TwoCop: Nonparametric test of equality between two copulas. This package implements the nonparametric test of equality between two copulas proposed by Remillard and Scaillet in their 2009 JMVA paper: Testing for equality between two copulas. We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Cramér-von Mises test statistic. Finite sample properties are assessed with Monte Carlo experiments. We apply the testing procedure on empirical examples in finance, psychology, insurance and medicine.

References in zbMATH (referenced in 54 articles )

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  1. Bahraoui, Tarik; Kolev, Nikolai: New measure of the bivariate asymmetry (2021)
  2. Beare, Brendan K.; Seo, Juwon: Randomization tests of copula symmetry (2020)
  3. Di Lascio, F. Marta L.; Menapace, Andrea; Righetti, Maurizio: Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach (2020)
  4. Bücher, Axel; Kojadinovic, Ivan: A note on conditional versus joint unconditional weak convergence in bootstrap consistency results (2019)
  5. Kojadinovic, Ivan; Stemikovskaya, Kristina: Subsampling (weighted smooth) empirical copula processes (2019)
  6. Quessy, Jean-François: Consistent nonparametric tests for detecting gradual changes in the marginals and the copula of multivariate time series (2019)
  7. Seo, Juwon: Tests of stochastic monotonicity with improved power (2018)
  8. Berghaus, Betina; Bücher, Axel: Goodness-of-fit tests for multivariate copula-based time series models (2017)
  9. Bücher, Axel; Kinsvater, Paul; Kojadinovic, Ivan: Detecting breaks in the dependence of multivariate extreme-value distributions (2017)
  10. Derumigny, Alexis; Fermanian, Jean-David: About tests of the “simplifying” assumption for conditional copulas (2017)
  11. Genest, Christian; Nešlehová, Johanna G.; Rémillard, Bruno: Asymptotic behavior of the empirical multilinear copula process under broad conditions (2017)
  12. Kojadinovic, Ivan: Some copula inference procedures adapted to the presence of ties (2017)
  13. Plante, Jean-François: Rank correlation under categorical confounding (2017)
  14. Bouzebda, Salim: Some applications of the strong approximation of the integrated empirical copula processes (2016)
  15. Bücher, Axel; Kojadinovic, Ivan: A dependent multiplier bootstrap for the sequential empirical copula process under strong mixing (2016)
  16. Côté, Marie-Pier; Genest, Christian; Abdallah, Anas: Rank-based methods for modeling dependence between loss triangles (2016)
  17. Quessy, Jean-François: A general framework for testing homogeneity hypotheses about copulas (2016)
  18. Fermanian, Jean-David; Radulović, Dragan; Wegkamp, Marten: Asymptotic total variation tests for copulas (2015)
  19. Hobæk Haff, Ingrid; Segers, Johan: Nonparametric estimation of pair-copula constructions with the empirical pair-copula (2015)
  20. Berghaus, Betina; Bücher, Axel: Nonparametric tests for tail monotonicity (2014)

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