Inference and robust extremes: Yuri Goegebeur
From Belle Taylor on June 28th, 2021
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Name: Yuri Goegebeur
Talk Title: Robust estimation of the conditional stable tail dependence function
Abstract: We consider the estimation of the stable tail dependence function when the variables of main interest are recorded along with a random covariate. In particular we focus on the development of a robust estimator, obtained by locally applying the minimum density power divergence criterion to suitably transformed observations. Under classical regularity conditions, we derive the finite dimensional weak convergence of the estimator, after proper normalisation. The performance of our estimator in terms of efficiency and robustness is illustrated through a small simulation study.
This talk is a contributed talk at EVA 2021.