Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149587 | Journal of Statistical Planning and Inference | 2009 | 9 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Liang Peng, Jingping Yang,