PUBLICATIONS BY J.G. NEŠLEHOVÁ

Book
  1. E. Cramer & J. Nešlehová (2018). Vorkurs Mathematik, 7th Edition. Springer, Berlin.
Papers in peer-reviewed journals

  1. S. Chatelain, S. Perreault, A.-L. Fougères & J.G. Nešlehová (2025). Clustered Archimax copulas. Electronic Journal of Statistics, 19, 314-360.
  2. C. Genest & J.G. Nešlehová (2025). Asymptotic behavior of the empirical checkerboard copula process for binary data: An educational presentation. Examples and Counterexamples, 7, Article 100176, 5 pp.

  3. C. Genest & J.G. Nešlehová (2024). On the Mai-Wang stochastic decomposition for lp-norm symmetric survival functions on the positive orthant. Journal of Multivariate Analysis, 203, Article 105331, 4 pp.
  4. T. Matys Grygar, U. Radojičić, I. Pavlů, S. Greven, J.G. Nešlehová, Š. Tůmová & K. Hron (2024). Exploratory functional data analysis of multivariate densities for the identification of agricultural soil contamination by risk elements. Journal of Geochemical Exploration, 259, Article 107416, 17 pp.
  5. S. Sun, J.G. Nešlehová & E.E.M. Moodie (2024). Principal stratification for quantile causal effects under partial compliance. Statistics in Medicine, 43, 34-48.

  6. A. Bücher, C. Genest, R.A. Lockhart & J.G. Nešlehová (2023). Asymptotic behavior of an intrinsic rank-based estimator of the Pickands dependence function constructed from B-splines. Extremes, 26, 101-138.
  7. C. Genest, K. Hron & J.G. Nešlehová (2023). Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation. Journal of Multivariate Analysis, 198, Article 105228, 24 pp.
  8. S. Perreault, T. Duchesne & J.G. Nešlehová (2023). Hypothesis tests for structured rank correlation matrices. Journal of the American Statistical Association, 118, 2889-2900.

  9. A.J. McNeil, J.G. Nešlehová & A.D. Smith (2022). On attainability of Kendall's tau matrices and concordance signatures. Journal of Multivariate Analysis, 191, Article 105033, 22 pp.

  10. S. Sun, E.E.M. Moodie & J.G. Nešlehová (2021). Causal inference for quantile treatment effect. Environmetrics, 32 (4), Article e2668.

  11. S. Chatelain, A.-L. Fougères & J.G. Nešlehová (2020). Inference for Archimax copulas. The Annals of Statistics, 48, 1025-1051.

  12. C. Genest, M. Mesfioui & J.G. Nešlehová (2019). On the asymptotic covariance of the multivariate empirical copula process. Dependence Modeling, 7, 279-291.
  13. C. Genest, J.G. Nešlehová, B. Rémillard & O.A. Murphy (2019). Testing for independence in arbitrary distributions. Biometrika, 106, 47-68.
  14. J. Jalbert, O.A. Murphy, C. Genest & J.G. Nešlehová (2019). Modelling extreme rain accumulation with an application to the 2011 Lake Champlain flood. Journal of the Royal Statistical Society, Series C, 68, 831-858.
  15. S. Perreault, T. Duchesne & J.G. Nešlehová (2019). Detection of block-exchangeable structure in large-scale correlation matrices. Journal of Multivariate Analysis, 169, 400-422.
  16. C.-L. Su, J.G. Nešlehová & W. Wang (2019). Modelling hierarchical clustered censored data with the hierarchical Kendall copula. The Canadian Journal of Statistics, 47, 182-203.

  17. C. Genest, J.G. Nešlehová & L.-P. Rivest (2018). The class of multivariate max-id copulas with L1-norm symmetric exponent measure. Bernoulli, 24, 3751-3790.

  18. L.R. Belzile & J.G. Nešlehová (2017). Extremal attractors of Liouville copulas. Journal of Multivariate Analysis, 160, 68-92.
  19. C. Genest, J.G. Nešlehová & B. Rémillard (2017). Asymptotic behavior of the empirical multilinear copula process under broad conditions. Journal of Multivariate Analysis, 159, 82-110.

