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We are Tilburg University

Expertise

John H.J. Einmahl is Arie Kapteyn professor of Statistics at the Department of Econometrics & OR and research fellow at CentER, both at Tilburg University. John's research has been published in leading journals in Statistics and Probability Theory, like the Annals of Statistics, the Annals of Probability, JRSS B, JASA, J. of Econometrics, and Probability Theory and Related Fields. His research interests are mainly in the area of nonparametric statistics and its ramifications, including statistics of extremes, empirical likelihood, generalized and multivariate quantiles, and (local) empirical processes.

John is a fellow of the Institute of Mathematical Statistics and an Associate Editor of Extremes, Econometrics and Statistics, and Statistica Neerlandica. He has been an Associate Editor of The Annals of Statistics, The Annals of Probability, and Bernoulli. He visited Florida State University as a Senior Fulbright Scholar. 

Courses

Recent publications

  1. Improved estimation of the extreme value index using related variables

    Ahmed, H., & Einmahl, J. (2019). Improved estimation of the extreme value index using related variables. Extremes, 22(4), 553-569.
  2. Estimating the maximum possible earthquake magnitude using extreme va…

    Beirlant, J., Kijko, A., Reynkens, T., & Einmahl, J. H. J. (2019). Estimating the maximum possible earthquake magnitude using extreme value methodology: The Groningen case. Natural Hazards, 98(3), 1091-1113.
  3. Limits to human life span through extreme value theory

    Einmahl, J., Einmahl, J., & de Haan, L. F. M. (2019). Limits to human life span through extreme value theory. Journal of the American Statistical Association, 114(527), 1075-1080.
  4. Improved Estimation of the Extreme Value Index Using Related Variables

    Ahmed, H., & Einmahl, J. (2018). Improved Estimation of the Extreme Value Index Using Related Variables. (CentER Discussion Paper; Vol. 2018-025). Tilburg: CentER, Center for Economic Research.
  5. A continuous updating weighted least squares estimator of tail depend…

    Einmahl, J. H. J., Kiriliouk, A., & Segers, J. (2018). A continuous updating weighted least squares estimator of tail dependence in high dimensions. Extremes, 21(2), 205-233.

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