Detecting breaks in the dependence of multivariate extreme-value distributions

DOI10.1007/s10687-016-0268-yzbMath1368.62110arXiv1505.00954OpenAlexW1641120366MaRDI QIDQ2363660

Axel Bücher, Paul Kinsvater, Ivan Kojadinovic

Publication date: 25 July 2017

Published in: Extremes (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1505.00954

zbMATH Keywords

copularesamplingPickands dependence functionsequential empirical processeshydrological applicationsmultivariate block maxima

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to environmental and related topics (62P12) Hypothesis testing in multivariate analysis (62H15) Extreme value theory; extremal stochastic processes (60G70)

Related Items (2)

A crossinggram for random fields on lattices ⋮ Testing for equality between conditional copulas given discretized conditioning events

Uses Software

• R
• ggplot2
• copula
• TwoCop
• npcp
• copula
• cowplot

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials
• Detecting changes in cross-sectional dependence in multivariate time series
• A dependent multiplier bootstrap for the sequential empirical copula process under strong mixing
• Testing the constancy of Spearman's rho in multivariate time series
• Homogeneous distributions -- and a spectral representation of classical mean values and stable tail dependence functions
• Asymptotics of empirical copula processes under non-restrictive smoothness assumptions
• Extreme value copula estimation based on block maxima of a multivariate stationary time series
• A goodness-of-fit test for bivariate extreme-value copulas
• An introduction to copulas.
• Construction of asymmetric multivariate copulas
• On the covariance of the asymptotic empirical copula process
• Testing for equality between two copulas
• The asymptotic behavior of some nonparametric change-point estimators
• Weak convergence and empirical processes. With applications to statistics
• TESTING FOR DISTRIBUTIONAL CHANGE IN TIME SERIES
• Structural breaks in time series
• Multivariate Kendall's tau for change-point detection in copulas
• Modelling pairwise dependence of maxima in space
• Bayesian Spatial Modeling of Extreme Precipitation Return Levels
• Statistics of Extremes
• TESTING FOR CHANGES IN KENDALL’S TAU
• A kolmogorov-smirnov type test for positive quadrant dependence

This page was built for publication: Detecting breaks in the dependence of multivariate extreme-value distributions