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. Sun, J.G. Nešlehová & E.E.M. Moodie (2023). Principal stratification for quantile causal effects under partial compliance. Statistics in Medicine, in press.
  2. 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, 105228.
  3. 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, in press.
  4. S. Perreault, T. Duchesne & J.G. Nešlehová (2023). Hypothesis tests for structured rank correlation matrices. Journal of the American Statistical Association, in press.

  5. 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.

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

  7. S. Chatelain, A.-L. Fougères & J.G. Nešlehová (2020). Inference for Archimax copulas. The Annals of Statistics, 48, 1025-1051.
  8. C. Genest & J.G. Nešlehová (2020). A conversation with Paul Embrechts. International Statistical Review, 88, 521-547.
  9. C. Genest & J.G. Nešlehová (2020). Une excursion dans l'univers en haute dimension. Accromath, 15(2), 8-13.

  10. C. Genest, M. Mesfioui & J.G. Nešlehová (2019). On the asymptotic covariance of the multivariate empirical copula process. Dependence Modeling, 7, 279-291.
  11. C. Genest, J.G. Nešlehová, B. Rémillard & O.A. Murphy (2019). Testing for independence in arbitrary distributions. Biometrika, 106, 47-68.
  12. 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.
  13. 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.
  14. 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.

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

  16. L.R. Belzile & J.G. Nešlehová (2017). Extremal attractors of Liouville copulas. Journal of Multivariate Analysis, 160, 68-92.
  17. 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.

  18. A. Charpentier, A.-L. Fougères, C. Genest & J.G. Nešlehová (2014). Multivariate Archimax copulas. Journal of Multivariate Analysis, 126, 118-136.
  19. E. Cormier, C. Genest & J.G. Nešlehová (2014). Using B-splines for nonparametric inference on bivariate extreme-value copulas. Extremes, 17, 633-659.
  20. C. Genest & J.G. Nešlehová (2014). On tests of radial symmetry for bivariate copulas. Statistical Papers, 55, 1107-1119.
  21. C. Genest & J.G. Nešlehová (2014). A conversation with James O. Ramsay. International Statistical Review, 82, 161-183.
  22. C. Genest, J.G. Nešlehová & B. Rémillard (2014). On the empirical multilinear copula process for count data. Bernoulli Journal, 20, 1344-1371.

  23. 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.
  24. Y. Du & J. Nešlehová (2013). A moment-based test for extreme-value dependence. Metrika, 76, 673-695.
  25. 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.

  26. E.F. Acar, C. Genest & J. Nešlehová (2012). Beyond simplified pair-copula constructions. Journal of Multivariate Analysis, 110, 74-90.
  27. 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.

  28. C. Genest, I. Kojadinovic, J. Nešlehová & J. Yan (2011). A goodness-of-fit test for bivariate extreme-value copulas. Bernoulli Journal, 17, 253-275.
  29. 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.
  30. C. Genest, J. Nešlehová & J. Ziegel (2011). Inference in multivariate Archimedean copula models (with discussion). TEST, 20, 223-256
  31. M. Larsson & J. Nešlehová (2011). Extremal behavior of Archimedean copulas. Advances in Applied Probability, 43, 195-216.

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

  35. 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.
  36. 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.
  37. 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.
  38. A.J. McNeil & J. Nešlehová (2009). Multivariate Archimedean copulas, d-monotone functions and L1-norm symmetric distributions. The Annals of Statistics, 37, 3059-3097.

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

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

  42. 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.
  43. J. Nešlehová, P. Embrechts & V. Chavez-Demoulin (2006). Infinite-mean models and the LDA for operational risk. Journal of Operational Risk, 1, 3-25.

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

  45. 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. Book chapter for Numerical methods in finance (R.A. Carmona, P. Del Moral, P. Hu & N. Oudjane, Eds.). Springer Proceedings in Mathematics, Volume 12, 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 (2021). Un’escursione nell’universo in alta dimensione. Ithaca: Viaggio nella Scienza, 18B, 177-184.
  2. C. Genest & J. Nešlehová (2020). Une excursion dans l'univers en haute dimension. Accromath, 15 (2), 8-13.

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

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

  3. C. Genest & J. Nešlehová (2013). Königsberg's Bridges, Holland's Dikes and Wall Street's Downfall / Les ponts de Königsberg, les digues de Hollande et la chute de Wall Street. 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.]
  4. J.G. Nešlehová & A. Singh (2013). Meeting report: New researchers conference. IMS Bulletin, 42 (6), 7.
  5. J.G. Nešlehová & A. Singh (2013). Le 15e congrès annuel des jeunes chercheurs de l'IMS. Bulletin du CRM, 19 (2), 12.
  6. J. Nešlehová (2013). Luke Bornn: Winner of the Pierre Robillard Award / Lauréat du prix Prix Pierre-Robillard. Liaison, 27 (2), 42-43.

  7. C. Genest & J. Nešlehová (2012). James O. Ramsay: Honorary Member of the SSC / Membre honoraire de la SSC. Liaison, 26 (3), 24-26.

Scientific report

  1. 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.