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Best Attainable Rates of Convergence for Estimators of the Stable Tail Dependence Function

Citations

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Cited by:

  1. Einmahl, J.H.J. & Krajina, A. & Segers, J., 2011. "An M-Estimator for Tail Dependence in Arbitrary Dimensions," Other publications TiSEM 27508aa0-9825-4d9e-b1f4-1, Tilburg University, School of Economics and Management.
  2. Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2004. "Weighted Approximations of Tail Copula Processes with Application to Testing the Multivariate Extreme Value Condition," Other publications TiSEM 0b2c1bfa-d609-494a-8929-8, Tilburg University, School of Economics and Management.
  3. Beirlant, Jan & Escobar-Bach, Mikael & Goegebeur, Yuri & Guillou, Armelle, 2016. "Bias-corrected estimation of stable tail dependence function," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 453-466.
  4. Falk, Michael & Reiss, Rolf-Dieter, 2003. "Efficient estimators and LAN in canonical bivariate POT models," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 190-207, January.
  5. Gissibl, Nadine & Klüppelberg, Claudia & Otto, Moritz, 2018. "Tail dependence of recursive max-linear models with regularly varying noise variables," Econometrics and Statistics, Elsevier, vol. 6(C), pages 149-167.
  6. John H. J. Einmahl & Anna Kiriliouk & Andrea Krajina & Johan Segers, 2016. "An M-estimator of spatial tail dependence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 275-298, January.
  7. Asenova, Stefka Kirilova & Mazo, Gildas & Segers, Johan, 2020. "Inference on extremal dependence in a latent Markov tree model attracted to a Husler-Reiss distribution," LIDAM Discussion Papers ISBA 2020005, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  8. Mercadier Cécile & Ressel Paul, 2021. "Hoeffding–Sobol decomposition of homogeneous co-survival functions: from Choquet representation to extreme value theory application," Dependence Modeling, De Gruyter, vol. 9(1), pages 179-198, January.
  9. Di Bernardino, Elena & Maume-Deschamps, Véronique & Prieur, Clémentine, 2013. "Estimating a bivariate tail: A copula based approach," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 81-100.
  10. Einmahl, J.H.J. & de Haan, L.F.M. & Piterbarg, V.I., 2001. "Nonparametric estimation of the spectral measure of an extreme value distribution," Other publications TiSEM c3485b9b-a0bd-456f-9baa-0, Tilburg University, School of Economics and Management.
  11. Einmahl, J.H.J. & Segers, J.J.J., 2008. "Maximum Empirical Likelihood Estimation of the Spectral Measure of an Extreme Value Distribution," Discussion Paper 2008-42, Tilburg University, Center for Economic Research.
  12. Juan-Juan Cai & John H. J. Einmahl & Laurens Haan & Chen Zhou, 2015. "Estimation of the marginal expected shortfall: the mean when a related variable is extreme," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(2), pages 417-442, March.
  13. Kiriliouk, Anna & Segers, Johan & Tafakori, Laleh, 2018. "An estimator of the stable tail dependence function based on the empirical beta copula," LIDAM Discussion Papers ISBA 2018029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  14. Bücher Axel, 2014. "A note on nonparametric estimation of bivariate tail dependence," Statistics & Risk Modeling, De Gruyter, vol. 31(2), pages 151-162, June.
  15. Guzmics Sándor & Pflug Georg Ch., 2020. "A new extreme value copula and new families of univariate distributions based on Freund’s exponential model," Dependence Modeling, De Gruyter, vol. 8(1), pages 330-360, January.
  16. Einmahl, John & Kiriliouk, A. & Segers, J.J.J., 2016. "A Continuous Updating Weighted Least Squares Estimator of Tail Dependence in High Dimensions," Discussion Paper 2016-002, Tilburg University, Center for Economic Research.
  17. Xin Lao & Zuoxiang Peng & Saralees Nadarajah, 2023. "Tail Dependence Functions of Two Classes of Bivariate Skew Distributions," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-24, March.
  18. Benchaira, Souad & Meraghni, Djamel & Necir, Abdelhakim, 2015. "On the asymptotic normality of the extreme value index for right-truncated data," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 378-384.
  19. Mikael Escobar-Bach & Yuri Goegebeur & Armelle Guillou & Alexandre You, 2017. "Bias-corrected and robust estimation of the bivariate stable tail dependence function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 284-307, June.
  20. Krajina, A., 2010. "An M-estimator of multivariate tail dependence," Other publications TiSEM 66518e07-db9a-4446-81be-c, Tilburg University, School of Economics and Management.
  21. Einmahl, John & Segers, Johan, 2020. "Empirical Tail Copulas for Functional Data," Other publications TiSEM edc722e6-cc70-4221-87a2-8, Tilburg University, School of Economics and Management.
  22. Goegebeur, Yuri & Guillou, Armelle & Qin, Jing, 2024. "Dependent conditional tail expectation for extreme levels," Stochastic Processes and their Applications, Elsevier, vol. 171(C).
  23. Einmahl, John & Zhou, C., 2024. "Tail Copula Estimation for Heteroscedastic Extremes," Discussion Paper 2024-003, Tilburg University, Center for Economic Research.
  24. Shuang Hu & Zuoxiang Peng & Johan Segers, 2024. "Modeling multivariate extreme value distributions via Markov trees," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(2), pages 760-800, June.
  25. Ahmed, Hanan & Einmahl, John, 2018. "Improved Estimation of the Extreme Value Index Using Related Variables," Discussion Paper 2018-025, Tilburg University, Center for Economic Research.
  26. Mourahib, Anas & Kiriliouk, Anna & Segers, Johan, 2023. "Multivariate generalized Pareto distributions along extreme directions," LIDAM Discussion Papers ISBA 2023034, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  27. Einmahl, J.H.J. & Khmaladze, E.V., 2007. "Central Limit Theorems For Local Emprical Processes Near Boundaries of Sets," Discussion Paper 2007-66, Tilburg University, Center for Economic Research.
