Bayes meets Bamberg: Workshop on Bayesian Statistics

INVITATION AND EXTENDED CALL FOR PAPERS for “Bayes meets Bamberg: Workshop on Bayesian Statistics” on 22-23 June 2023 (new date!) at the University of Bamberg


Please send an email to workshop.stat-oek(at) if you want to attend, with the reference „BMB workshop registration“.  Registration is free of charge, but we kindly ask you to notify us if you cannot participate and have to withdraw your registration. The maximum participant number is capped at 50 and registrations are handled on a first-come, first-served basis.

General information on the workshop topic

Bayesian Statistics provide an intuitive approach to interpreting what we can learn from data, and how we can update prior knowledge. With growing access to easy-to-use software for Bayesian methods, this approach has become well established within the scientific community. This workshop provides a forum for an interdisciplinary exchange of Bayesian applications and ideas.

Program and course of the workshop

The workshop is a two-day workshop consisting of two parts, with the first day being a “gentle” introduction to Bayesian concepts for anyone who is interested in but not yet quite familiar with Bayesian Statistics. The second day consists of a keynote and sessions with presentations on applied Bayesian research.

Day 1: A Primer on Bayesian Statistics

David Kaplan will give an introduction to Bayesian Statistics. He is Patricia Busk Professor of Quantitative Methods in the Department of Educational Psychology at the University of Wisconsin – Madison, and has published extensively on Bayesian methods.

9 am Reception
9:30 - 12:30 pm Part I
12:30 - 1:30 pmLunch Break
1:30 - 5 pmPart II                                                                                                                                                                                                 

Day 2: Bayesian Statistics in Practice

9 amReception
9:30-10:30 amKeynote by David Kaplan: Probabilistic Forecasting with International Large-Scale Assessments: Applications to the UN Sustainable Development Goals
10:30-10:45 amCoffee Break
10:45-11:30 am

Mariana Nold: Bayesian Methods for Assessing Model Uncertainty with Complex Data

11:30-12:15 pmTobias Eilert/ Miguel Cordero: A Modern Approach to Stability Studies via Bayesian Linear Mixed Models Incorporating Auxiliary Effects
12:15-1:15 pmLunch Break
1:15-1:45 pmJulius Goes: Bayesian Computation with Nimble: Introduction and Applications
1:45-2:15 pmTheodor Rogalski: Spare Part Demand Recognition Using a Bayesian Gompertz Model
2:15 pmFarewell