Sumários

Lecture 8

8 Abril 2022, 11:00 • Rui Paulo

Estimation of the regression coefficients via maximum likelihood: continuation. Residual deviance. Estimation of the dispersion parameter. Illustrative examples using R.

Lecture 7

1 Abril 2022, 11:00 • Rui Paulo

Maximum likelihood estimation of beta.

Lecture 6

25 Março 2022, 11:00 • Rui Paulo

EDM in dispersion form. Unit deviance. The saddlepoint approximation.


The systematic component of  a GLM. The link function, the canonical link function.

GLM defined: the total deviance and the total scaled deviance. Approximate distribution of the scaled total deviance when the saddlepoint approximation holds.

Lecture 5

18 Março 2022, 11:00 • Rui Paulo

Generalized linear models: random and systematic components.


The exponential dispersion family of distributions. Examples and properties.

Lecture 4

11 Março 2022, 11:00 • Rui Paulo

Inference in the context of the normal (weighted) multiple regression model. Maximum likelihood estimate coincides with the weighted least squares estimate. Distribution of the estimators; confidence intervals and tests of marginal significance. Confidence intervals for fitted values. Comparing nested models: analysis of variance (ANOVA). Sequential ANOVA. Diagnostic analysis.