Statistical inference on a changing extreme value dependence structure
From MaRDI portal
Publication:6183760
DOI10.1214/23-aos2314arXiv2201.06389OpenAlexW4387828490MaRDI QIDQ6183760
Publication date: 4 January 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2201.06389
multivariate regular variationlocal estimationextreme value dependenceintegrated spectral measuretest of nonstationarity
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32)
Cites Work
- Unnamed Item
- An updated review of goodness-of-fit tests for regression models
- Distributionally robust inference for extreme value-at-risk
- Boundary non-crossings of Brownian pillow
- Fitting and validation of a bivariate model for large claims
- Functional nonparametric estimation of conditional extreme quantiles
- Estimating the spectral measure of an extreme value distribution
- Tail behaviour of Gaussian processes with applications to the Brownian pillow.
- Time-varying extreme value dependence with application to leading European stock markets
- Testing the equality of nonparametric regression curves
- Weak convergence and empirical processes. With applications to statistics
- Local robust estimation of the Pickands dependence function
- Estimation of extreme quantiles from heavy-tailed distributions in a location-dispersion regression model
- Nonparametric estimation of the conditional tail copula
- On kernel smoothing for extremal quantile regression
- Estimation of Extreme Conditional Quantiles Through Power Transformation
- Nonparametric regression estimation of conditional tails: the random covariate case
- Spectral Density Ratio Models for Multivariate Extremes
- Statistics of Heteroscedastic Extremes
- Trends in Extreme Value Indices
This page was built for publication: Statistical inference on a changing extreme value dependence structure