ABS16 - 2016 Applied Bayesian Statistics School
The Applied Bayesian Statistics summer school has been running since 2004. From 2012 it is organized by
Since 2014 the school is organized in cooperation with Centro di Cultura Scientifica "Alessandro Volta"
The school aims
to present state-of-the-art Bayesian applications, inviting leading
experts in their field. Each year a different topic is chosen. Past
editions were devoted to Gene Expression Genomics, Decision
Modelling in Health Care, Spatial Data in Environmental and
Health Sciences, Bayesian Methods and Econometrics, Bayesian
Decision Problems in Biostatistics and Clinical Trials, Bayesian
Methodology for Clustering, Classification and Categorical Data
Analysis, Bayesian Machine Learning with Biomedical
Applications, Hierarchical Modeling for Environmental
Processes, Stochastic Modelling for Systems Biology, Bayesian
Methods for Variable Selection with
Applications to High-Dimensional Data and Applied Bayesian
Nonparametrics, Modern Bayesian Methods and Computing for the Social
The topic chosen for the 2016 school
is Bayes, Big Data, and the Internet.
The lecturer is:
Dr Steve Scott, Director of Statistics Research Google, USA
He will be assisted by Ilaria Bianchini (Politecnico di Milano, Italy).
INTENDED PARTICIPANTS AND PREREQUISITES
course is intended for students with little or no background in
Bayesian statistics, who would like to use applied Bayesian methods.
Students should have a basic familiarity with R, and some elementary
knowledge of probability (so we can talk about "binomial" models and
"gamma" priors). Some background in linear models will be
helpful but is not strictly necessary.
The course will not follow a specific text. Several good textbooks on Bayesian inference include.
* Bayesian Data Analysis (Gelman, Carlin, Stern, Dunson, Vehtari, Rubin)
* Bayesian Methods and Marketing (Rossi, Allenby, McCulloch)
* Bayesian Computation with R (Albert)
* George and McCulloch (1997, Statistica Sinica) "Approaches for Bayesian Variable Selection"
* Scott and Varian (2013) Predicting the present with Bayesian Structural Time Series
* Scott (2010) A Modern Bayesian Look at the Multi-Armed Bandit
* Bayes and Big Data: The consensus Monte Carlo algorithm
will use the following R packages (available from CRAN)
2016 school will be held at Villa
del Grumello, a magnificent villa located in the city of
Como, along the Lake Como shoreline.
Please note that the number of available places is limited.
The school will start on Monday, August , 29th, and it will end on Friday, September, 2th .