New Reduced-bias Estimators of a Positive Extreme Value Index

作者：Ivette Gomes M; Fatima Brilhante M; Pestana Dinis

来源：Communications in Statistics - Simulation and Computation, 2016, 45(3): 833-862.

DOI：10.1080/03610918.2013.875567

• Bias estimation
• Heavy tails
• Monte Carlo simulation
• Semi-parametric reduced-bias estimation
• Statistics of extremes
• Primary 62G32
• Secondary 65C05

Noting that the classical Hill estimator of a positive extreme value index (EVI) is the logarithm of the mean of order-0 of a set of certain statistics, a more general class of EVI-estimators based on the mean of order-p (MOP), p 0, of such statistics was recently introduced. The asymptotic behavior of the class of MOP EVI-estimators is reviewed, and compared to their reduced-bias MOP (RBMOP) and optimal RBMOP versions, which are suggested here and studied both asymptotically and for finite samples, through a large-scale simulation study. Applications to simulated datasets are also put forward.

• 出版日期2016