There are still a few places left. Please register soon.
Best wishes, Sujit
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Announce: Two Short-courses on Bayesian Modelling and Computation and
Hierarchical Modelling of Spatial and Temporal Data
Lecturers: Alan Gelfand (Duke University, USA) and Sujit Sahu
(University of Southampton, UK)
Date: June 1-4, 2015
Venue: University of Southampton, UK.
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Course 1: Introduction to Bayesian Modelling and Computation.
Date: June 1-2, 2015 (Monday-Tuesday)
The first short-course is aimed at applied scientists who are thinking
of using Bayesian methods and would like to receive a gentle
introduction with a large practical component.
No previous knowledge of Bayesian methods is necessary. However,
familiarity with standard probability distributions (normal, binomial,
Poisson, gamma) and standard statistical methods such as multiple
regression will be assumed.
Theory lectures on the Bayes theorem, elements of Bayesian inference,
choice of prior distributions and introduction to MCMC will be followed
by hands-on experience using R and the WinBUGS software. Some of the
data analysis examples discussed here will be enhanced by using spatial
statistics methods in the second course.
More advanced methods using Hamiltonian MCMC, reversible jump, INLA,
Variational Bayes, and ABC will also be introduced.
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Course 2: Hierarchical Modelling of Spatial and Temporal Data.
Date: June 3-4, 2015 (Wednesday-Thursday)
This course will provide an overview of current ideas in statistical
inference methods appropriate for analysing various types of spatially
point referenced data, some of which may also vary temporally. The
course will cover hierarchical modelling for spatial response data,
including Bayesian kriging and lattice modelling with many practical
examples. Hands-on training using R and WinBugs will be provided.
Participants should have a good understanding of mathematical statistics
(such as a typical Bachelor's degree in mathematics, statistics or a
related discipline from a UK university). In addition, basic familiarity
with standard statistical models such as multiple linear regression and
computing will be required. Attending the preceding two-day course on
Bayesian statistics and MCMC will help prepare for this course,
although that is not an absolute pre-requisite.
If you are unsure about the suitability of your background for the
course, please email Prof Sujit Sahu ([log in to unmask]) who can advise.
For further information and registration please visit:
http://www.southampton.ac.uk/~sks/course2015/index.php
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--
Prof Sujit Sahu
Mathematical Sciences & Southampton Statistical Sciences Research
Institute (S3RI) University of Southampton Southampton, SO17 1BJ UK
+44-(0)23-8059-5123
[log in to unmask]
http://www.soton.ac.uk/~sks/
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