ASSEE 2022 - Bayesian Networks in Policy and Society
The 16th Advanced Summer School in Economics and Econometrics was held from August 7st to August 13th, 2022, at the University Campus in Rethymno, Crete. The topic of the School was “Bayesian Networks in Policy and Society“.
Dr. Marco Scutari, Senior Researcher in Bayesian Networks and Graphical Models, Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Polo Universitario Lugano, Switzerland, will be the guest lecturer., was the Distinguished Guest Professor.
Since 2006 the Department of Economics of the University of Crete is successfully running its Advanced Summer School in Economics and Econometrics. The broader objective of this series of events is to provide advanced training for young researchers from all over Europe and beyond on important disciplines of economics and econometrics. The Summer School follow a traditional structure: lectures in the morning and computer practical sessions in the afternoon. The specialized topic varies from year to year and reflects issues that are currently lively areas of new research and policy interest. The faculty is comprised of leaders in the field, and offers an overall coverage of the specialist area.
Magdalena Erdem, ASSEE 2014
The course justified my expectations completely!
The organization of the course was excellent and I do not hesitate to recommend ASSEE to anyone who wants to learn some theory of interest as well as practical aspects of econometrics.
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Through systematic interaction participants will be encouraged to compare their approaches and examine their research work. A unique opportunity will be given to advanced doctoral students to present their own work and to discuss it with the Distinguished Guest Professor. The Advanced Summer School Series on Economics and Econometrics facilitates the establishment of contacts between young researchers coming from various universities and research institutions throughout Europe.
Bayesian Networks in Policy and Society
Dr. Marco Scutari, Senior Researcher in Bayesian Networks and Graphical Models, Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Polo Universitario Lugano, Switzerland
Course Objective
This course introduced attendees to recent developments of Bayesian Networks using the statistical language R.
Topics Covered
- Definitions and Fundamentals
- Models and Distributional Assumptions
- Probabilistic Inference
- Structure Learning
- Causal Inference
Reading List:
“Bayesian Networks with Examples in R,” Routhledge, (2022) link
“Causal Inference in Statistics: A Prime”, Wiley & Sons Ltd, (2016) link