A new partially reduced-bias mean-of-order p class of extreme value index estimators

作者：Gomes M Ivette^*; Brilhante M Fatima; Caeiro Frederico; Pestana Dinis

来源：Computational Statistics & Data Analysis, 2015, 82: 223-237.

DOI：10.1016/j.csda.2014.08.017

• Bias estimation
• Heavy right-tails
• Heuristic methods
• Optimal levels
• Semi-parametric estimation
• Statistics of extremes

A class of partially reduced-bias estimators of a positive extreme value index (EVI), related to a mean-of-order-p class of EVI-estimators, is introduced and studied both asymptotically and for finite samples through a Monte-Carlo simulation study. A comparison between this class and a representative class of minimum-variance reduced-bias (MVRB) EVI-estimators is further considered. The MVRB EVI-estimators are related to a direct removal of the dominant component of the bias of a classical estimator of a positive EVI, the Hill estimator, attaining as well minimal asymptotic variance. Heuristic choices for the tuning parameters p and k, the number of top order statistics used in the estimation, are put forward, and applied to simulated and real data.

• 出版日期2015-2