Jackknife method for intermediate quantiles

  • Peng L
  • Yang J
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Abstract

Quantile function plays an important role in statistical inference, and intermediate quantile is useful in risk management. It is known that Jackknife method fails for estimating the variance of a sample quantile. By assuming that the underlying distribution satisfies some extreme value conditions, we show that Jackknife variance estimator is inconsistent for an intermediate order statistic. Further we derive the asymptotic limit of the Jackknife-Studentized intermediate order statistic so that a confidence interval for an intermediate quantile can be obtained. A simulation study is conducted to compare this new confidence interval with other existing ones in terms of coverage accuracy. © 2009 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Coverage probability
  • Extreme value index
  • Intermediate quantile
  • Jackknife

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Authors

  • Liang Peng

  • Jingping Yang

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