When uniform weak convergence fails: empirical processes for dependence functions and residuals via epi- and hypographs
DOI10.1214/14-AOS1237zbMath1323.60038arXiv1305.6408OpenAlexW3103006235MaRDI QIDQ464198
Stanislav Volgushev, Axel Bücher, Johan Segers
Publication date: 17 October 2014
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1305.6408
copulabootstrapweak convergencelinear regression\(L^{p}\)-convergencestable tail dependence functionepigraphshypographsresidual empirical process
Linear regression; mixed models (62J05) Central limit and other weak theorems (60F05) Non-Markovian processes: estimation (62M09) Order statistics; empirical distribution functions (62G30) Statistics of extreme values; tail inference (62G32) (L^p)-limit theorems (60F25)
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- Empirical and sequential empirical copula processes under serial dependence
- On the empirical multilinear copula process for count data
- Asymptotics of empirical copula processes under non-restrictive smoothness assumptions
- When uniform weak convergence fails: empirical processes for dependence functions and residuals via epi- and hypographs
- Empirical processes of multidimensional systems with multiple mixing properties
- A note on bootstrap approximations for the empirical copula process
- An empirical central limit theorem with applications to copulas under weak dependence
- An M-estimator for tail dependence in arbitrary dimensions
- Bootstrap approximation of tail dependence function
- Asymptotic local efficiency of Cramér\,-\,von Mises tests for multivariate independence
- Testing for equality between two copulas
- The space D(A) and weak convergence for set-indexed processes
- The empirical distribution function of residuals from generalised regression
- Asymptotic distributions of multivariate rank order statistics
- Best attainable rates of convergence for estimators of the stable tail dependence function
- Weak convergence of empirical copula processes
- Weak convergence of the empirical process of residuals in linear models with many parameters
- Asymptotics of maximum likelihood estimator in a two-phase linear regression model
- On the asymptotics of constrained \(M\)-estimation
- Weak convergence and empirical processes. With applications to statistics
- Asymptotic theory of weakly dependent stochastic processes
- Multiplier bootstrap of tail copulas with applications
- A multivariate Bahadur-Kiefer representation for the empirical Copula process
- Introduction to empirical processes and semiparametric inference
- On some metrics compatible with the Fell-Matheron topology
- Conditional sampling for spectrally discrete max-stable random fields
- A Convergence Theory for Saddle Functions
- The empirical process of autoregressive residuals
- Asymptotic Statistics
- Variational Analysis
- Empirical processes indexed by estimated functions
- Theory of Random Sets
- Convex Analysis
- Asymptotic Behavior of Wilcoxon Type Confidence Regions in Multiple Linear Regression
- On Weak Convergence of Stochastic Processes with Multidimensional Time Parameter
- Convergence Criteria for Multiparameter Stochastic Processes and Some Applications
- Semiparametric estimation in copula models