Undergraduate Degree in Finance
Course Structure Finanças
Generalized Linear Models (MLG)
Competence Course
Generalized Linear Models(Matemática)Execution Courses
Generalized Linear Models (2020/2021 - Semestre 2)Generalized Linear Models (2019/2020 - Semestre 2)
Generalized Linear Models (2018/2019 - Semestre 2)
Contexts
Group: Finanças > First Cycle > Optional Course Units
Period: 3 Year, 2 Semester
Weight
4.0 (for average grade calculus)
Objectives
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.
Program
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
Assessment Methodology
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.
Bibliographic Reference
Main
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
Secondary
Applying Generalized Linear Models
Lindsey, J.K.
1997
Springer-Verlag, New York.