Detail publikace

Use of censored distribution in the intervals estimator of the extremal index

HOLEŠOVSKÝ, J. FUSEK, M.

Originální název

Use of censored distribution in the intervals estimator of the extremal index

Typ

abstrakt

Jazyk

angličtina

Originální abstrakt

From the theory it follows that the local dependence in a stationary series causes clustering of extreme values. Hence, the inference for extremes typically requires proper identification of clusters of high threshold exceedances and estimation of the extremal index which is the primary measure of the local dependence. An intervals estimator of the extremal index based on the distribution of interexceedances times has been previously introduced. Direct application of the limiting distribution to interexceedances times of a stationary series may cause the intervals estimator to be biased toward independence. Several modifications have been proposed including the $K$-gaps likelihood estimator, where $K$ determines the intra- and intercluster spacings. The aim is to introduce a new estimator of the extremal index based on censored distributions that can be viewed as an alternative to the $K$-gaps estimator without using fixed replacements of the intracluster spacings. Properties of the estimator are studied using simulations. The main benefit lies in reducing the bias of the estimates, especially when large clusters are present in the series.

Klíčová slova

clustering; extreme values; interval censoring; maximum likelihood; time series

Autoři

HOLEŠOVSKÝ, J.; FUSEK, M.

Vydáno

14. 12. 2018

Nakladatel

ECOSTA Econometrics and Statistics

Místo

Pisa, Italy

ISBN

978-9963-2227-5-9

Kniha

CFE-CM Statistics 2018, Book of Abstracts

Strany od

155

Strany do

155

Strany počet

1

URL

BibTex

@misc{BUT152126,
  author="Jan {Holešovský} and Michal {Fusek}",
  title="Use of censored distribution in the intervals estimator of the extremal index",
  booktitle="CFE-CM Statistics 2018, Book of Abstracts",
  year="2018",
  pages="155--155",
  publisher="ECOSTA Econometrics and Statistics",
  address="Pisa, Italy",
  isbn="978-9963-2227-5-9",
  url="http://www.cmstatistics.org/CMStatistics2018/docs/BoACFECMStatistics2018.pdf?20181120232255",
  note="abstract"
}