– Introduction: motivating examples
– Revision of standard linear regression models
– Exponential family of distributions
– Formulation of generalized linear models, Poisson regression, logistic regression
– Estimation using the iterated weighted least squares algorithm
– Inference based on asymptotics or bootstrap methods
– Model selection (AIC & BIC), model checking using residuals
– Extensions (GLMMs, GAMs)
The course language will be English.
Teilnahmevoraussetzungen, notwendige Vorkenntnisse
It will be expected that participants are familiar with basic statistics (e.g. from introductory courses in statistics, stochastics or econometrics). Basic knowledge of the free software R would be advantageous, but is not required.