We propose a method of estimating the endpoint, $\theta$, of a distribution when only limited information is available about the behaviour of the distribution in the neighbourhood of $\theta$. By using increasing numbers of extreme order statistics we obtain an estimator which improves on earlier estimators based on only a bounded number of extremes. In a certain particular model our estimator is equal to a maximum likelihood estimator, but it is robust against departures from this model.
Peter Hall. "On Estimating the Endpoint of a Distribution." Ann. Statist. 10 (2) 556 - 568, June, 1982. https://doi.org/10.1214/aos/1176345796