Statistics of extremes under random censoring
Copyright policy )Statistics of extremes under random censoring
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.
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)
- Sorbonne University France
- Laboratoire de Probabilités, Statistique et Modélisation France
- French National Centre for Scientific Research France
- Tilbury University Netherlands
- UNIVERSITE PARIS DESCARTES France
Censored data models, Statistics of extreme values; tail inference, asymptotic normality, extreme value index, Mathematics - Statistics Theory, Statistics Theory (math.ST), random censoring, Applications of statistics to biology and medical sciences; meta analysis, extreme quantiles, Asymptotic normality;extreme value index;extreme quantiles;random censoring, FOS: Mathematics, Asymptotic normality, Asymptotic normality; extreme value index; extreme quantiles; random censoring, jel: jel:C41, jel: jel:C13, jel: jel:C14
Censored data models, Statistics of extreme values; tail inference, asymptotic normality, extreme value index, Mathematics - Statistics Theory, Statistics Theory (math.ST), random censoring, Applications of statistics to biology and medical sciences; meta analysis, extreme quantiles, Asymptotic normality;extreme value index;extreme quantiles;random censoring, FOS: Mathematics, Asymptotic normality, Asymptotic normality; extreme value index; extreme quantiles; random censoring, jel: jel:C41, jel: jel:C13, jel: jel:C14
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