- Tuesday 10.15-11.45 - Lecture, Narva mnt 18 - 1007
- Wednesday 10.15-11.45 - Computer Lab, Narva mnt 18 - 2004
Moodle page of the course: https://moodle.ut.ee/course/view.php?id=5843
Amount of credits: 6 ECTS (EAP)
Course code: MTMS.01.011
Lecturer: Meelis Käärik (associate professor, Institute of Mathematics and Statistics, University of Tartu)
Target group: master students of actuarial and financial engineering / mathematics and statistics programmes
- MTMS.01.001 Mathematical Statistics I (6 ECTS)
- MTMS.01.008 Matrix Calculus for Statistics (3 ECTS)
- MTMS.01.071 Linear Models (6 ECTS)
- MTMS.01.035 Mathematical Statistics II (6 ECTS)
- MTMS.01.007 Data Analysis II (6 ECTS)
Brief description: The following topics will be covered:
- Exponential family of distributions, maximum likelihood estimation, link function, Fisher scoring
- Models for continuous responses (normal, exponent, gamma and inverse Gaussian distribution),
- Models for binomial responses and for count data (including zero-modified models)
Objectives of the course: The aim of the course is to provide a systematic overview of generalized linear models as models for responses with distribution from exponential family of distributions.
Learning outcomes: Participants who pass this course
- knows exponential family of distributions
- is able to select models with appropriate link functions and response functions
- is able to fit models with overdispersion
- has practical skills for interpreting results.
Final assessment: non-differentiated (pass, fail)
Requirements to be met for final assessment:
- Both tests passed. To pass a test, at least of maximum is required.
- At least 60% needs to be acquired from the final exam to pass the course. The more points one has obtained from midterm tests, the fewer questions one needs to answer in final exam.
Recommended study materials:
- G. Tutz (2012). Regression for Categorical Data. Cambridge University Press
- P. De Jong, G.Z. Heller (2008). Generalized Linear Models for Insurance Data. Cambridge University Press, NY.
- P. McCullagh, J.A. Nelder (1989). Generalized Linear Models. Chapman &Hall, London.
- A.F. Zuur, E.N. Ieno, N. Walker, A.A. Saveliev, G.M. Smith (2009). Mixed Effects Models and Extensions in Ecology with R. Springer.
Additional information: Meelis Käärik (firstname.lastname@example.org)