Course syllabus

Statistisk modellering av extremvärden
Statistical Modelling of Extreme Values

FMS155, 7,5 credits, A (Second Cycle)

Valid for: 2016/17
Decided by: Education Board B
Date of Decision: 2016-03-28

General Information

Elective for: D4, F4, F4-fm, I4, I4-fir, Pi4-fm, Pi4-biek
Language of instruction: The course will be given in English on demand


The course aims to give theoretical knowledge in mathematical modelling of extreme events and discusses in detail how the theory can be applied in practice. Different courses of action for modelling of extreme values are discussed and guidance is given as to how the models can be modified to fit different practical situations. The students should also learn about more advanced models for extreme value analysis, including extreme values for non-stationary processes.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must


Extreme value theory concerns mathematical modelling of random extreme events. Recent development has introduced mathematical models for extreme values and statistical methods for them. Extreme values are of interest in, e.g., economics, safety and reliability, insurance mathematics, hydrology, meteorology, environmental sciences, and oceanography, as well as branches in statistics such as sequential analysis and robust statistics. The theory is used, e.g., for flood monitoring, construction of oil rigs, and calculation of insurance premiums for re-insurance of storm damage. Often extreme values can lead to very large consequences, both financial and in the loss of life and property. At the same time the experience of really extreme events is always very limited. Extreme value statistics is therefore forced to difficult and uncertain extrapolations, but is, none the less, necessary in order to use available experience in order to solve important problems.

The course will present the fundamental statistical methods for extreme value analysis, discuss examples of applications, i.a., regarding floods, storm damage, human life expectancy, and corrosion, provide practical use of the models, and point to some open problems and possible developments.

Examination details

Grading scale: TH
Assessment: Written exam and compulsory computer exercises.

Code: 0116. Name: Examination.
Credits: 6. Grading scale: TH. Assessment: Written examination
Code: 0216. Name: Laboratory Work.
Credits: 1,5. Grading scale: UG. Assessment: Computer exercises


Admission requirements:

Required prior knowledge: Probability theory corresponding to FMSF05.
The number of participants is limited to: No
The course overlaps following course/s: MASM15

Reading list

Contact and other information

Course coordinator: Docent Nader Tajvidi,
Director of studies: Anna Lindgren,
Course homepage:
Further information: The course is also given at the faculty of science with the code MASM15.