Estimating extreme quantiles under random truncation

Gardes, Laurent; Stupfler, Gilles

Abstract

The goal of this paper is to provide estimators of the tail index and extreme quantiles of a heavy-tailed random variable when it is right truncated. The weak consistency and asymptotic normality of the estimators are established. The finite sample performance of our estimators is illustrated on a simulation study and we showcase our estimators on a real set of failure data.

Citation

Gardes, L., & Stupfler, G. (2015). Estimating extreme quantiles under random truncation. TEST, 24(2), 207–227. https://doi.org/10.1007/s11749-014-0403-5

• Journal Article Type: Article
• Acceptance Date: Sep 23, 2014
• Online Publication Date: Oct 4, 2014
• Publication Date: 2015-06
• Deposit Date: Jul 6, 2018
• Publicly Available Date: Oct 23, 2018
• Print ISSN: 1133-0686
• Publisher: BMC
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 2
• Pages: 207–227
• DOI: https://doi.org/10.1007/s11749-014-0403-5
• Keywords: Asymptotic normality; Consistency; Extreme quantile; Heavy-tailed distribution; Tail index
• Public URL: https://nottingham-repository.worktribe.com/output/1116699
• Publisher URL: https://link.springer.com/article/10.1007%2Fs11749-014-0403-5
• Additional Information: This is a post-peer-review, pre-copyedit version of an article published in TEST. The final authenticated version is available online at: https://dx.doi.org/10.1007/s11749-014-0403-5.