A0220
Title: Comparative study on tail probability estimators
Authors: Taku Moriyama - Yokohama City University (Japan) [presenting]
Abstract: Tail probability estimators in iid settings are considered. There are mainly two ways for the estimation; the fitting to the generalized Pareto distribution and the fully nonparametric estimation. The fitting estimator is justified by the approximation proven in the extreme value theory; however, the accuracy depends on how extremely large the target is. The nonparametric estimator does not need the approximation and has the advantage of wide applicability. Both theoretical and numerical comparative studies on excess distribution estimation are conducted. Asymptotic convergence rates of estimators are obtained, and the mean integrated squared errors are numerically surveyed by simulation study.
