Currículo

Generalized Linear Models MLG

Contextos

Groupo: Finanças > 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

  • Generalized Linear Models: McCullagh P. And Nelder, J.A. 1989 2nd Edition, Chapman and Hall, London.
  • Statistical Inference ? Based on the Likelihood: Azzalini A. 1996 Chapman and Hall
  • Modern Applied Statistics with S: Venables W. N. and Ripley B. D 2002 4th Edition, Spinger

Secundária

Disciplinas de Execução

2021/2022 - 2 Semestre

2018/2019 - 2 Semestre

2019/2020 - 2 Semestre