Jackknife method for intermediate quantiles

3Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Peng, L., & Yang, J. (2009). Jackknife method for intermediate quantiles. Journal of Statistical Planning and Inference, 139(7), 2373–2381. https://doi.org/10.1016/j.jspi.2008.10.022

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free