  20. A. Charpentier, A.-L. Fougères, C. Genest & J.G. Nešlehová (2014). Multivariate Archimax copulas. Journal of Multivariate Analysis, 126, 118-136.
  21. E. Cormier, C. Genest & J.G. Nešlehová (2014). Using B-splines for nonparametric inference on bivariate extreme-value copulas. Extremes, 17, 633-659.
  22. C. Genest & J.G. Nešlehová (2014). On tests of radial symmetry for bivariate copulas. Statistical Papers, 55, 1107-1119.
  23. C. Genest, J.G. Nešlehová & B. Rémillard (2014). On the empirical multilinear copula process for count data. Bernoulli, 20, 1344-1371.

  24. Y. Du, A. Khalili, J. Nešlehová & R.J. Steele (2013). Simultaneous fixed and random effects selection in finite mixture of linear mixed-effects models. The Canadian Journal of Statistics, 41, 596-616.
  25. Y. Du & J. Nešlehová (2013). A moment-based test for extreme-value dependence. Metrika, 76, 673-695.
  26. C. Genest & J. Nešlehová & B. Rémillard (2013). On the estimation of Spearman's rho and related tests of independence for possibly discontinuous multivariate data. Journal of Multivariate Analysis, 117, 214-228.

  27. E.F. Acar, C. Genest & J. Nešlehová (2012). Beyond simplified pair-copula constructions. Journal of Multivariate Analysis, 110, 74-90.
  28. C. Genest, J. Nešlehová & J.-F. Quessy (2012). Tests of symmetry for bivariate copulas. The Annals of the Institute of Statistical Mathematics, 64, 811-834.

  29. C. Genest, I. Kojadinovic, J. Nešlehová & J. Yan (2011). A goodness-of-fit test for bivariate extreme-value copulas. Bernoulli, 17, 253-275.
  30. C. Genest, J. Nešlehová & N. Ben Ghorbal (2011). Estimators based on Kendall's tau in multivariate copula models. The Australian and New Zealand Journal of Statistics, 53, 157-177.
  31. C. Genest, J. Nešlehová & J. Ziegel (2011). Inference in multivariate Archimedean copula models (with discussion). TEST, 20, 223-256
  32. M. Larsson & J. Nešlehová (2011). Extremal behavior of Archimedean copulas. Advances in Applied Probability, 43, 195-216.

  33. A. Feidt, C. Genest & J. Nešlehová (2010). Asymptotics of joint maxima for discontinuous random variables. Extremes, 13, 35-53.
  34. C. Genest, J. Nešlehová & N. Ben Ghorbal (2010). Spearman's footrule and Gini's gamma revisited. Journal of Nonparametric Statistics, 22, 937-954.
  35. A.J. McNeil & J. Nešlehová (2010). From Archimedean to Liouville copulas. Journal of Multivariate Analysis, 101, 1772-1790.

  36. N. Ben Ghorbal, C. Genest & J. Nešlehová (2009). On the Ghoudi, Khoudraji, and Rivest test for extreme-value dependence. The Canadian Journal of Statistics, 37, 534-552.
  37. P. Embrechts, J. Nešlehová & M.V. Wüthrich (2009). Additivity properties for value-at-risk under Archimedean dependence and heavy-tailedness. Insurance: Mathematics and Economics, 44, 164-169.
  38. C. Genest & J. Nešlehová (2009). Analytical proofs of classical inequalities between Spearman's rho and Kendall's tau. Journal of Statistical Planning and Inference, 139, 3795-3798.
  39. A.J. McNeil & J. Nešlehová (2009). Multivariate Archimedean copulas, d-monotone functions and L1-norm symmetric distributions. The Annals of Statistics, 37, 3059-3097.

  40. Z. Landsman & J. Nešlehová (2008). Stein's lemma for elliptical distributions. Journal of Multivariate Analysis, 99, 912-927.

  41. C. Genest & J. Nešlehová (2007). A primer on copulas for count data. The Astin Bulletin, 37, 475-515.
  42. J. Nešlehová (2007). On rank correlation measures for non-continuous random variables. Journal of Multivariate Analysis, 98, 544-567.

