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Statistics of Multivariate Extremes
International Statistical Review / Revue Internationale de Statistique, 1990Summary: The paper is concerned with statistical aspects of multivariate extreme value distributions. The family is infinite dimensional, so direct parametric estimation is not possible. We describe such nonparametric and parametric approaches, the latter being based on parametric subfamilies.
Smith, R. L., Tawn, J. A., Yuen, H. K.
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2004
We use in the following the theory developed in the preceding chapters to discuss a few nonstandard applications. Of interest are here the statistical estimation of the cluster distribution and of the extremal index in a stationary situation.
Beirlant, J. +3 more
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We use in the following the theory developed in the preceding chapters to discuss a few nonstandard applications. Of interest are here the statistical estimation of the cluster distribution and of the extremal index in a stationary situation.
Beirlant, J. +3 more
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Annual Review of Statistics and Its Application, 2015
Statistics of extremes concerns inference for rare events. Often the events have never yet been observed, and their probabilities must therefore be estimated by extrapolation of tail models fitted to available data. Because data concerning the event of interest may be very limited, efficient methods of inference play an important role.
Davison, Anthony C., Huser, Raphaël
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Statistics of extremes concerns inference for rare events. Often the events have never yet been observed, and their probabilities must therefore be estimated by extrapolation of tail models fitted to available data. Because data concerning the event of interest may be very limited, efficient methods of inference play an important role.
Davison, Anthony C., Huser, Raphaël
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2004
When we model returns using a GARCH process with normally distributed innovations, we have already taken into account the second stylised fact (see Chapter 13.). The distribution of the random returns automatically has a leptokurtosis and larger losses occurring more frequently than under the assumption that the returns are normally distributed. If one
Jürgen Franke +2 more
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When we model returns using a GARCH process with normally distributed innovations, we have already taken into account the second stylised fact (see Chapter 13.). The distribution of the random returns automatically has a leptokurtosis and larger losses occurring more frequently than under the assumption that the returns are normally distributed. If one
Jürgen Franke +2 more
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Dynamics and Statistics of Extreme Events
2010Complex dynamics is characterized by an irregular, non-periodic time dependence of characteristic quantities. Rare fluctuations which lead to unexpectedly large (or small) values are called extreme events. Since such large deviations from the system’s mean behavior have in many applications huge impact, their statistical characterization and their ...
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Anthropogenic intensification of short-duration rainfall extremes
Nature Reviews Earth & Environment, 2021Hayley Fowler +2 more
exaly
Energy insecurity during temperature extremes in remote Australia
Nature Energy, 2021Thomas Longden, Simon Quilty, Brad Riley
exaly