Detail publikace

Sensitivity Assessment and Comparison of Maxima Methods in the Estimation of Extremal Index

HOLEŠOVSKÝ, J.

Originální název

Sensitivity Assessment and Comparison of Maxima Methods in the Estimation of Extremal Index

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Extremal index is the primary measure of local dependence of extreme values and plays important role in extreme value estimation for stationary processes. The maxima estimators are often preferred in practical situations. These estimators, based on properties of the block maxima, are asymptotically characterized by the Generalized extreme value distribution. In contrast to other methods, the maxima estimators gain advantage in stability to the choice of auxiliary parameters. Still the main part of the maxima methods is selection of a proper approximation to the marginal distribution of the underlying process. Although the suitability of the approximation may significantly affect the estimation quality, to the effect of available approaches has not been paid a great interest in the literature. The aim of this contribution is the comparison of available sampling schemes and the assessment of sensitivity of existing maxima estimates of the extremal index.

Klíčová slova

extreme value; extremal index; stationary series; block maxima; resampling

Autoři

HOLEŠOVSKÝ, J.

Vydáno

18. 12. 2017

Nakladatel

University of Defence

Místo

Brno, Czech Republic

ISBN

978-80-7582-026-6

Kniha

MITAV 2017, Post-Conference Proceedings of Extended Versions of Selected Papers

Strany od

110

Strany do

120

Strany počet

10

URL

BibTex

@inproceedings{BUT142575,
  author="Jan {Holešovský}",
  title="Sensitivity Assessment and Comparison of Maxima Methods in the Estimation of Extremal Index",
  booktitle="MITAV 2017, Post-Conference Proceedings of Extended Versions of Selected Papers",
  year="2017",
  pages="110--120",
  publisher="University of Defence",
  address="Brno, Czech Republic",
  isbn="978-80-7582-026-6",
  url="http://mitav.unob.cz/data/MITAV%202017%20Proceedings.pdf"
}