Developments in Statistical Modelling

Jochen Einbeck is Professor of Statistics at Durham University, UK, Co-Director of the Durham Research Methods Centre, and Chair of IWSM 2024. He has been a regular attendee of the IWSM conferences since co-hosting the workshop in 2006 in Galway. He is Associate Editor of Statistical Modelling and Advances in Statistical Analysis, having previously served as Associate Editor of CSDA and Statistics. His research interests include mixture models, nonparametric regression, principal curves and random effect modelling.Hyeyoung Maeng is an Assistant Professor of Statistics at Durham University, UK. Her research interests include change-point and feature detection, high-dimensional statistics, data-adaptive and multiscale methods and factor analysis. She is also interested in applying statistical methods in economics, finance and environment.Emmanuel Ogundimu is an Associate Professor of Statistics at Durham University, UK and Co-Director of the Durham Biostatistics Unit. He leads a team of researchers on statistical aspects of clinical trials. His scholarly work centers on applying and developing statistical methodology and learning algorithms.Konstantinos Perrakis is an Assistant Professor of Statistics at Durham University, UK. His research focuses on aspects of Bayesian and computational statistics and on statistical models for high-dimensional problems. He has applied his research to the fields of biomedicine, epidemiology and transportation.

• REML for two dimensional P splines.- Learning Bayesian networks from ordinal data The Bayesian way.- Latent Dirichlet allocation and hidden Markov models to identify public perception of sustainability in social media data.- Bayesian approaches to model overdispersion in Spatio temporal binomial data.- Elicitation of priors for intervention effects in educational trial data.- Elicitation of priors for intervention effects in educational trial data.- Optimism correction of the AUC with complex survey data.- Statistical models for patient centered outcomes in clinical studies.- Bayesian hidden Markov models for early warning.- A Bayesian Markov-switching for smooth modelling of extreme value distributions.