Applied Bayesian Statistics School 2019Enter
The Applied Bayesian Statistics summer school has been running since 2004. Since 2012 it is organised by
Since 2014 the school is organized in cooperation with Fondazione "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 Sciences, Bayes Big Data and the Internet, Modeling Spatial And Spatio-Temporal Data With Environmental Applications, Bayesian Statistical Modelling and Analysis in Sport.
The topic chosen for the 2019 school is
The instructors are leaders of the research group that developed the methods to be taught in the course (http://bayespop.csss.washington.edu).
Population projections have until recently usually been done
deterministically. Recently, the United Nation Population Division adopted
a probabilistic approach to project fertility, mortality and population for
all countries. In this approach, the total fertility rate and female and
male life expectancy at birth are projected using Bayesian hierarchical
models estimated via Markov Chain Monte Carlo. They are then combined with
a cohort component model, which yields probabilistic projection for any
quantity of interest. The methodology is implemented in a suite of R
packages, which has been used by the UN analysts to produce the most recent
revision of the World Population Prospects.
This course will teach the theory and practice of Bayesian probabilistic projections. Ideas of the Bayesian hierarchical modeling for the three main components of population change, fertility, mortality and migration, will be explained. In hands-on exercises, students will become familiar with the functionality of the R packages.
By the end of the course, participants will have a
basic understanding of the methods, be able to generate projections using
their own data, and visualize probabilistic projections for many quantities
of interest using various output formats, such as graphs, tables, maps, and
pyramids. The target audience for the course includes professional
demographers in government, international agencies, universities and
industry, as well as advanced students in statistics and other relevant
disciplines (demography, sociology, economics, anthropology, actuarial
Practical sessions will make use of R software which should be installed in participants' computers
The material will be provided by the lecturers during the course
The 2019 school will be held at Villa del Grumello, a magnificent villa located in the city of Como, along the Lake Como shoreline.
start time - Monday, June, 24th, at 2 p.m.
end time - Friday, June, 28th at 1 p.m..
Since a limited number of places is available, we strongly encourage participants to register as soon as possible. Please note that the registration form can be filled only if you are able to provide some data which are necessary according to the current Italian laws.
If you have any question, please contact the ABS School Secretariat.