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Strongly-Consistent, Distribution-Free Confidence Intervals for Quantiles
Statistics and Probability Letters
  • David Gilat, Tel Aviv University
  • Theodore P. Hill, Georgia Institute of Technology - Main Campus
Publication Date
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.
Citation Information
David Gilat and Theodore P. Hill. "Strongly-Consistent, Distribution-Free Confidence Intervals for Quantiles" Statistics and Probability Letters Vol. 29 Iss. 1 (1996) p. 45 - 53
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