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Extreme Value Index Estimation by Means of an Inequality Curve

1
Department of Economics and Management, University of Trento, 38122 Trento, Italy
2
Department of Economics, University of Verona, 37136 Verona, Italy
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Author to whom correspondence should be addressed.
Mathematics 2020, 8(10), 1834; https://doi.org/10.3390/math8101834
Received: 3 September 2020 / Revised: 1 October 2020 / Accepted: 9 October 2020 / Published: 19 October 2020
(This article belongs to the Section Probability and Statistics Theory)
A characterizing property of Zenga (1984) inequality curve is exploited in order to develop an estimator for the extreme value index of a distribution with regularly varying tail. The approach proposed here has a nice graphical interpretation which provides a powerful method for the analysis of the tail of a distribution. The properties of the proposed estimation strategy are analysed theoretically and by means of simulations. The usefulness of the method will be tested also on real data sets. View Full-Text
Keywords: extreme value index; inequality curve; non-parametric estimation; bootstrap; regularly varying tail extreme value index; inequality curve; non-parametric estimation; bootstrap; regularly varying tail
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MDPI and ACS Style

Taufer, E.; Santi, F.; Novi Inverardi, P.L.; Espa, G.; Dickson, M.M. Extreme Value Index Estimation by Means of an Inequality Curve. Mathematics 2020, 8, 1834. https://doi.org/10.3390/math8101834

AMA Style

Taufer E, Santi F, Novi Inverardi PL, Espa G, Dickson MM. Extreme Value Index Estimation by Means of an Inequality Curve. Mathematics. 2020; 8(10):1834. https://doi.org/10.3390/math8101834

Chicago/Turabian Style

Taufer, Emanuele, Flavio Santi, Pier L. Novi Inverardi, Giuseppe Espa, and Maria M. Dickson. 2020. "Extreme Value Index Estimation by Means of an Inequality Curve" Mathematics 8, no. 10: 1834. https://doi.org/10.3390/math8101834

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