Abstract
Classical extreme value models are families of limit distributions of sample maxima. Now, consider expansions of length two where limit distributions are the leading terms. Such expansions define extended extreme value models.
We will study the asymptotic performance of an adaptive estimator of the scale parameter α in an extended Gumbel model, thus also getting an estimator of the tail index 1/α in a model of Pareto type distributions. Under the present conditions the new estimator is asymptotically superior to those given in literature.
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© 1989 Springer-Verlag Berlin Heidelberg
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Reiss, RD. (1989). Extended Extreme Value Models and Adaptive Estimation of the Tail Index. In: Hüsler, J., Reiss, RD. (eds) Extreme Value Theory. Lecture Notes in Statistics, vol 51. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3634-4_14
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DOI: https://doi.org/10.1007/978-1-4612-3634-4_14
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-96954-1
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