  43. V. Chavez-Demoulin, P. Embrechts & J. Nešlehová (2006). Quantitative models for operational risk: Extremes, dependence and aggregation. Journal of Banking and Finance, 30, 2635-2658.
  44. J. Nešlehová, P. Embrechts & V. Chavez-Demoulin (2006). Infinite-mean models and the LDA for operational risk. Journal of Operational Risk, 1, 3-25.

  45. D. Pfeifer & J. Nešlehová (2004). Modeling and generating dependent risk processes for IRM and DFA. The Astin Bulletin, 34, 333-360.

  46. D. Pfeifer & J. Nešlehová (2003). Modeling dependence in finance and insurance: The copula approach. Blätter der deutschen Gesellschaft für Versicherungs- und Finanzmathematik, Bd. XXVI/2.
Papers in books or refereed conference proceedings
  1. C. Genest & J.G. Nešlehová (2017). When Gumbel met Galambos. In Copulas and Dependence Models with Applications: Contributions in Honor of Roger B. Nelsen (M. Úbeda-Flores, E. de Amo-Artero, F. Durante & J. Fernández-Sánchez, Eds.). Springer, Berlin, pp. 83-93.

  2. C. Genest & J. Nešlehová (2014). Modeling dependence beyond correlation. In Statistics in Action: A Canadian Outlook (J.F. Lawless, Ed.), Chapman & Hall, London, pp. 58-78.

  3. C. Genest & J. Nešlehová (2013). Assessing and modeling asymmetry in bivariate continuous data. In Copulae in Mathematical and Quantitative Finance, Proceedings of the Workshop Held in Cracow, 10-11 July 2012 (P. Jaworski, F. Durante & W.K. Härdle, Eds.). Springer, Berlin, pp. 91-114.

  4. C. Genest & J. Nešlehová (2012). Copula modeling for extremes. Encyclopedia of Environmetrics, Second Edition (A.H. El-Shaarawi & W.W. Piegorsch, Eds.). Wiley, Chichester, vol. 2, pp. 530-541.
  5. C. Genest & J. Nešlehová (2012). Copulas and copula models. Encyclopedia of Environmetrics, Second Edition (A.H. El-Shaarawi & W.W. Piegorsch, Eds.). Wiley, Chichester, vol. 2, pp. 541-553.
  6. L.J. Powers, J. Nešlehová & D.A. Stephens (2012). Pricing American options in an infinite activity Lévy market: Monte Carlo and deterministic approaches using a diffusion approximation. In Numerical methods in finance (R.A. Carmona, P. Del Moral, P. Hu & N. Oudjane, Eds.). Springer Proceedings in Mathematics, Volume 12, pp. 291-321.

  7. E. Cramer & J. Nešlehová (2003). (e)Learning the Basics of Probability. Proceedings of the International Statistical Institute, 54th Congress, Berlin.
Other Refereed Contributions: Popular Science Articles

  1. C. Genest & J.G. Nešlehová (2022). Exkurze do světa vyšší dimenze. Pokroky Matematiky, Fyziky a Astronomie, 67 (4), 223-232.

  2. C. Genest & J.G. Nešlehová (2021). Un’escursione nell’universo in alta dimensione. Ithaca: Viaggio nella Scienza, 18B, 177-184.

  3. C. Genest & J.G. Nešlehová (2020). Une excursion dans l'univers en haute dimension. Accromath, 15(2), 8-13.

Other Refereed Contributions: Interviews

  1. C. Genest & J.G. Nešlehová (2020). A conversation with Paul Embrechts. International Statistical Review, 88, 521-547.

  2. C. Genest & J.G. Nešlehová (2014). A conversation with James O. Ramsay. International Statistical Review, 82, 161-183.

