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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" }