✦ LIBER ✦

A general class of estimators of the extreme value index

✍ Scribed by Holger Drees

Publisher: Elsevier Science
Year: 1998
Tongue: English
Weight: 816 KB
Volume: 66
Category: Article
ISSN: 0378-3758
DOI: 10.1016/s0378-3758(97)00076-1

No coin nor oath required. For personal study only.

✦ Synopsis

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" if/q is positive. As a consequence, a widely applicable method lbr the construction of estimators with a prescribed asymptotic behavior is introduced. If [¢ ~< 0 then either T :must be location invariant or it has to satisfy a certain regularity condition on a neighborhood of a constant function to ensure asymptotic normality. It turns out that in this situation location invariant estimators are clearly preferable.

📜 SIMILAR VOLUMES

Double-thresholded estimator of extreme

Double-thresholded estimator of extreme value index

✍ Laurent Gardes 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 112 KB

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

A comparative study of alternative extre

A comparative study of alternative extreme-value volatility estimators

✍ Turan G. Bali; David Weinbaum 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 147 KB

Recent advances in econometric methodology and newly available sources of data are used to examine empirically the performance of the various extreme-value volatility estimators that have been proposed over the past two decades. Overwhelming support is found for the use of extreme-value estimators w

How Large is the Class of Generalized Ex

How Large is the Class of Generalized Extreme Value Random Utility Models?

✍ John K. Dagsvik 📂 Article 📅 1995 🏛 Elsevier Science 🌐 English ⚖ 378 KB

Estimation of probability tails based on

Estimation of probability tails based on generalized extreme value distributions

✍ Maurizio Guida; Maurizio Longo 📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 944 KB

For high reliability devices or structures it is not uncommon that the probabilities to be estimated are lower than 10 -6 . In such cases the standard methods of the empirical fit approach and the counting approach may become impractical. In this paper the estimation problem is handled by extrapolat

A simulation-based hyperparameter select

A simulation-based hyperparameter selection for quantile estimation of the generalized extreme value distribution

✍ Jeong-Soo Park 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 125 KB

Parameter and quantile estimation for th

Parameter and quantile estimation for the generalized extreme-value distribution: a second look

✍ D. J. Dupuis 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 83 KB

The Generalized Extreme Value distribution (GEVD) was introduced by Jenkinson (1955; Quarterly Journal of the Meteorological Society 81, 158±171) as a model for extremes of natural phenomena such as sea level, rainfall, river heights and air pollutants. The GEVD is a three-parameter family with a lo