Strongly-consistent, distribution-free confidence intervals for quantiles

David Gilat*, T. P. Hill

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Strongly-consistent, distribution-free confidence intervals are derived to estimate the fixed quantiles of an arbitrary unknown distribution, based on order statistics of an iid sequence from that distribution. This new method, unlike classical estimates, works for totally arbitrary (including discontinuous) distributions, and is based on recent one-sided strong laws of large numbers.

Original languageEnglish
Pages (from-to)45-53
Number of pages9
JournalStatistics and Probability Letters
Volume29
Issue number1
DOIs
StatePublished - 15 Aug 1996

Keywords

  • Confidence intervals
  • Empirical distribution function
  • One-sided strong laws
  • Order statistics
  • Quantile estimators
  • Quantile intervals
  • Quantiles
  • Strongly-consistent estimators

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