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Computational Statistics
Provider: Faculty of Science

Activity no.: 5544-21-07-31 
Enrollment deadline: 06/09/2021
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time06.09.2021, at: 00:00 - 14.11.2021, at: 16:00
Regular seats50
ECTS credits7.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserNiels Richard Hansen    E-mail address: niels.r.hansen@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 1
Scheme groupA (Tues 8-12 + Thurs 8-17)
Exam formCourse participation
Exam formCourse participation
Grading scalePassed / Not passed
Criteria for exam assessmentCourse participation under invigilation
Course workload
Course workload categoryHours
Lectures28.00
Exercises28.00
Preparation119.00
Eksamensforberedelse30.00
Exam1.00
Sum206.00
Content
- Maximum-likelihood and numerical optimization.
- The EM-algorithm.
- Stochastic optimization algorithms.
- Simulation algorithms and Monte Carlo methods.
- Nonparametric density estimation.
- Bivariate smoothing.
- Numerical linear algebra in statistics. Sparse and structured matrices.
- Practical implementation of statistical computations and algorithms.
- R/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.

Teaching and learning methods
4 hours of lectures per week for 7 weeks.
2 hours of presentation and discussion of the exam assignments per week for 7 weeks.
2 hours of exercises per week for 7 weeks.

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