Contribution to a discussion

  1. C. Genest, J. Nešlehová & M. Ruppert (2011). Comment on "Statistical models and methods for dependence in insurance data" by S. Haug, C. Klüppelberg & L. Peng. Journal of the Korean Statistical Society, 40, 141-148.
Editorials

  1. J.G. Nešlehová (2022). Editorial as the incoming Editor-In-Chief. The Canadian Journal of Statistics, 50 (1), 5-7.

  2. J.G. Nešlehová, A.-L. Fougères, A.J. McNeil & M. Scherer (2019). Editorial for the Special Issue on dependence models. Journal of Multivariate Analysis, 172, 1-4.

  3. R. Zitikis, E. Furman, A. Necir, J. Nešlehová & M.L. Puri (2010). Editorial for the special issue entitled "Actuarial and Financial Risks: Models, Statistical Inference, and Case Studies." Journal of Probability and Statistics, 2010, 3 pp.

Articles in professional journals
  1. J.G. Nešlehová (2024). CJS Editor's corner. Liaison, 38 (1), 22-26.
  2. J.G. Nešlehová (2024). CJS Editor's corner. Liaison, 38 (2), 12-15.
  3. J.G. Nešlehová (2024). CJS Editor's corner. Liaison, 38 (5), 3-6.
  4. J.G. Nešlehová (2024). CJS Editor's corner. Liaison, 38 (7), 3-6.

  5. J.G. Nešlehová (2023). CJS Editor's corner. Liaison, 37 (1), 8-10.
  6. J.G. Nešlehová (2023). CJS Editor's corner. Liaison, 37 (3), 2-5.

  7. C. Genest & J.G. Nešlehová (2018). François Bellavance: Recipient of the 2018 Lise Manchester Award. Liaison, 32 (3), 13-14.

  8. J.G. Nešlehová (2017). Claudia Klüppelberg (Technische Universität München), Aisenstadt Chair. Bulletin du CRM, 23 (2), 6 + 8.

  9. C. Genest & J. Nešlehová (2013). Königsberg's Bridges, Holland's Dikes and Wall Street's Downfall. Liaison, 27 (3), 56-58.
    [Reprinted in abridged form in the Bulletin du CRM, 19 (2), 11 + 14.]
    [Also reprinted in abridged form in H.G. Kaper & C. Rousseau, Editors (2015). Mathematics of Planet Earth: Mathematicians Reflect on How to Discover, Organize, and Protect Our Planet. Society for Industrial and Applied Mathematics, Philadelphia, PA, pp. 194-196.]
  10. J.G. Nešlehová & A. Singh (2013). Meeting report: New researchers conference. IMS Bulletin, 42 (6), 7.
  11. J.G. Nešlehová & A. Singh (2013). Le 15e congrès annuel des jeunes chercheurs de l'IMS. Bulletin du CRM, 19 (2), 12.
  12. J. Nešlehová (2013). Luke Bornn: Winner of the Pierre Robillard Award. Liaison, 27 (2), 42-43.

  13. C. Genest & J. Nešlehová (2012). James O. Ramsay: Honorary Member of the SSC. Liaison, 26 (3), 24-26.

Scientific reports

  1. J.G. Nešlehová, M. Maathuis, L. Mhalla, P. Naveau (2022). Report on the BIRS workshop 22w5079 Combining Causal Inference and Extreme Value Theory in the Study of Climate Extremes and their Causes held June 26, 2022 - July 1, 2022.

  2. X. Chen, W.K. Härdle, P. Jaworski & J.G. Nešlehová (2015). Copulae: On the Crossroads of Mathematics and Economics. Report No. 20/2015, Mathematisches Forschungsinstitut Oberwolfach, Oberwolfach (Germany) pp. 1085-1088.
Book reviews

  1. J.G. Nešlehová (2016). Review of the book entitled "Quantitative Risk Management: Concepts, Techniques and Tools," Revised Edition, by A.J. McNeil, R. Frey & P. Embrechts. Journal of Time Series Analysis, 37, 431-432.

  2. J. Nešlehová (2007). Review of the book entitled "Fractal-Based Point Processes," by S.B. Lowen & M.C. Teich. Journal of the American Statistical Association, 102, 382-383.

  3. J. Nešlehová (2005). Review of the book entitled "Weibull Models," by P.D.N. Murthy, M. Xie & R. Jiang. Journal of the American Statistical Association, 100, 1094.