NMAK16005U Computational Statistics

Volume 2016/2017
Education

MSc Programme in Statistics
MSc Programme in Mathematics-Economy

Content
  • Maximum-likelihood and the EM-algorithm.
  • Simulation algorithms and Monte Carlo methods.
  • Markov Chain Monte Carlo.
  • Univariate and multivariate smoothing.
  • Numerical linear algebra in statistics. Sparse and structured matrices.
  • Practical implementation of statistical computations and algorithms.
  • R/C/C++ and RStudio statistical software development.
Learning Outcome

Knowledge:

  • fundamental algorithms for statistical computations
  • R packages that implement some of these algorithms or are useful for developing novel implementations.

 

Skills: Ability to

  • implement, test, debug, benchmark, profile and optimize statistical software.

 

Competences: Ability to

  • select appropriate numerical algorithms for statistical computations
  • evaluate implementations in terms of correctness, robustness, accuracy and memory and speed efficiency.
Statistik 2 or similar knowledge of statistics and some experience with R usage. Linear algebra, multivariate distributions, likelihood and least squares methods are essential prerequisites.
4 hours of lectures per week for 7 weeks.
2 hours of presentation and discussion of a weekly assignment per week for 7 weeks.
  • Category
  • Hours
  • Exam
  • 1
  • Exam Preparation
  • 30
  • Exercises
  • 14
  • Lectures
  • 28
  • Preparation
  • 133
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination, 25 min
During the course a total of 6 assignments will be given. At the oral exam one of the 6 assignments is selected at random and the student presents it without preparation. The presentation is followed by a discussion with the examinator within the topics of the course.
Exam registration requirements

To participate in the final oral exam one oral presentation must have been given during the course.

Marking scale
7-point grading scale
Censorship form
No external censorship
Two internal examiners.
Re-exam

Same as ordinary exam. To be eligible for the re-exam, students who did not give an oral presentation during the course must hand in synopses of the solutions to all 6 assignments no later than 2 weeks before the beginning of the re-exam week. The 6 synopses must be approved in order to take the re-exam.

Criteria for exam assesment

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