Bayesian Analysis with R

WinBUGS and R

During the last years Bayesian statistical modelling has become one of the most fashionable statistical approaches in scientific and technological applications. There are at least two reasons for this trend. One is the current demand of building statistical models which deal with multiple sources of variability. Bayesian models are well suited for this task and they provide an avenue to combine complex information in a coherent form. Successful examples of this approach include innumerable applications of hierarchical modelling.

The other reason is the computation revolution produced by the rediscovery of Markov chain Monte Carlo (MCMC) techniques in statistics, together with their implementation in public domain and friendly to use statistical software like WinBUGS and many R packages. As a result, researchers can construct arbitrary complex statistical models, which may better reflect the phenomena of interest.

This course has two aims. First, it presents a conceptual introduction to Bayesian statistical techniques to practitioners and researchers. Second, it provides a large number of case studies analysed with R and WinBUGS. These examples can serve as a ready to use templates for immediate applications. The course follows a practical perspective rather than a theoretical one. We focus on model building with WinBUGS and interacting WinBUGS with R. Some advantages of running WinBUGS within R include the ability to perform effective model checking, sensitivity and convergence analysis and using the extremely powerful graphical capabilities of R. The target audience are statisticians and data analysts who have familiarity in classical methods such as generalized linear models and random-effects modelling. Neither experience in Bayesian methods nor in WinBUGS will be assumed. However, some working experience in R will be.

Die Kurssprache und die Kursunterlagen sind Englisch; Diskussionen und Hilfestellungen sind in Deutsch, Englisch und Spanisch möglich.

german description available here

This course is very popular among students and postgraduates. Hence we have a special arrangement for students.

course

3 days, €915,00 + VAT = €1088,85 all-inclusive

Full 8 hours per day, complete set of literature, free internet access everywhere, lended notebook, full board, drinks ( special wines go extra ), cakes and pastries, sauna, evening entertainment.

Additional or reduced services by request:

• extra fee for single room 129,00€ + VAT. = 138,03€ per night (sorry, we are very short of rooms)
• extra fee for double room 59,00€ + VAT. = 63,13€ per night
• extra fee for single room in our shared flat 83,00€ + VAT. = 88,81€ per night
• reduction on doing without full board: 29,41 € + VAT = 35 € per day
• reduction on doing without evening entertainment: 8,40 € + VAT = 10 €

tax deductions * cancellation

Dates

01.12. - 03.12.2011 registration

Instructors

Dr. rer. nat. Pablo E. Verde arbeitet auf dem Gebiet der statistischen Modellierung in der medizinischen und klinischen Forschung, aktuell in der Evidenz-Synthese (Meta-Analysen). Er leitet die Arbeitsgruppe Biometrie im Koordinierungszentrum für klinische Studien der Heinrich-Heine-Universität Düsseldorf und forscht am Institut für Medizinische Soziologie der Heinrich-Heine Universität Düsseldorf. Er hat mehr als 20 Jahre internationale Erfahrung in statistischer Beratung, Forschung und Lehre auf den Gebieten Medizin, Landwirtschaft, Gesundheitsforschung und Risikoanalyse Finanz-Econometrie.

Pablo ist Experte der Statistiksoftware R und WinBUGS für MCMC Berechnungen. Seit 1998 ist er aktives Mitglied der R Community, wo er für die Übersetzung von R ins Spanische verantwortlich ist.

Seit 1990 lehrt er die Anwendung von S und R, zunächst für die Finanz-Branche, seit 2000 im akademischen Bereich.
Pablo ist visiting Lecturer am Department of Statistics an der Stanford University und seit 2007 Stanford community member. Seit 2000 ist Pablo Mitglied der Royal Statistical Society.

English:

Since 1990 Pablo teaches the use of S and R, first for finance industry, since 2000 in the field of academics.
Pablo ist visiting lecturer at Department of Statistics of Stanford University and since 2007 Stanford community member. Since 2000 Pablo is a member of Royal Statistical Society.

Pablo is an expert for the software R and WinBUGS for MCMC calculations. Since 1998 he is an active member of the R community, translating R into Spanish.

course prerequisites

Der Kurs wendet sich an Datenanalysten mit praktischer Erfahung in der Statistiksprache R. This course is meant for data analists with practical experience in the R programming language and software environment for statistical computing and graphics.