Bayesian Statistical Models

Scienze Statistiche ed Economiche

Autore/Autrice
Affiliazione

Riccardo Corradin

Università degli Studi di Milano-Bicocca

In this page, you can find teaching materials, examples, case studies and information related to the Bayesian Statistical Models module taught in the Scienze Statistiche ed Economiche degree course.

Slides and teaching material

Here you can find slides, examples and case studies.

Topic Slides Further material Case studies
Introduction Notes introduction
Computational methods Notes computation
Regression models Notes regression
Model improvement and extension
Clustering
Spatial Bayesian models

Material is subject to changes during the term.


Office hour

To book a meeting, you can write an email to riccardo.corradin@unimib.it. Office hours are every Tuesday at 16:30.


Exam

The final exam consists of two parts, a project to be carried out in groups and an oral exam. The project focuses on the evaluation of the analysis and use of model skills acquired by the students, where they will be asked to produce a paper discussing the analysis of an applied problem using Bayesian techniques. The oral exam aims to verify the methodological skills acquired by the student.


Textbooks and reading materials

Main textbooks:

  • Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis, Third Edition. CRC Press.

  • Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.

Further readings:

  • Hoff, P. D. (2009). A First Course in Bayesian Statistical Methods. Springer.

  • Neal, P., Dellaportas, P., Polson, N. G., & Stephens, D. A. (2013). Bayesian theory and applications. Oxford University Press.

  • Congdon P. (2007). Bayesian Statistical Modelling, 2nd Edition. Wiley.

  • Robert, C.P., Casella, G. (2004). Monte Carlo Statistical Methods, 2nd Edition. Springer.


Acknowledgments

Slides, examples, case studies and other form of material presented in this module are the results of multiple sources. I gently acknoledge Alessandra Guglielmi and Tommaso Rigon. All credits are theirs, all mistakes are mine.