Department of Finance

  • Center for Statistics
Assistant professor

Room: SOL/A4.19
PIC_Mads Stehr

Mads Stehr is an Assistant Professor in Statistics at the Department of Finance, and he holds a PhD in Statistics and Probability Theory from Aarhus University. His research lies mainly within applied probability theory including Lévy-based modeling and extreme value theory. 

Primary research areas
Applied probability theory
Lévy-based spatio-temporal modeling
Extreme value theory
Numerical integration based on stationary sampling
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Stokastiske processer og deres statistiske analyse

Publications sorted by:
Anders Rønn-Nielsen; Mads Stehr / Extremal Clustering and Cluster Counting for Spatial Random Fields
In: Bernoulli, Vol. 29, No. 4, 11.2023, p. 2771-2796
Journal article > peer review
Anders Rønn-Nielsen; Mads Stehr / Extremes of Lévy-driven Spatial Random Fields with Regularly Varying Lévy Measure
In: Stochastic Processes and Their Applications, Vol. 150, 8.2022, p. 19-49
Journal article > peer review
Mads Stehr; Anders Rønn-Nielsen / Extremes of Subexponential Lévy-driven Random Fields in the Gumbel Domain of Attraction
In: Extremes, Vol. 25, No. 1, 3.2022, p. 79–105
Journal article > peer review
Mads Stehr; Markus Kiderlen; Karl‐Anton Dorph‐Petersen / Improving Cavalieri Volume Estimation Based on Non‐equidistant Planar Sections : The Trapezoidal Estimator.
In: Journal of Microscopy, Vol. 288, No. 1, 10.2022, p. 40-53
Journal article > peer review
Mads Stehr; Anders Rønn-Nielsen / Extreme Value Theory for Spatial Random Fields – With Application to a Lévy-Driven Field
In: Extremes, Vol. 24, No. 4, 12.2021, p. 753–795
Journal article > peer review
Mads Stehr; Anders Rønn-Nielsen / Tail Asymptotics of an Infinitely Divisible Space-time Model with Convolution Equivalent Lévy Measure
In: Journal of Applied Probability, Vol. 58, No. 1, 3.2021, p. 42-67
Journal article > peer review
Mads Stehr; Markus Kiderlen / Asymptotic Variance of Newton–Cotes Quadratures Based on Randomized Sampling Points
In: Advances in Applied Probability, Vol. 52, No. 4, 12.2020, p. 1284-1307
Journal article > peer review
Mads Stehr; Markus Kiderlen / Improving the Cavalieri Estimator under Non-Equidistant Sampling and Dropouts
In: Image Analysis and Stereology, Vol. 39, No. 3, 2020, p. 197-212
Journal article > peer review
Mads Stehr / Stereology and Spatio-temporal Models : Numerical Integration Methods for Volume Estimation and Extremes for Lévy-based Models.
Aarhus : Aarhus University. Department of Mathematics 2020, 145 p.
PhD thesis
Mads Stehr; Markus Kiderlen / Asymptotic Variance of Newton-Cotes Quadratures based on Randomized Sampling Points
Aarhus : Centre for Stochastic Geometry and Advanced Bioimaging (CSGB), Aarhus University 2019, 33 p. (CSGB Research Reports, No. 2)
Working paper
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