WEIGHTED LEAST-SQUARES ESTIMATORS OF TAIL INDICES
Abstract: We propose a class of weighted least-squares estimators for the tail index of a
regularly varying upper tail of a distribution. Universal asymptotic normality of the
estimators is established over the whole model. Asymptotic mean square errors of these and
earlier estimators are compared within a submodel of regular variation, more general than
Hall’s model. We also discuss the choice of the optimal weights and the choice of the number
of extreme order statistics to be used.
1991 AMS Mathematics Subject Classification: Primary: -; Secondary: -;
Key words and phrases: -