Statistics of extremes under random censoring
Statistics Theory
2008-12-18 v1 Statistics Theory
Abstract
We investigate the estimation of the extreme value index when the data are subject to random censorship. We prove, in a unified way, detailed asymptotic normality results for various estimators of the extreme value index and use these estimators as the main building block for estimators of extreme quantiles. We illustrate the quality of these methods by a small simulation study and apply the estimators to medical data.
Cite
@article{arxiv.0803.2162,
title = {Statistics of extremes under random censoring},
author = {John H. J. Einmahl and Amélie Fils-Villetard and Armelle Guillou},
journal= {arXiv preprint arXiv:0803.2162},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.3150/07-BEJ104 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)