Syllabus

Title
5636 Advanced Topics in Extreme-Value Analysis and Dependence Modeling
Instructors
Univ.Prof. Dr. Johana Genest Neslehova
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/17/25 to 03/10/25
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Monday 04/28/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Tuesday 04/29/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Monday 05/05/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Tuesday 05/06/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Wednesday 05/07/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Thursday 05/08/25 01:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Wednesday 06/18/25 01:00 PM - 04:00 PM Online-Einheit
Contents
This course will cover the modeling and statistical analysis extreme events in more complex settings than in the case of independent univariate variables. Topics include: (1) modeling extremes of dependent sequences and time series; (2) statistical models and methods for multivariate extremes, copulas, and point process models; (3) max-stable processes and spatial extremes.  
 
Assessment: 
 
The course assessment will be based on project work and on an oral presentation of the project.
 
Suggested reading: 

·      Modeling Extremal Events by P. Embrechts, C. Klüppelberg and T. Mikosch, Springer 1997 (Chapter 4)

·      An Introduction to Statistical Modeling of Extreme Values by S. Coles, Springer 2001 (Chapters 5 and 8)

·      Extremes and related properties of random sequences and processes by R. Leadbetter, G. Lindgren and H. Rootzén, Springer 1983

·      Statistics of Extremes by A.C. Davison and R. Huser, Annu. Rev. Stat. Appl. 2015. 2:203–35

·     Copula Modeling for Extremes by C. Genest and J.G. Nešlehová, Encyclopedia of Environmetrics (El-Shaarawi, Abdel H. and Piegorsch, Walter W. Eds.), Wiley 2012

Learning outcomes

Students will acquire a good understanding of theoretical and practical aspects of  univariate EVT. Moreover, they will be able to analyze data with EVT.

Attendance requirements

at least 80% of the units

Teaching/learning method(s)

Classroom teaching; project and group work

Assessment

The course assessment will be based on project work and on an oral presentation of the project.

Prerequisites for participation and waiting lists

The course assessment will be based on project work and on an oral presentation of the project.

Readings

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Last edited: 2025-01-03



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