Advanced Statistical Modelling of Space-Time Environmental Data Using Gams
A.Y. 2023/2024
Course offered to students on the PhD programme in
Visit the PhD website for the course schedule and other information
Lead instructor: Corrado Alberto Sigfrido Camera
"Understand what semi-parametric statistical modelling is.
Understand GAMs and how many regression methods can be viewed as specific cases.
Appreciate uncertainty in statistical modelling, its sources, and why/how it is quantified.
Understand Bayesian inference for GAMs including predictive inference and model checking.
Appreciate the use of the mgcv R package as a flexible data modelling tool for environmental data."
Understand GAMs and how many regression methods can be viewed as specific cases.
Appreciate uncertainty in statistical modelling, its sources, and why/how it is quantified.
Understand Bayesian inference for GAMs including predictive inference and model checking.
Appreciate the use of the mgcv R package as a flexible data modelling tool for environmental data."
The course builds upon "Statistical and geostatistical analyses of geo-environmental data" and assumes knowledge of basic statistical concepts (probability distributions, random variables, linear regression). Basic R knowledge is also required.
Assessment methods
Giudizio di approvazione
Assessment result
superato/non superato
How to enrol
Deadlines
The course enrolment deadline is usually the 27th day of the month prior to the start date.
How to enrol
- Access enrolment on PhD courses online service using your University login details
- Select the desired programme and click on Registration (Iscrizione) and then on Register (Iscriviti)
Ignore the option "Exam session date” that appears during the enrolment procedure.
Contacts
For help please contact [email protected]