Estimators of the extreme-value index are based on a set of upper order statistics. When the number of upper-order statistics used in the estimation of the extreme-value index is small, the variance of the estimator will be large. On the other hand, the use of a large number of upper statistics will
K-record values and the extreme-value index
โ Scribed by Mohamed Berred
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 422 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0378-3758
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The purpose of this Note is to propose an estimator of the extreme value index constructed by using only the number of points exceeding random thresholds. We prove the weak consistency and the asymptotic normality of this estimator. We deduce from this last result that the rate of convergence of our
We consider the class of estimators of the extreme value index [~ that can be represented as a scale invariant functional T applied to the empirical tail quantile function Q,. From an approximation of Q,, first asymptotic normality of T(Q~) is derived under quite natural smoothness conditions on 7"