Publication detail

Estimation of the extremal index using censored distributions

HOLEŠOVSKÝ, J. FUSEK, M.

Original Title

Estimation of the extremal index using censored distributions

Type

journal article in Web of Science

Language

English

Original Abstract

The extremal index is an important parameter in the characterization of extreme values of a stationary sequence, since it measures short-range dependence at extreme values and governs clustering of extremes. This paper presents a novel approach to estimation of the extremal index based on artificial censoring of inter-exceedance times. The censored estimator based on the maximum likelihood method is derived together with its variance, which is estimated from the expected Fisher information measure. In order to evaluate performance of the proposed estimator, a simulation study is carried out for various stationary processes satisfying the local dependence condition $D^{(k)}(u_n)$. An application to daily maximum temperatures at Uccle, Belgium, is also presented.

Keywords

Extremal index; Extreme value theory; Censoring; Clusters

Authors

HOLEŠOVSKÝ, J.; FUSEK, M.

Released

25. 5. 2020

Publisher

Springer

Location

Berlin

ISBN

1386-1999

Periodical

EXTREMES

Year of study

23

Number

2

State

United States of America

Pages from

197

Pages to

213

Pages count

17

URL

https://link.springer.com/article/10.1007/s10687-020-00374-3

BibTex

@article{BUT161099,
  author="Jan {Holešovský} and Michal {Fusek}",
  title="Estimation of the extremal index using censored distributions",
  journal="EXTREMES",
  year="2020",
  volume="23",
  number="2",
  pages="197--213",
  doi="10.1007/s10687-020-00374-3",
  issn="1386-1999",
  url="https://link.springer.com/article/10.1007/s10687-020-00374-3"
}