Abstract
This work considers estimators of the tails of the cdf, quantile function and edf, which are generally applicable because they use only those observations in the sample which exceed a high threshold value. Three seemingly different approaches have been proposed by Hill (1975), Hall (1982), and Pickands (1975). Herein the tail behavior of the underlying probability model is expressed using the density-quantile function. This general tail behavior model is shown to be a common origin for the parametric models proposed by Hill, Hall, and Pickands' GPD model. Further, this tail behavior model motivates a representation for the quantile function of the exceedences which is used to obtain a parametric model for tail estimates using the exceedences which unifies the seemingly different tail estimators mentioned above.
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