A New Class of Reduced-Bias Generalized Hill Estimators.
| Title: | A New Class of Reduced-Bias Generalized Hill Estimators. |
|---|---|
| Authors: | Henriques-Rodrigues, Lígia1 (AUTHOR) ligiahr@uevora.pt, Caeiro, Frederico2 (AUTHOR) fac@fct.unl.pt, Gomes, M. Ivette3 (AUTHOR) migomes@ciencias.ulisboa.pt |
| Source: | Mathematics (2227-7390). Sep2024, Vol. 12 Issue 18, p2866. 18p. |
| Subject Terms: | *MONTE Carlo method, *EXTREME value theory, *ESTIMATION bias, *VALUATION of real property, *RISK assessment |
| Abstract: | The estimation of the extreme value index (EVI) is a crucial task in the field of statistics of extremes, as it provides valuable insights into the tail behavior of a distribution. For models with a Pareto-type tail, the Hill estimator is a popular choice. However, this estimator is susceptible to bias, which can lead to inaccurate estimations of the EVI, impacting the reliability of risk assessments and decision-making processes. This paper introduces a novel reduced-bias generalized Hill estimator, which aims to enhance the accuracy of EVI estimation by mitigating the bias. [ABSTRACT FROM AUTHOR] |
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| Database: | Academic Search Complete |
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