STATISTICS SEMINAR:: Confidence Intervals for High Quantiles of A Heavy Tailed Distribution

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Estimating high quantiles plays an important role in the context of risk management. This involves extrapolation of an unknown distribution function beyond observations. Under consideration is construsting confidence intervals for high quantiles of a heavy tailed distribution. In this talk we introduce three methods, including the normal approximation method based on Hill's estimator, the likelihood ratio method and the data tilting method. Our simulation study shows that the data tilting method has a better performance in terms of the accuracy of coverage probabilities.


  • Workflow Status: Published
  • Created By: Barbara Christopher
  • Created: 10/08/2010
  • Modified By: Fletcher Moore
  • Modified: 10/07/2016


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