On optimising the estimation of high quantiles of a probability distribution
From MaRDI portal
Publication:4454284
DOI10.1080/0233188021000055345zbMath1210.62052OpenAlexW2021284105MaRDI QIDQ4454284
No author found.
Publication date: 8 March 2004
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/0233188021000055345
Asymptotic properties of nonparametric inference (62G20) Statistics of extreme values; tail inference (62G32) Nonparametric statistical resampling methods (62G09)
Related Items
Interval estimation of value-at-risk based on GARCH models with heavy-tailed innovations, Threshold selection in univariate extreme value analysis, A general estimator for the right endpoint with an application to supercentenarian women's records, Bayesian threshold selection for extremal models using measures of surprise, A Mean-of-Order-$$p$$ Class of Value-at-Risk Estimators, Estimation of the extreme-value index and generalized quantile plots, Maximum likelihood estimation of extreme value index for irregular cases, Bootstrapping endpoint, On the estimation of extreme directional multivariate quantiles, Bias reduction in risk modelling: semi-parametric quantile estimation, Semi-parametric second-order reduced-bias high quantile estimation, Extreme Value Theory and Statistics of Univariate Extremes: A Review, On dealing with the unknown population minimum in parametric inference, POT-based estimator of the ruin probability in infinite time for loss models: An application to insurance risk, Inference of high quantiles of a heavy-tailed distribution from block data, Mixed moment estimator and location invariant alternatives, Invited article by M. Gidea: Extreme events and emergency scales, Confidence regions for high quantiles of a heavy tailed distribution, Regularization of nonparametric frontier estimators, Comparing extreme models when the sign of the extreme value index is known, Empirical likelihood confidence intervals for the endpoint of a distribution function, Asymptotic comparison of the mixed moment and classical extreme value index estimators, Bias reduction for high quantiles, Asymptotic Normality of Extreme Quantile Estimators Based on the Peaks-Over-Threshold Approach, A practical method for analysing heavy tailed data, A \(\Gamma\)-moment approach to monotonic boundary estimation, Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate, Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions, Bootstrap and empirical likelihood methods in extremes, Does bias reduction with external estimator of second order parameter work for endpoint?, Modelling extreme claims via composite models and threshold selection methods, Smooth tail-index estimation, Scoring predictions at extreme quantiles, Assessing the performance of confidence intervals for high quantiles of Burr XII and Inverse Burr mixtures, Iterative estimation of the extreme value index
Cites Work
- Unnamed Item
- A moment estimator for the index of an extreme-value distribution
- On the estimation of extreme tail probabilities
- Selecting the optimal sample fraction in univariate extreme value estimation
- On the estimation of high quantiles
- Sur la distribution limite du terme maximum d'une série aléatoire
- The empirical distribution function as a tail estimator
- Fighting the arch–enemy with mathematics‘
- On Smooth Statistical Tail Functionals
- Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
- On the maximal life span of humans
- Using a bootstrap method to choose the sample fraction in tail index estimation
- A bootstrap-based method to achieve optimality in estimating the extreme-value index