Nonparametric tail estimation using a double bootstrap method.

DOI10.1016/S0167-9473(98)00060-7zbMath1042.62542MaRDI QIDQ1275535

Jef Caers, Jozef Van Dyck

Publication date: 12 January 1999

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Mathematics Subject Classification ID

Statistics of extreme values; tail inference (62G32) Nonparametric statistical resampling methods (62G09)

Related Items (9)

Asymptotic and bootstrap inference for inequality and poverty measures ⋮ Statistical inference in the presence of heavy tails ⋮ Estimation of central shapes of error distributions in linear regression problems ⋮ Statistical learning theory for fitting multimodal distribution to rainfall data: an application ⋮ Estimation of heavy-tailed probability density function with applications to Web data ⋮ Bootstrap and empirical likelihood methods in extremes ⋮ Abelian and Tauberian Theorems on the Bias of the Hill Estimator ⋮ Bootstrap confidence intervals for the pareto index ⋮ On the use of the peaks over thresholds method for estimating out-of-sample quantiles.

Uses Software

• bootstrap

Cites Work

• Unnamed Item
• Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems
• A moment estimator for the index of an extreme-value distribution
• Kernel estimates of the tail index of a distribution
• Estimating tails of probability distributions
• ACORN - A new method for generating sequences of uniformly distributed pseudo-random numbers
• Bootstrap confidence intervals for tail indices.
• Statistical inference using extreme order statistics
• A simple general approach to inference about the tail of a distribution
• Excess functions and estimation of the extreme-value index
• Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. With comments and a rejoinder by the author
• Tail Index Estimation, Pareto Quantile Plots, and Regression Diagnostics

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