Publications dans des revues internationales avec comité de lecture

[60] A. Folcher & J.-F. Quessy (2025). Semiparametric copula-based confidence intervals on level curves: application to the risk level of atmospheric pollutants. Environmetrics 36, e70005

[59] N. Agbangla, J.-F. Quessy & L.-P. Rivest (2025). The family of multivariate beta copulas revisited. The Annals of the Institute of Statistical Mathematics 77, 757-778

[58] J.-F. Quessy (2024). A general construction of multivariate dependence structures with nonmonotone mappings and its applications. Statistical Science 39, 391-408

[57] M. Belalia & J.-F. Quessy (2024). Generalized simulated method-of-moments estimators for multivariate copulas. Statistical Papers 65, 4811–4841

[56] J.-F. Quessy (2024). Gradual change-point analysis based on Spearman matrices for multivariate time series. The Annals of the Institute of Statistical Mathematics 76, 423-446

[55] F. Camirand Lemyre & J.-F. Quessy (2024). Kendall's tau-based inference for gradually changing dependence structures. Statistical Papers 65, 2033-2075

[54] J.-F. Quessy & S. Lemaire-Paquette (2024). The weighted characteristic function of the multivariate PIT: independence and goodness-of-fit tests. Journal of Multivariate Analysis (Special issue «Copula modeling from Abe Sklar to the present day») 201

[53] T. Bahraoui & J.-F. Quessy (2022). Tests of multivariate copula exchangeability based on Lévy measures. Scandinavian Journal of Statistics 49, 1215-1243

[52] J.-F. Quessy (2021). A Szekely-Rizzo inequality for testing general copula homogeneity hypotheses. Journal of Multivariate Analysis 186

[51] J.-F. Quessy & M. Mesfioui (2021). A new family of copula-based concordance orderings of random pairs: properties and nonparametric test. Electronic Journal of Statistics 15, 2393-2429

[50] J.-F. Quessy (2021). On nonparametric tests of multivariate meta-ellipticity. Statistical Papers 62, 2283-2310

[49] T. Bouezmarni, F. Camirand Lemyre & J.-F. Quessy (2019). Inference on local causality and tests of non-causality in time series. Electronic Journal of Statistics 13, 4121-4156

[48] J.-F. Quessy, L.-P. Rivest & M.-H. Toupin (2019). Goodness-of-fit tests for the family of multivariate chi-square copulas. Computational Statistics and Data Analysis 140, 21-40

[47] J.-F. Quessy (2019). Consistent nonparametric tests for detecting gradual changes in the marginals and the copula of multivariate time series. Statistical Papers 60, 367-396

[46] J.-F. Quessy & M. Durocher (2019). The class of copulas arising from squared distributions: Properties and inference. Econometrics & Statistics 12, 148-166

[45] T. Bouezmarni, F. Camirand Lemyre & J.-F. Quessy (2019). On the large-sample behavior of two estimators of the conditional copula under serially dependent data. Metrika 82, 823-841

[44] A. Assani, V. Maloney-Dupont, A. Pothier-Champagne, C. Kinnard & J.-F. Quessy (2019). Comparison of the temporal variability of summer temperature and rainfall as it relates to climate indices in southern Quebec (Canada). Theoretical and Applied Climatology 137, 2425-2435

[43] T. Bahraoui, T. Bouezmarni & J.-F. Quessy (2018). Testing the symmetry of a dependence structure with a characteristic function. Dependence Modeling 6, 331-355

[42] A.-C. Favre, J.-.F. Quessy & M.-H. Toupin (2018). The new family of Fisher copulas to model upper tail dependence and radial asymmetry: properties and application to high-dimensional rainfall data. Environmetrics 29

[41] T. Bahraoui, T. Bouezmarni & J.-F. Quessy (2018). A family of goodness-of-fit tests for copulas based on characteristic functions, Scandinavian Journal of Statistics 45, 301-323