• Warandelaan 2, Prisma Building, room P 3.210

    5037 AB Tilburg

    Netherlands

1985 …2019
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Personal profile

Research interests

John H.J. Einmahl is 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.

Career

John is a fellow of the Institute of Mathetematical Statistics and he has been an elected member of its council. He is also an elected member of the International Statistical Institute.  John is 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, Bernoulli, and the J. of Statistical Planning and Inference. He has been a codirector of the Stochastics of Extremes and Risk Analysis program at the European research institute Eurandom. He visited Florida State University as a Senior Fulbright Scholar. He is a co-chair of the organizing committee of the 10th Extreme Value Analysis meeting in Delft in 2017.

Current courses

Click here for my courses.

Keywords

  • Statistical Methods
  • Estimation Theory
  • Mathematics
  • Extreme Value Theory
  • Theory Of Probability
  • Statistics

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Research Output 1985 2019

Limits to human life span through extreme value theory

Einmahl, J., Einmahl, J. & de Haan, L. F. M., Jan 2019, In : Journal of the American Statistical Association.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
Extreme Value Theory
Life Span
Mortality
Probability Distribution
Configuration

A continuous updating weighted least squares estimator of tail dependence in high dimensions

Einmahl, J. H. J., Kiriliouk, A. & Segers, J., 1 Jun 2018, In : Extremes. 21, 2, p. 205-233

Research output: Contribution to journalArticleScientificpeer-review

Weighted Least Squares Estimator
Tail Dependence
Higher Dimensions
Updating
Estimator

Estimating the maximum possible earthquake magnitude using extreme value methodology: The Groningen case

Beirlant, J., Kijko, A., Reynkens, T. & Einmahl, J. H. J., Jan 2018, In : Natural Hazards.

Research output: Contribution to journalArticleScientificpeer-review

earthquake magnitude
methodology
insurance industry
disaster management
earthquake engineering

Improved Estimation of the Extreme Value Index Using Related Variables

Ahmed, H. & Einmahl, J., 16 Jul 2018, Tilburg: CentER, Center for Economic Research, 16 p. (CentER Discussion Paper; vol. 2018-025).

Research output: Working paperDiscussion paperOther research output

File
Extreme Value Index
Hill Estimator
Earthquake
Extreme Value Statistics
Tail Dependence

Testing the Multivariate Regular Variation Model

Einmahl, J., Yang, F. & Zhou, C., 29 Oct 2018, Tilburg: CentER, Center for Economic Research, 25 p. (CentER Discussion Paper; vol. 2018-044).

Research output: Working paperDiscussion paperOther research output

File
Multivariate Regular Variation
Testing
Extreme Value Index
Regular Variation
Model

Projects 2005 2012

Project on Multivariate Extreme Value Theory

Cai, J., Einmahl, J. & de Haan, L. F. M.

1/09/0924/10/12

Project: Research project

Essays in nonparametric statistics

Gantner, M. & Einmahl, J.

1/04/071/04/10

Project: Research project

Extreme values in high-dimensional time series

Krajina, A. & Einmahl, J.

1/09/051/09/09

Project: Research project