained from standard frequentist approaches. In addition, for small to moderate sized populations, Polya posterior-based interval estimates for quantiles of a continuous characteristic of interest tend to agree with the standard frequentist interval estimates.

Original languageEnglish (US)
Pages (from-to)53-67
Number of pages15
JournalJournal of Statistical Planning and Inference
Issue number1
StatePublished - Jan 1 2006

Bibliographical note

Copyright 2005 Elsevier B.V., All rights reserved.


  • Admissibility
  • Finite population sampling
  • Noninformative inference
  • Nonparametric inference
  • Quantile estimation


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