On extreme quantile region estimation under heavy-tailed elliptical distributions
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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20
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Journal of Multivariate Analysis, Volume 202, pp. 1-20
Abstract
Consider the estimation of an extreme quantile region corresponding to a very small probability. Estimation of extreme quantile regions is important but difficult since extreme regions contain only a few or no observations. In this article, we propose an affine equivariant extreme quantile region estimator for heavy-tailed elliptical distributions. The estimator is constructed by extending a well-known univariate extreme quantile estimator. Consistency of the estimator is proved under estimated location and scatter. The practicality of the developed estimator is illustrated with simulations and a real data example.Description
Publisher Copyright: © 2024 The Author(s)
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Pere, J, Ilmonen, P & Viitasaari, L 2024, 'On extreme quantile region estimation under heavy-tailed elliptical distributions', Journal of Multivariate Analysis, vol. 202, 105314, pp. 1-20. https://doi.org/10.1016/j.jmva.2024.105314