Bias correction in multivariate extremes
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Publication:2343968
DOI10.1214/14-AOS1305zbMath1312.62061arXiv1504.00490MaRDI QIDQ2343968
Cécile Mercadier, Anne-Laure Fougères, Laurens De Haan
Publication date: 11 May 2015
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1504.00490
Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32)
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Cites Work
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- Adapting extreme value statistics to financial time series: dealing with bias and serial dependence
- A method of moments estimator of tail dependence in meta-elliptical models
- Asymptotically unbiased estimators for the extreme-value index
- Semi-parametric estimation for heavy tailed distributions
- New estimators of the Pickands dependence function and a test for extreme-value dependence
- An M-estimator for tail dependence in arbitrary dimensions
- A method of moments estimator of tail dependence
- Adaptive estimates of parameters of regular variation
- Families of min-stable multivariate exponential and multivariate extreme value distributions
- Estimating the spectral measure of an extreme value distribution
- Semi-parametric estimation of the second order parameter in statistics of extremes
- Estimation of a bivariate extreme value distribution
- Bivariate distributions with given extreme value attractor
- Estimating the probability of a rare event
- Bias-reduced estimators for bivariate tail modelling
- Bias correction in extreme value statistics with index around zero
- Non-parametric estimators of multivariate extreme dependence functions
- The t Copula and Related Copulas
- Reduced-Bias Tail Index Estimators Under a Third-Order Framework
- Tail Index Estimation for Heavy-Tailed Models: Accommodation of Bias in Weighted Log-Excesses
- Point processes, regular variation and weak convergence
- Bivariate extreme value theory: Models and estimation
- Statistics for near independence in multivariate extreme values
- Estimating the limit distribution of multivariate extremes
- Comparison of Approaches for Estimating the Probability of Coastal Flooding
- Statistics of Extremes
- Asymptotically Unbiased Estimation of the Coefficient of Tail Dependence
- Projection estimators of Pickands dependence functions
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