Sumários

Lecture 9

21 Abril 2023, 11:00 • RUI MIGUEL BATISTA PAULO

Homework 5: continuation.

Estimation of the dispersion parameter.

Inference for generalized linear models: inference for the regression coefficients and comparison of nested models when the dispersion parameter is known. Goodness of fit test.

Lecture 8

14 Abril 2023, 11:00 • RUI MIGUEL BATISTA PAULO

Homework 3, 4 and 5 (partial).

Lecture 7

31 Março 2023, 11:00 • RUI MIGUEL BATISTA PAULO

Maximum likelihood estimation of the vector of regression coefficients.

Lecture 6

24 Março 2023, 11:00 • RUI MIGUEL BATISTA PAULO

The random component of a GLM: the variance function determines the EDM. EDM in dispersion form: the unit deviance. The saddlepoint approximation and conditions under which it holds for different members of the exponential dispersion family.

Lecture 5

17 Março 2023, 11:00 • RUI MIGUEL BATISTA PAULO

Comparing nested models: sequential anova table.

Diagnostics.

Generalized linear models: random and systematic structure. The exponential dispersion family: definition, examples, properties.