We are glad to announce that the 2018 Applied Bayesian Statistics Summer
School (15th edition) will be held in the magnificent Villa del Grumello,
Como (Italy), along the Lake Como shore.


       BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT

                       	4-8 June, 2018

Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics,
Queensland University of Technology, Brisbane, Australia.

Further details are provided below.


Guido Consonni and Fabrizio Ruggeri
ABS18 Directors
Raffaele Argiento
ABS18 Executive Director

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          *            ABS18            *
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        Applied Bayesian Statistics School

BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT

         Villa del Grumello, Como, Italy

	        4-8 June, 2018

Lecturer: Kerrie MENGERSEN, Distinguished Professor of Statistics,
Queensland University of Technology, Brisbane, Australia.

The conference webpage is

>>>>   web.mi.imati.cnr.it/conferences/abs18.html   <<<<

Registration is now open. Please note that the conference
room allows only for a limited number of participants.

The ABS18 Secretariat can be contacted at

        [log in to unmask]

COURSE OUTLINE

The aim of this course is to increase students' ability to develop
Bayesian models and computational solutions for real problems in the world
of sport. A case study based teaching approach will be taken for the course.
Each day, students will be presented with one or two problems posed by
Sports Institutes regarding aspects of athlete training for world games.
Through participatory problem solving, the students will be challenged to
learn about theory, methods and applications of a range of Bayesian models
including mixtures, spatio-temporal models, hidden Markov models and
experimental design, and computational approaches including Markov chain
Monte Carlo and Approximate Bayesian Computation. This hands-on course pays
equivalent attention to theory and application, foundation and frontiers in
Bayesian modelling and analysis. While the focus of the case studies is on
sport, both sporting novices and lovers of sports are welcome, noting that
the learning obtained in the course will be widely applicable to many other
areas.

COURSE SCHEDULE

Day 1: Lectures on introduction to Bayesian modelling and computation.
Presentation of Problem 1: ranking and benchmarking athletes. Discussion and
implementation of potential Bayesian hierarchical models and computational
solutions. Communication of results.

Day 2: Lectures on foundational Bayesian theory. Presentation of Problem 3:
modelling swimmers' effective work per stroke. Discussion and implementation
of potential Bayesian high dimensional regression models and computational
solutions. Communication of results. Presentation of Problem 4: modelling
cyclists' wearable data. Discussion and implementation of potential (marked)
time series models and computational solutions. Communication of results.

Day 3: Lectures on foundational Bayesian computation. Presentation of
Problem 5: optimising athletes' resilience. Discussion and implementation of
potential Bayesian mixture models to relate performance, fatigue and recovery.
Communication of results.

Day 4: Lectures on foundational Bayesian computation and frontier Bayesian
theory. Presentation of Problem 6: optimal sampling strategies. Discussion
and implementation of potential Bayesian experimental design methods for
acquiring data from athletes. Presentation of Problem 7: using video data
to compare planned and set play in team sports. Discussion and implementation
of potential Bayesian spatio-temporal models. Communication of results.

Day 5: Lectures on frontier Bayesian computation. Finalisation of problems
1-7. Extensions. Concluding remarks


PRACTICAL INFORMATION

The school will replicate the successful format of the previous years, and
will feature lectures and practical sessions (run by a junior researcher),
as well as participants' talks. It will start on Monday after lunch and end
on Friday before lunch; Wednesday afternoon is free. Accommodation is
available either at the Villa guesthouse or in downtown hotels (info will
appear soon on the website). Como can be easily reached by train from Milan
and its airports. More details are available on the website.

--
Fabrizio Ruggeri                    fabrizio AT mi.imati.cnr.it
CNR IMATI                           tel +39 0223699532
Via Bassini 15                      fax +39 0223699538
I-20133 Milano (Italy)              web.mi.imati.cnr.it/fabrizio

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