Dual Divergence Estimators of the Tail Index | Zendy

Salim Bouzebda | Zendy; Mohamed Cherfi | Zendy

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Dual Divergence Estimators of the Tail Index

Author(s) -

Salim Bouzebda,

Mohamed Cherfi

Publication year - 2012

Publication title -

isrn probability and statistics

Language(s) - English

Resource type - Journals

eISSN - 2090-472X

pISSN - 2090-4711

DOI - 10.5402/2012/746203

Subject(s) - estimator , extremum estimator , robustness (evolution) , divergence (linguistics) , influence function , mathematics , duality (order theory) , m estimator , index (typography) , mathematical optimization , computer science , statistics , econometrics , combinatorics , philosophy , world wide web , gene , biochemistry , chemistry , linguistics

The main purpose of the present paper is to propose a new estimator of the tail index using -divergences and the duality technique. These estimators are explored with respect to robustness through the influence function approach. The empirical performances of the proposed estimators are illustrated by simulation.

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