In this paper we consider the estimation problem for high quantiles of a heavy-tailed distribution from block data when only a few largest values are observed within blocks. We propose estimators for high quantiles and prove that these estimators are asymptotically normal. Furthermore, we employ empirical likelihood method and adjusted empirical likelihood method to constructing the confidence intervals of high quantiles. Through a simulation study we also compare the performance of the normal approximation method and the adjusted empirical likelihood methods in terms of the coverage probability and length of the confidence intervals.

翻译：在本文中,我们考虑在区块内只观测到几个最大值时,从区块数据中进行重尾分布的高量化的估算问题。我们建议对高量化的估算值进行估算,并证明这些估算值无损正常。此外,我们采用经验概率方法和经调整的经验概率方法来构建高量化的置信间隔。通过模拟研究,我们还比较了正常近似方法的性能和经调整的经验概率方法在信任间隔的覆盖概率和长度方面的情况。