A general estimator for the extreme value index: applications to conditional and heteroscedastic extremes
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Publication:497491
DOI10.1007/s10687-015-0220-6zbMath1327.62207OpenAlexW982980915MaRDI QIDQ497491
Publication date: 24 September 2015
Published in: Extremes (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10687-015-0220-6
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30) Statistics of extreme values; tail inference (62G32)
Related Items (10)
Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions ⋮ Efficient estimation of partially linear tail index models using B‐splines ⋮ Estimation of extreme quantiles from heavy-tailed distributions with neural networks ⋮ Simple change point model in heteroscedastic extremes ⋮ Distributions derived from the continuous iteration of the hyperbolic sine function ⋮ Estimation of extreme quantiles from heavy-tailed distributions in a location-dispersion regression model ⋮ Tail dimension reduction for extreme quantile estimation ⋮ Nonparametric confidence intervals for conditional quantiles with large-dimensional covariates ⋮ Trend detection for heteroscedastic extremes ⋮ A nonparametric estimator for the conditional tail index of Pareto-type distributions
Uses Software
Cites Work
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