English

Elemental unbiased estimators for the Generalized Pareto tail

Statistics Theory 2013-04-16 v1 Statistics Theory

Abstract

Unbiased location- and scale-invariant `elemental' estimators for the GPD tail parameter are constructed. Each involves three log-spacings. The estimators are unbiased for finite sample sizes, even as small as N=3. It is shown that the elementals form a complete basis for unbiased location- and scale-invariant estimators constructed from linear combinations of log-spacings. Preliminary numerical evidence is presented which suggests that elemental combinations can be constructed which are consistent estimators of the tail parameter for samples drawn from the pure GPD family.

Cite

@article{arxiv.1304.3918,
  title  = {Elemental unbiased estimators for the Generalized Pareto tail},
  author = {Allan McRobie},
  journal= {arXiv preprint arXiv:1304.3918},
  year   = {2013}
}

Comments

15 pages, 7 figures

R2 v1 2026-06-21T23:59:20.814Z