  28. Bücher, Axel & Volgushev, Stanislav & Zou, Nan, 2019. "On second order conditions in the multivariate block maxima and peak over threshold method," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 604-619.
  29. Rootzen, Holger & Segers, Johan & Wadsworth, Jennifer, 2017. "Multivariate generalized Pareto distributions: parametrizations, representations, and properties," LIDAM Discussion Papers ISBA 2017016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  30. Einmahl, J.H.J. & Krajina, A. & Segers, J.J.J., 2007. "A Method of Moments Estimator of Tail Dependence," Other publications TiSEM 6ee60ab8-3c01-4bd9-aa5e-7, Tilburg University, School of Economics and Management.
  31. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
  32. Cai, J., 2012. "Estimation concerning risk under extreme value conditions," Other publications TiSEM a92b089f-bc4c-41c2-b297-c, Tilburg University, School of Economics and Management.
  33. Falk, Michael & Reiss, Rolf Dieter, 2002. "A characterization of the rate of convergence in bivariate extreme value models," Statistics & Probability Letters, Elsevier, vol. 59(4), pages 341-351, October.
  34. Ahmed, Hanan & Einmahl, John & Zhou, Chen, 2021. "Extreme Value Statistics in Semi-Supervised Models," Discussion Paper 2021-007, Tilburg University, Center for Economic Research.
  35. Kiriliouk, Anna & Segers, Johan & Tafakori, Laleh, 2017. "An estimator of the stable tail dependence function based on the empirical beta copula," LIDAM Discussion Papers ISBA 2017028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  36. Mhalla, Linda & Chavez-Demoulin, Valérie & Naveau, Philippe, 2017. "Non-linear models for extremal dependence," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 49-66.
  37. Khader Khadraoui & Pierre Ribereau, 2019. "Bayesian Inference with M-splines on Spectral Measure of Bivariate Extremes," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 765-788, September.
  38. de Haan, Laurens & Neves, Cláudia & Peng, Liang, 2008. "Parametric tail copula estimation and model testing," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1260-1275, July.
  39. Guzmics Sándor & Pflug Georg Ch., 2020. "A new extreme value copula and new families of univariate distributions based on Freund’s exponential model," Dependence Modeling, De Gruyter, vol. 8(1), pages 330-360, January.
  40. Roman Matkovskyy, 2020. "A measurement of affluence and poverty interdependence across countries: Evidence from the application of tail copula," Bulletin of Economic Research, Wiley Blackwell, vol. 72(4), pages 404-416, October.
  41. Ahmed, Hanan, 2022. "Extreme value statistics using related variables," Other publications TiSEM 246f0f13-701c-4c0d-8e09-e, Tilburg University, School of Economics and Management.
  42. Asenova, Stefka & Segers, Johan, 2022. "Extremes of Markov random fields on block graphs," LIDAM Discussion Papers ISBA 2022013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  43. Kiriliouk, Anna, 2020. "Hypothesis testing for tail dependence parameters on the boundary of the parameter space," Econometrics and Statistics, Elsevier, vol. 16(C), pages 121-135.
  44. Segers, Johan, 2012. "Max-Stable Models For Multivariate Extremes," LIDAM Discussion Papers ISBA 2012011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  45. Goix, Nicolas & Sabourin, Anne & Clémençon, Stephan, 2017. "Sparse representation of multivariate extremes with applications to anomaly detection," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 12-31.
  46. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
  47. Krupskii, Pavel & Joe, Harry & Lee, David & Genton, Marc G., 2018. "Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution," Journal of Multivariate Analysis, Elsevier, vol. 163(C), pages 80-95.
  48. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
  49. Michael Falk & Gilles Stupfler, 2021. "The Min-characteristic Function: Characterizing Distributions by Their Min-linear Projections," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 254-282, February.
  50. Rootzén, Holger & Segers, Johan & Wadsworth, Jennifer L., 2018. "Multivariate generalized Pareto distributions: Parametrizations, representations, and properties," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 117-131.
  51. Kiriliouk, Anna, 2017. "Hypothesis testing for tail dependence parameters on the boundary of the parameter space with application to generalized max-linear models," LIDAM Discussion Papers ISBA 2017027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  52. Einmahl, J.H.J. & de Haan, L.F.M. & Li, D., 2006. "Weighted approximations of tail copula processes with applications to testing the bivariate extreme value condition," Other publications TiSEM 18b65ac3-ba79-4bff-ad53-2, Tilburg University, School of Economics and Management.
  53. Hu, Shuang & Peng, Zuoxiang & Segers, Johan, 2022. "Modelling multivariate extreme value distributions via Markov trees," LIDAM Discussion Papers ISBA 2022021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  54. Peng, Liang & Qi, Yongcheng, 2008. "Bootstrap approximation of tail dependence function," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1807-1824, September.
  55. Einmahl, John & Zhou, C., 2024. "Tail Copula Estimation for Heteroscedastic Extremes," Other publications TiSEM 6bcb09c5-8b19-48b8-9320-b, Tilburg University, School of Economics and Management.
  56. Kiriliouk, Anna & Segers, Johan & Warchol, Michal, 2014. "Nonparametric estimation of extremal dependence," LIDAM Discussion Papers ISBA 2014044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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