Currículo
Generalized Linear Models MLG
Contextos
Groupo: Matemática Aplicada à Economia e à Gestão > 1º Ciclo > Unidades Curriculares Optativas
ECTS
4.0 (para cálculo da média)
Objectivos
To introduce the foundations of Generalized Linear Models (GLM) and its applications. Provide skills for real-data estimation of GLM. Additionally, to introduce the main concepts of machine learning and some key algorithms. Provide skills to use appropriate software to apply machine learning techniques to simple real-data problems.
Programa
Generalized Linear Models: - Review of linear regression models - Generalized linear models: general overview - Inference - Examples of generalized linear models for continuous and discrete response - Quasi-likelihood and overdispersion Machine Learning: - What is machine learning - Branches of machine learning - Applications
Método de Avaliação
Lectures will alternate theoretical presentations of statistical models with data analysis performed with suitable software. The final grade, on a 0-20 scale, is awarded on the basis of a written exam and of a practical exam done on a computer using R. The mark on the written exam will be worth 70% of the final grade.
Carga Horária
Carga Horária de Contacto -
Trabalho Autónomo - 86.0
Carga Total -
Bibliografia
Principal
- Modern Applied Statistics with S: Venables W. N. and Ripley B. D 2002 4th Edition, Spinger
- Statistical Inference ? Based on the Likelihood: Azzalini A. 1996 Chapman and Hall
- Generalized Linear Models: McCullagh P. And Nelder, J.A. 1989 2nd Edition, Chapman and Hall, London.
Secundária
- Introduction to S-Plus for Generalized Linear Modelling: Altham, P.M.E. 2006 null
- Applying Generalized Linear Models: Lindsey, J.K. 1997 Springer-Verlag, New York.