[ 551OKMEVLMK14 ] KV Generalized linear models

(*) Unfortunately this information is not available in english.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4 ECTS B2 - Bachelor's programme 2. year Statistics Helga Wagner 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites (*)keine
Original study plan Bachelor's programme Statistics 2015W
Objectives Students are familiar with methods for regression analysis of binary, categorical or count data
Subject Distribution and structural assumptions of the generalized linear model, link and response function

Logit, Probit and complementary log-log model, loglinear Poisson model, multivariate logistic regression

parameter estimation (ML estimation, score function, numerical optimization, existence, uniqueness and asymptotic properties)

tests of linear hypotheses; model choice, goodness of fit

Criteria for evaluation Homework and written exam
Methods presentation by the lecturer

presentation of the homework by students and discussion

Language German
Study material Fahrmeir L., Kneib T., Lang S. and Marx B., Regression. Models, Methods and Applications. Springer, 2013
Changing subject? No
Corresponding lecture (*)ist gemeinsam mit 551STMEMVVK14: KV Multivariate Verfahren (4 ECTS) äquivalent zu
4MSMV1KV: Multivariate Verfahren I (8 ECTS)
On-site course
Maximum number of participants 40
Assignment procedure Assignment according to priority