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2020 Method of moments estimators for the extremal index of a stationary time series
Axel Bücher, Tobias Jennessen
Electron. J. Statist. 14(2): 3103-3156 (2020). DOI: 10.1214/20-EJS1734

Abstract

The extremal index $\theta $, a number in the interval $[0,1]$, is known to be a measure of primal importance for analyzing the extremes of a stationary time series. New rank-based estimators for $\theta $ are proposed which rely on the construction of approximate samples from the exponential distribution with parameter $\theta $ that is then to be fitted via the method of moments. The new estimators are analyzed both theoretically as well as empirically through a large-scale simulation study. In specific scenarios, in particular for time series models with $\theta \approx 1$, they are found to be superior to recent competitors from the literature.

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Axel Bücher. Tobias Jennessen. "Method of moments estimators for the extremal index of a stationary time series." Electron. J. Statist. 14 (2) 3103 - 3156, 2020. https://doi.org/10.1214/20-EJS1734

Information

Received: 1 December 2019; Published: 2020
First available in Project Euclid: 21 August 2020

zbMATH: 1448.62131
MathSciNet: MR4137597
Digital Object Identifier: 10.1214/20-EJS1734

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Vol.14 • No. 2 • 2020
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