NMAK23002U Computational Methods in Non-life Insurance
MSc Programme in Actuarial Mathematics
Some Bayesian theory. Standard and Monte Carlo based integration, including Laplace approximation and variational inference. Markov Monte Carlo methods including Metropolis Hastings and Gibbs sampling. Some classical optimization methods. Simulated annealing and CMA-ES. EM-algorithm. Hyperparameter optimization.
Knowledge: Understand the difference between pure Bayesian and frequentist methods. Insight into a number of numerical methods to solve the relevant problems. Knowledge about choosing good hyperparameter values in complex models.
Skills: Be able to identify problems and formulate them mathematically. Also be able to either program the solutions oneself or find relevant programs elsewhere.
Competences: To be able to understand the principles behind the various methods, including knowledge of their advantages and drawbacks. In addition the students will be able to run and understand the input and output of suitable programs in R. There will also be some focus on how to choose a good computational solution for a given task.
NMAK11022U Regression (Reg) or NMAB22011U Regression for Actuaries (RegAct)
Academic qualifications equivalent to a BSc degree is recommended.
- Theory exercises
- Project work
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- 7,5 ECTS
- Type of assessment
- Oral examination, 30min
- Type of assessment details
- Without preparation.
- Exam registration requirements
Two compulsory homeworks. They do not count for the grade.
- Without aids
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
Oral exam, 30 minutes without preparation. The two compulsory homeworks have to be turned in no later than three weeks before the reexam.
Criteria for exam assesment
In order to obtain the grade 12 the student should convincingly and accurately demonstrate the knowledge, skills and competences described under Learning outcome.
- Course code
- 7,5 ECTS
- Full Degree Master
- 1 block
- Block 4
- Course capacity
- No limit.
The number of seats may be reduced in the late registration period.
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Jostein Paulsen (7-6c717576676b70426f63766a306d7730666d)