Dr Kirstin Strokorb
Lecturer
- strokorbk@cardiff.ac.uk
- +44 (0)29 2068 8833
- M/2.37, Adeilad Mathemateg ac Addysg, Ffordd Senghennydd, Caerdydd, CF24 4AG
- Ar gael fel goruchwyliwr ôl-raddedig
Trosolwg
Research Group
- Statistics Research Group
- Mathematical Analysis Research Group
Research Interests
My research focus lies on stochastic processes and dependence concepts in extreme value theory, a branch of probability and statistics that provides theoretically sound procedures for extrapolation beyond the range of data (as good as possible, knowing the limits is also an important issue). Its methods are usually relevant for institutions that are exposed to high risks, for instance, financial services and insurance companies or environmental engineering institutions.
Bywgraffiad
- 2017 - present: Lecturer at Cardiff School of Mathematics, Cardiff University.
- 2013 - 2016: Postdoctoral Research and Teaching assistant at Institute of Mathematics, University of Mannheim.
- Autumn 2015: Research stay at Department of Mathematical Sciences, University of Copenhagen.
- 2013: PhD at Institute of Mathematical Stochastics/RTG 1023, University of Goettingen.
- 2010: Diploma at Mathematics Institute, University of Goettingen.
- Autumn 06/Winter 07: Exchange student at Mathematics Institute, Warwick University.
Pwyllgorau ac adolygu
Associate Editor for peer-reviewed scientific journals:
Reviewing for peer-reviewed scientific journals:
- Bernoulli
- Electronic Journal of Statistics
- Extremes
- Journal of Mathematical Analysis and Applications
- Journal of Multivariate Analysis
- Journal of Nonparametric Statistics
- Journal of Statistical Computation and Simulation
- Journal of the American Statistical Association
- Statistics
- Statistics and its Interface
- Stochastic Models
Reviews for MathSciNet.
Cyhoeddiadau
2021
- Oesting, M. and Strokorb, K. 2021. A comparative tour through the simulation algorithms for max-stable processes. Statistical Science
2019
- Brehmer, J. R. and Strokorb, K. 2019. Why scoring functions cannot assess tail properties. Electronic Journal of Statistics 13(2), pp. 4015-4034. (10.1214/19-EJS1622)
2018
- Oesting, M. and Strokorb, K. 2018. Efficient simulation of Brown-Resnick processes based on variance reduction of Gaussian processes. Advances in Applied Probability 50(4), pp. 1155-1175. (10.1017/apr.2018.54)
2017
- Fiebig, U., Strokorb, K. and Schlather, M. 2017. The realization problem for tail correlation functions. Extremes 20, pp. 121-168. (10.1007/s10687-016-0250-8)
- Papastathopoulos, I.et al. 2017. Extreme events of Markov chains. Advances in Applied Probability 49(1), pp. 134-161. (10.1017/apr.2016.82)
2016
- Molchanov, I. and Strokorb, K. 2016. Max-stable random sup-measures with comonotonic tail dependence. Stochastic Processes and their Applications 126(9), pp. 2835-2859. (10.1016/j.spa.2016.03.004)
- Papastathopoulos, I. and Strokorb, K. 2016. Conditional independence among max-stable laws. Statistics and Probablity Letters 108, pp. 9-15. (10.1016/j.spl.2015.08.008)
2015
- Strokorb, K., Ballani, F. and Schlather, M. 2015. Tail correlation functions of max-stable processes. Extremes 18, pp. 241-271. (10.1007/s10687-014-0212-y)
- Strokorb, K. and Schlather, M. 2015. An exceptional max-stable process fully parameterized by its extremal coefficients. Bernoulli 21(1), pp. 276-302. (10.3150/13-BEJ567)
- Schlather, M.et al. 2015. Analysis, simulation and prediction of multivariate random fields with package RandomFields. Journal of Statistical Software 63(8) (10.18637/jss.v063.i08)
2013
- Strokorb, K. 2013. Characterization and construction of max-stable processes. PhD Thesis, eDiss University of Goettingen.
2010
- Strokorb, K. 2010. Eine holomorphe Untersuchung des verallgemeinerten Seiberg-Witten-Modulraumes für Gibbons-Hawking-Faserungen. , Mathematisches Institut, Universität Göttingen, Germany.
Addysgu
Cardiff
- Autumn 17 MA2801 Econometrics for Financial Mathematics
- Spring 17 MA1801 Finance I : Financial Markets and Corporate Financial Management
Mannheim
- Autumn 16: Introduction to Extreme Value Statistics (Lectures and Tutorials)
- Spring 16: Introduction to Insurance Mathematics (Lectures and Tutorials, jointly with M. Schlather)
- Spring 15: Introduction to Spatial Extreme Value Theory (Lectures and Tutorials)
- Autumn 14: Introduction to Extreme Value Statistics (Lectures and Tutorials)
- Spring 14: Linear Models (Tutorials and Assistance)
- Autumn 13: Functional Analysis (Tutorials and Assistance)
- Autumn 13: Introduction to the statistical programming language R (Assistance)
Goettingen
Tutorials in
- Functional Analysis
- Linear Algebra and Analytic Geometry
- Analysis II
- Discrete Mathematics
Mentoring for Bachelor and Master students, Assistance in creating lecture notes for Mathematics for Biologists, Training for Mathematical Olympiads
My research focus lies on stochastic processes and dependence concepts in extreme value theory, a branch of probability and statistics that provides theoretically sound procedures for extrapolation beyond the range of data (as good as possible, knowing the limits is also an important issue). Its methods are usually relevant for institutions that are exposed to high risks, for instance, financial services and insurance companies or environmental engineering institutions.
So far, I have been involved in projects concerning the following topics:
- Extreme value theory (correlation functions and dependence concepts for extreme values, connections to stochastic geometry and risk measures, conditional independence)
- Realisability problems (that deal with the existence of stochastic models with some prescribed distributional properties, connections to convex geometry)
- Stochastic processes (in particular Gaussian and max-stable processes, construction principles, simulation, R software RandomFields)
- Markov chains (modelling the evolution of the chain after an extreme event)
With my research I would like to contribute to the development of improved tools for the analysis and prediction of rare events, in particular their temporal and spatial extent, and the rigorous verification that these tools are suitable in very general situations.
Invited talks
- CFE-CMStatistics, London (2017)
- 10th Conference on Extreme Value Analysis, Delft (2017)
- German Statistical Week (Minisymposium on EVT), Augsburg (2016)
- 3rd Conference of the International Society of Non-Parametric Statistics, Avignon (2016)
- Working group Extreme Value Theory UPMC Paris 6 (2016)
- Workshop on Dependence, Stability and Extremes, Fields Institute Toronto (2016)
- Seminar in Applied Mathematics and Statistics, Copenhagen (2015)
- The Mathematics and Statistics of Quantitative Risk Management, Oberwolfach (2015)
- 9th Conference on Extreme Value Analysis, Ann Arbor (2015)
- Workshop New Developments in Econometrics and Time Series, Bochum (2015)
- Working group Stochastic Geometry, Karlsruhe (2015)
- Colloquium on Probability and Statistics, Bern (2014)
- Research Seminar Gauge Theory and Topology, Bielefeld (2010)
