Yuri Goegebeur Associate Professor, Ph.D. Department of Mathematics and Computer Science (IMADA) University of Southern Denmark Campusvej 55 DK-5230 Odense M Denmark E-mail: yuri.goegebeur(at)imada.sdu.dk Tel: + 45 65 50 44 76 Fax: +45 65 50 23 25 CV

Villum project 'Univariate and multivariate regression on extreme values'

The Villum Foundation awarded a grant of 1883700 Danish Krones to the project `Univariate and Multivariate Regression on Extreme Values'. The project ran over the period March 2014 to March 2018.

Participants

Yuri Goegebeur (University of Southern Denmark)
Armelle Guillou (Strasbourg University)
Mikael Falk (Würzburg University)

Ph.D. Student

Mikael Escobar-Bach, 2014-2017, Ph.D. thesis `Estimation of Dependence Structure for Multivariate Extremes'.

Publications

Escobar-Bach, M., Goegebeur, Y., Guillou, A., 2018. Local robust estimation of the Pickands dependence function. Accepted for publication in Annals of Statistics. paper, supplement

Escobar-Bach, M., Goegebeur, Y., Guillou, A., 2018. Local estimation of the conditional stable tail dependence function. Accepted for publication in Scandinavian Journal of Statistics. paper

Escobar-Bach, M., Goegebeur, Y., Guillou, A., You, A., 2017. Bias-corrected and robust estimation of the bivariate stable tail dependence function. TEST, 26, 284-307. paper

Goegebeur, Y., Guillou, A., Qin, J., 2017. On kernel estimation of the second order rate parameter in multivariate extreme value statistics. Statistics and Probability Letters, 128, 35-43. paper

Goegebeur, Y., Guillou, A., Osmann, M., 2017. A local moment type estimator for an extreme quantile in regression with random covariates. Communications in Statistics - Theory and Methods, 46, 319-343. paper

de Wet, T., Goegebeur, Y., Guillou, A., Osmann, M., 2016. Kernel regression with Weibull-type tails. Annals of the Institute of Statistical Mathematics, 68, 1135-1162. paper

Beirlant, J., Escobar-Bach, M., Goegebeur, Y., Guillou, A., 2016. Bias-corrected estimation of stable tail dependence function. Journal of Multivariate Analysis, 143, 453-466. paper

Dutang, C., Goegebeur, Y., Guillou, A., 2016. Robust and bias-corrected estimation of extreme failure sets. Sankhya A, 78, 52-86. paper

Goegebeur, Y., Guillou, A., Stupfler, G., 2015. Uniform asymptotic properties of a nonparametric regression estimator of conditional tails. Annales de l'Institut Henri Poincar\'e - Probabilit\'es et Statistiques, 51, 1190-1213. paper

Goegebeur, Y., Guillou, A., Osmann, M., 2015. An estimator for the tail index of an integrated conditional Pareto-Weibull-type model. Statistics and Probability Letters, 103, 8-16. paper

Goegebeur, Y., Guillou, A., Rietsch, T., 2015. Robust conditional Weibull-type estimation. Annals of the Institute of Statistical Mathematics, 67, 479-514. paper

Dutang, C., Goegebeur, Y., Guillou, A., 2014. Robust and unbiased estimation of the coefficient of tail dependence. Insurance: Mathematics and Economics, 57, 46-57. paper

Goegebeur, Y., Guillou, A., Osmann, M., 2014. A local moment type estimator for the extreme value index in regression with random covariates. Canadian Journal of Statistics, 42, 487-507. paper

Dierckx, G., Goegebeur, Y., Guillou, A., 2014. Local robust and asymptotically unbiased estimation of conditional Pareto-type tails. TEST, 23, 330-355. paper, Appendix

Goegebeur, Y., Guillou, A., Schorgen, A., 2014. Nonparametric regression estimation of conditional tails - the random covariate case. Statistics, 48, 732-755. paper

Goegebeur, Y., Guillou, A., Verster, A., 2014. Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions. Statistics and Probability Letters, 87, 108-114. paper

R Package

RTDE Package: robust tail dependence estimation for bivariate models.