Valid for: 2024/25
Faculty: Faculty of Engineering LTH
Decided by: PLED I
Date of Decision: 2024-04-16
Effective: 2024-05-08
Depth of study relative to the degree requirements: Second cycle, in-depth level of the course cannot be classified
Elective for: D4, F4, F4-fm, I4-fir, Pi4-fm, Pi4-biek, R4
Language of instruction: The course will be given in English
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.
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
Grading scale: TH - (U, 3, 4, 5) - (Fail, Three, Four, Five)
Assessment: Written exam and compulsory computer exercises.
The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.
Modules
Code: 0117. Name: Examination.
Credits: 6.0. Grading scale: TH - (U, 3, 4, 5).
Assessment: Written examination
Code: 0217. Name: Laboratory Work.
Credits: 1.5. Grading scale: UG - (U, G).
Assessment: Computer exercises
Admission requirements:
Director of studies: Johan Lindström,
studierektor@matstat.lu.se
Course administrator: Susann Nordqvist,
expedition@matstat.lu.se
Course homepage: https://www.maths.lu.se/utbildning/civilingenjoersutbildning/matematisk-statistik-paa-civilingenjoersprogram/