Estimation of the extreme-value index and generalized quantile plots

replacing the Zipf plot by a generalized quantile plot. We make an asymptotic comparison of our estimator with the moment estimator and with the maximum likelihood estimator. A case study illustrates our findings. Finally, we offer a regression model that generalizes the ERM in that it allows the construction of bias-reduced estimators. Moreover, the model provides an adaptive selection rule for the number of extremes needed in several of the existing estimators.

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