a two step subsample bootstrap method. This method adaptively determines the sample fraction that minimizes the …

a two step subsample bootstrap method. This method adaptively determines the sample fraction that minimizes the …

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the sample …

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

shape estimates are inefficient unless the threshold is accurately determined. We will apply bootstrap methodology to select …

(derived from our threshold estimator) we overcome the bias problems of the usual tail index estimators (Hill or Pickands). The …

-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than … in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias …