NMAK13020U Functional Data Analysis

Volume 2013/2014
Education
MSc Programme in Statistics
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
Stat1, Stat2
Lectures, exercises, student presentations
  • Category
  • Hours
  • Colloquia
  • 10
  • Exam
  • 23
  • Lectures
  • 20
  • Preparation
  • 139
  • Theory exercises
  • 14
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Written examination, 1 week
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Exam registration requirements
One presentation of article or data analysis during the course. Presentation of solutions to excercises in exercise classes.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner
Re-exam
Oral exam. Several internal examiners
Criteria for exam assesment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.