Subsampling Extremes: From Block Maxima to Smooth Tail Estimation

2012/04/02 by Wager, Stefan · 2 citations
#FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.1204.0316

Abstract

We study a new estimator for the tail index of a distribution in the Frechet domain of attraction that arises naturally by computing subsample maxima. This estimator is equivalent to taking a U-statistic over a Hill estimator with two order statistics. The estimator presents multiple advantages over the Hill estimator. In particular, it has asymptotically smooth sample paths as a function of the threshold k, making it considerably more stable than the Hill estimator. The estimator also admits a simple and intuitive threshold selection rule that does not require fitting a second-order model. Journal of Multivariate Analysis, 130, 2014

Cited by

• A hybrid-Hill estimator enabled by heavy-tailed block maxima
• Design-Life Levels for Environmental Extremes: A Dependence-Aware Block-Maxima Workflow for Severity and Persistence

Related

• Detecting tail behavior: mean excess plots with confidence bounds
• Threshold selection and trimming in extremes
• Trimming the Hill estimator: robustness, optimality and adaptivity
• Modification of Moment-Based Tail Index Estimator: Sums versus Maxima
• Bias Reduced Peaks over Threshold Tail Estimation