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In this project, we develop a new mathematical framework to efficiently model multivariate systems during extreme events like floods, heatwaves, or financial crashes. This PhD position offers a
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of settings where only parts of a system are extreme. Special attention will be given to parametric families like the Hüsler–Reiss distribution, which lead to an extremal analogue of Gaussian structural causal
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in practice when the dimension of the data-generating process exceeds the sample size, this project will contribute by developing the distributional properties of generalized inverses of the high
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