NMAK15013U Functional Data Analysis
Volume 2015/2016
Education
MSc Programme in Statistics
MSc Programme in Mathematics-Economy
Content
One- and multidimensional functional data, smoothing,
alignment, principal component analysis, functional
regression,
classification
Learning Outcome
Knowledge:
- Recognize the possibilities and challenges with functional data
- Recognize similarities and differences between methods for low-dimensional data, high-dimensional data, and functional data
- Understand methods used for smoothing, alignment, PCA, regression
Skills:
- Carry out simple data analyses with functional data
- Use R to carry out smoothing, alignment, PCA, regression
- Read scientific papers in the area (applied and theoretical)
Competences:
- Choose appropriate statistical methods of functional data, taking into account their functional nature and the purpose of the analysis
- Evaluate the appropriateness of methods in analyses of functional data in scientific papers
Academic qualifications
Stat1, Stat2
Teaching and learning methods
Lectures, exercises, student
presentations
Workload
- Category
- Hours
- Exercises
- 16
- Lectures
- 28
- Preparation
- 126
- Project work
- 36
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Continuous assessmentThree individual mandatory projects each counting 1/3 of the final grade.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Re-exam
30 minutes oral exam with 30 minutes preparation time and all aids allowed during the preparation time and no aids allowed during the examination.
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
- NMAK15013U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- B
- 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
- Lars Lau Raket (7-6e6374756e6377426f63766a306d7730666d)
Lecturers
Lars Lau Raket
Saved on the
30-04-2015