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Elemental estimators for the Generalized Extreme Value tail

McRobie, FA (2013) Elemental estimators for the Generalized Extreme Value tail.

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In a companion paper (McRobie(2013) arxiv:1304.3918), a simple set of `elemental' estimators was presented for the Generalized Pareto tail parameter. Each elemental estimator: involves only three log-spacings; is absolutely unbiased for all values of the tail parameter; is location- and scale-invariant; and is valid for all sample sizes $N$, even as small as $N= 3$. It was suggested that linear combinations of such elementals could then be used to construct efficient unbiased estimators. In this paper, the analogous mathematical approach is taken to the Generalised Extreme Value (GEV) distribution. The resulting elemental estimators, although not absolutely unbiased, are found to have very small bias, and may thus provide a useful basis for the construction of efficient estimators.

Item Type: Article
Divisions: Div D > Structures
Depositing User: Unnamed user with email
Date Deposited: 09 Dec 2016 18:17
Last Modified: 27 Apr 2017 05:17