NMAK22008U Point Processes
MSc Programme in Statistics
MSc Programme in Mathematics-Economics
MSc Programme in Actuarial Mathematics
- Random measures and Poisson processes.
- Stochastic processes with locally bounded variation.
- Integration w.r.t. random measures and locally bounded variation processes.
- Stochastic integral equations, numerical solutions and simulation algorithms.
- Elements of continuous time martingale theory.
- Change of measure, the likelihood process and statistical inference.
- Multivariate asynchronous event time models.
- Aspects of stochastic analysis for processes with finite local variation.
- Statistical methods for estimation and model selection.
- Applications of concrete multivariate recurrent event time models.
Skills: Ability to
- compute with stochastic integrals w.r.t. locally bounded variation processes
- construct univariate and multivariate models as solutions to stochastic integral equations
- simulate solutions to stochastic integral equations
- estimate parameters via likelihood and penalized likelihood methods
- implement the necessary computations
- build dynamic models of multivariate event times, fit the models to data, simulate from the models and validate the models.
Competences: Ability to
- analyze mathematical models of events with appropriate probabilistic techniques
- develop statistical tools based on the mathematical theory of event times
- assess which asynchronous event time models are appropriate for a particular data modelling task
The courses StatMet and MStat (alternatively MatStat from previous years), Regression and Advanced Probability 1+2 are sufficient. Advanced Probability 2 can be followed at the same time.
- Theory exercises
- 7,5 ECTS
- Type of assessment
- Continuous assessment
- Type of assessment details
- A total of 3 individual assignments. 2 minor theoretical assignments (each with weight 15%) and 1 mixed theoretical and practical assignment (weight 70%).
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
one internal examiner
Same as ordinary. Each of three assignments from the ordinary exam can be reused or remade.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
- Course code
- 7,5 ECTS
- Full Degree Master
- 1 block
- Block 2
- Course capacity
- 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
- Niels Richard Hansen (14-716c686f763175316b6471766871437064776b316e7831676e)