NMAK14019U Point processes (Pointproc)
Volume 2014/2015
Education
MSc Programme in Mathematics
MSc Programme in Statistics
MSc Programme in Mathematics-Economics
MSc Programme in Statistics
MSc Programme in Mathematics-Economics
Content
- 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.
- The R package ppstat.
- Elements of continuous time martingale theory.
- Change of measure, the likelihood process and statistical inference.
- Multivariate event time models.
Learning Outcome
Knowledge:
- Aspects of stochastic analysis with a focus on processes with finite local variation.
- Statistical methods for estimation and model selection.
- Concrete multivariate models applied to social and neuron network modeling.
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 in R.
Competences: Ability to
- build dynamic models of multivariate event times, fit the models to data, simulate from the models and validate the models.
Teaching and learning methods
5 hours of lectures for 7
weeks
Workload
- Category
- Hours
- Course Preparation
- 70
- Exam
- 40
- Exercises
- 61
- Lectures
- 35
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Continuous assessmentA total of 3 individual assignments. 2 minor theoretical assignments (each with weight 15%) and 1 mixed theoretical and practical assignment (weight 70%).
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal examiner
- Re-exam
- Resubmission of all the assignments from the continuous assignment. The assignments must be resubmitted at the end of the reexamination week.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- NMAK14019U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- C (Mon 13-17 + Wednes 8-17)
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Niels Richard Hansen (14-716c686f763175316b6471766871437064776b316e7831676e)
Phone: +45 3532 0783
Saved on the
01-12-2014