Detail publikace

Estimation of the extremal index using censored distributions

HOLEŠOVSKÝ, J. FUSEK, M.

Originální název

Estimation of the extremal index using censored distributions

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Extremal index; Extreme value theory; Censoring; Clusters

Autoři

HOLEŠOVSKÝ, J.; FUSEK, M.

Vydáno

25. 5. 2020

Nakladatel

Springer

Místo

Berlin

ISSN

1386-1999

Periodikum

EXTREMES

Ročník

23

Číslo

2

Stát

Spojené státy americké

Strany od

197

Strany do

213

Strany počet

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"
}