Tests of independence and randomness based on the empirical copula process

DOI10.1007/BF02595777zbMath1069.62039OpenAlexW2143512982WikidataQ105583343 ScholiaQ105583343MaRDI QIDQ2387481

Publication date: 5 September 2005

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02595777

zbMATH Keywords

copula empirical process Möbius inversion formula semi-parametric models pseudo-observations serial dependence dependogram tests of independence Cramer-von Mises statistic linear rank statistics

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of parametric tests (62F05)

Related Items

Joint parametric specification checking of conditional mean and volatility in time series models with martingale difference innovations, A Bayesian semiparametric Gaussian copula approach to a multivariate normality test, Testing for Serial Independence: Beyond the Portmanteau Approach, Quantile spectral processes: asymptotic analysis and inference, On coverage limits and deductibles for SAI loss severities, Linking the Hoeffding-sobol and Möbius formulas through a decomposition of Kuo, Sloan, Wasilkowski, and Woźniakowski, A method for constructing higher-dimensional copulas, GSH Dependence Modeling with an Application to Risk Management, Empirical process of concomitants for partly categorial data and applications in statistics, Measurement Error Correction by Exploiting Gene-Environment Independence in Family-Based Case-Control Studies, Stat trek. An interview with Christian Genest, American-style options in jump-diffusion models: estimation and evaluation, Inference for asymptotically independent samples of extremes, The autodependogram: a graphical device to investigate serial dependences, A new test of independence for bivariate observations, Optimal detection of weak positive latent dependence between two sequences of multiple tests, Nonparametric dependence modeling via cluster analysis: A financial contagion application, Multivariate extensions of Spearman's rho and related statistics, A multivariate version of Hoeffding's phi-square, On testing equality of pairwise rank correlations in a multivariate random vector, Asymptotic behavior of weighted multivariate Cramér-von Mises-type statistics under contiguous alternatives, Empirical copulas for consecutive survival data, An independence test based on recurrence rates, Diagnostic tests for non-causal time series with infinite variance, On the estimation of Spearman's rho and related tests of independence for possibly discontinuous multivariate data, Empirical and sequential empirical copula processes under serial dependence, Statistical testing of covariate effects in conditional copula models, A Primer on Copulas for Count Data, On the empirical multilinear copula process for count data, Testing conditional multivariate rank correlations: the effect of institutional quality on factors influencing competitiveness, On the distribution of Gini’s rank association index, A random walk through Canadian contributions on empirical processes and their applications in probability and statistics, New non-parametric tests for independence, Empirical processes for infinite variance autoregressive models, Stochastic declustering of earthquakes with the spatiotemporal renewal ETAS model, Test of bivariate independence based on angular probability integral transform with emphasis on circular-circular and circular-linear data, IPCW approach for testing independence, Distributed testing on mutual independence of massive multivariate data, On the weighted tests of independence based on Bernstein empirical copula, General tests of conditional independence based on empirical processes indexed by functions, A note on testing independence by a copula-based order selection approach, On the Least Squares Estimation of Multiple-Threshold-Variable Autoregressive Models, Testing for independence in high dimensions based on empirical copulas, The weighted characteristic function of the multivariate PIT: independence and goodness-of-fit tests, Tests of independence and randomness for arbitrary data using copula-based covariances, Copula modeling from Abe Sklar to the present day, Autocopulas: investigating the interdependence structure of stationary time series, Tests of serial independence for continuous multivariate time series based on a Möbius decomposition of the independence empirical copula process, A test when the Fisher information may be infinite, exemplified by a test for marginal independence in extreme value distributions, Asymptotics of empirical copula processes under non-restrictive smoothness assumptions, Serial independence tests for innovations of conditional mean and variance models, Nonparametric tests for independence: a review and comparative simulation study with an application to malnutrition data in India, A review of copula models for economic time series, Copula-based semiparametric models for multivariate time series, Independence tests for continuous random variables based on the longest increasing subsequence, Estimating spatial quantile regression with functional coefficients: a robust semiparametric framework, Statistical models and methods for dependence in insurance data, Hierarchical clustering of continuous variables based on the empirical copula process and permutation linkages, Spearman's footrule and Gini's gamma: local bounds for bivariate copulas and the exact region with respect to Blomqvist's beta, General tests of independence based on empirical processes indexed by functions, Unnamed Item, Goodness-of-fit tests for elliptical and independent copulas through projection pursuit, Change detection for uncertain autoregressive dynamic models through nonparametric estimation, A class of multivariate copulas based on products of bivariate copulas, Weak convergence of the weighted empirical beta copula process, Nonparametric tests of independence between random vectors, Asymptotic behavior of the empirical multilinear copula process under broad conditions, Graphical tests of independence for general distributions, Weighted least-squares inference for multivariate copulas based on dependence coefficients, New measure of the bivariate asymmetry, Applications and asymptotic power of marginal-free tests of stochastic vectorial independence, Multivariate conditional versions of Spearman's rho and related measures of tail dependence, Asymptotic local efficiency of Cramér\,-\,von Mises tests for multivariate independence, Spearman's footrule and Gini's gamma: a review with complements, A distribution free test to detect general dependence between a response variable and a covariate in the presence of heteroscedastic treatment effects, Semi-parametric copula-based models under non-stationarity, On the least squares estimation of multiple-regime threshold autoregressive models, Locally most powerful rank tests of independence for copula models, Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions, Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence, Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market, Tests of independence among continuous random vectors based on Cramér-von Mises functionals of the empirical copula process, Theoretical efficiency comparisons of independence tests based on multivariate versions of Spearman's rho, A-dependence statistics for mutual and serial independence of categorical variables, Kendall's 𝒲 Reconsidered, Non-parametric weighted tests for independence based on empirical copula process, Discussion of: Brownian distance covariance, Tests of serial dependence for multivariate time series with arbitrary distributions, Independent block identification in multivariate time series, Combining Cumulative Sum Change‐Point Detection Tests for Assessing the Stationarity of Univariate Time Series, On testing for independence between the innovations of several time series, Unnamed Item, Local efficiency of a Cramér\,-\,von Mises test of independence, Conditional independence testing via weighted partial copulas, Testing independence based on Bernstein empirical copula and copula density, Forecasting time series with multivariate copulas, Diagnostic Tests for Innovations of ARMA Models Using Empirical Processes of Residuals

Cites Work