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On Smooth Statistical Tail Functionals

Citations

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Cited by:

  1. 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.
  2. Svetlana Litvinova & Mervyn J. Silvapulle, 2020. "Consistency of full-sample bootstrap for estimating high-quantile, tail probability, and tail index," Monash Econometrics and Business Statistics Working Papers 15/20, Monash University, Department of Econometrics and Business Statistics.
  3. Jo~ao Nicolau & Paulo M. M. Rodrigues, 2024. "A simple but powerful tail index regression," Papers 2409.13531, arXiv.org.
  4. Drees, Holger & de Haan, Laurens & Li, Deyuan, 2003. "On large deviation for extremes," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 51-62, August.
  5. Drees, Holger & Kaufmann, Edgar, 1998. "Selecting the optimal sample fraction in univariate extreme value estimation," Stochastic Processes and their Applications, Elsevier, vol. 75(2), pages 149-172, July.
  6. Pan, Xiaoqing & Leng, Xuan & Hu, Taizhong, 2013. "The second-order version of Karamata’s theorem with applications," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1397-1403.
  7. Neves, Cláudia & Pereira, António, 2010. "Detecting finiteness in the right endpoint of light-tailed distributions," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 437-444, March.
  8. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
  9. 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.
  10. de Haan, Laurens & Canto e Castro, Luisa, 2006. "A class of distribution functions with less bias in extreme value estimation," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1617-1624, September.
  11. Holger Drees & Laurens F.M. de Haan & Sidney Resnick, 1998. "How to make a Hill Plot," Tinbergen Institute Discussion Papers 98-090/4, Tinbergen Institute.
  12. Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2018. "Tail expectile process and risk assessment," TSE Working Papers 18-944, Toulouse School of Economics (TSE).
  13. Frederico Caeiro & M. Gomes, 2009. "Semi-parametric second-order reduced-bias high quantile estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 392-413, August.
  14. Goedele Dierckx & Yuri Goegebeur & Armelle Guillou, 2021. "Local Robust Estimation of Pareto-Type Tails with Random Right Censoring," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 70-108, February.
  15. El Methni, Jonathan & Stupfler, Gilles, 2018. "Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions," Econometrics and Statistics, Elsevier, vol. 6(C), pages 129-148.
  16. Yaolan Ma & Bo Wei & Wei Huang, 2020. "A nonparametric estimator for the conditional tail index of Pareto-type distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(1), pages 17-44, January.
  17. Cuntz, A. & Haeusler, E. & Segers, J.J.J., 2003. "Edgeworth Expansions for the Distribution Function of the Hill Estimator," Other publications TiSEM 345501c7-c622-4b04-8d27-9, Tilburg University, School of Economics and Management.
  18. Dierckx, Goedele & Goegebeur, Yuri & Guillou, Armelle, 2013. "An asymptotically unbiased minimum density power divergence estimator for the Pareto-tail index," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 70-86.
  19. Wager, Stefan, 2014. "Subsampling extremes: From block maxima to smooth tail estimation," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 335-353.
  20. Einmahl, J.H.J. & Lin, T., 2003. "Asymptotic Normality of Extreme Value Estimators on C[0,1]," Discussion Paper 2003-132, Tilburg University, Center for Economic Research.
  21. Haeusler, E. & Segers, J., 2005. "Assessing Confidence Intervals for the Tail Index by Edgeworth Expansions for the Hill Estimator," Other publications TiSEM e635c476-8fa8-4f16-8760-2, Tilburg University, School of Economics and Management.
  22. Chiapino, Mael & Sabourin, Anne & Segers, Johan, 2018. "Identifying groups of variables with the potential of being large simultaneously," LIDAM Discussion Papers ISBA 2018006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  23. Tertius de Wet & Yuri Goegebeur & Armelle Guillou, 2012. "Weighted Moment Estimators for the Second Order Scale Parameter," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 753-783, September.
  24. Tang, Qihe & Yang, Fan, 2014. "Extreme value analysis of the Haezendonck–Goovaerts risk measure with a general Young function," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 311-320.
  25. Jürg Hüsler & Deyuan Li, 2008. "Weak Convergence of the Empirical Mean Excess Process with Application to Estimate the Negative Tail Index," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 577-593, December.
  26. Bucher, Axel & Segers, Johan, 2015. "Maximum likelihood estimation for the Frechet distribution based on block maxima extracted from a time series," LIDAM Discussion Papers ISBA 2015023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  27. Frederico Caeiro & M. Ivette Gomes & Björn Vandewalle, 2014. "Semi-Parametric Probability-Weighted Moments Estimation Revisited," Methodology and Computing in Applied Probability, Springer, vol. 16(1), pages 1-29, March.
  28. Matheus Henrique Junqueira Saldanha & Adriano Kamimura Suzuki, 2023. "On dealing with the unknown population minimum in parametric inference," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 509-535, September.
  29. Peng, Zuoxiang & Liao, Xin, 2015. "Second-order asymptotics for convolution of distributions with light tails," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 199-208.
  30. Yuri Goegebeur & Armelle Guillou, 2011. "A weighted mean excess function approach to the estimation of Weibull-type tails," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 138-162, May.
  31. Sun, Haoze & Jiang, Yuexiang, 2014. "Empirical likelihood based confidence intervals for the tail index when γ<−1/2," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 149-157.
  32. Stupfler, Gilles & Yang, Fan, 2018. "Analyzing And Predicting Cat Bond Premiums: A Financial Loss Premium Principle And Extreme Value Modeling," ASTIN Bulletin, Cambridge University Press, vol. 48(1), pages 375-411, January.
  33. Geluk, J.L. & de Haan, L.F.M., 2002. "On bootstrap sample size in extreme value theory," Econometric Institute Research Papers EI 2002-40, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  34. Yongcheng Qi, 2010. "On the tail index of a heavy tailed distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(2), pages 277-298, April.
  35. Matthys, Gunther & Delafosse, Emmanuel & Guillou, Armelle & Beirlant, Jan, 2004. "Estimating catastrophic quantile levels for heavy-tailed distributions," Insurance: Mathematics and Economics, Elsevier, vol. 34(3), pages 517-537, June.
  36. S. Cheng & L.F.M. de Haan, 1999. "Penultimate Approximation for Hill's Estimator," Tinbergen Institute Discussion Papers 99-062/4, Tinbergen Institute.
  37. Haoyu Chen & Tiantian Mao & Fan Yang, 2024. "Estimation of the Adjusted Standard-deviatile for Extreme Risks," Papers 2411.07203, arXiv.org.
  38. Cuntz, A. & Haeusler, E. & Segers, J.J.J., 2003. "Edgeworth Expansions for the Distribution Function of the Hill Estimator," Discussion Paper 2003-8, Tilburg University, Center for Economic Research.
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