Chair of Spatial Data Science and Statistical Learning

This year the International Workshop on Statistical Modelling (IWSM) took place in Durham, UK. We actively participated in the annual conference again this year and are proud to have received an award!

Dr. Colin Griesbach opened the conference with his presentation on model-based gradient boosting methods for GAMLSS models applied to data from cystic fibrosis patients. The conference article has been published in the conference proceedings.

Lars Kniepergave a presentation on the phenomenon of spatial confounding, which can be resolved in model-based gradient boosting using the spatial+ approach. He illustrated his approach using AirBnB data. The corresponding short article has been published by Springer.

Quentin Seifert´s paper entitled ‘Function-on-scalar regression via first-order gradient-based optimization’ combines classical statistics with elements from neural networks and allows to analyse a large amount of parking data during the COVID-19 pandemic and identify patterns in shopping behaviour.

Dr. Joaquin Cavieres also presented part of his research comparing approximated Gaussian random fields with different parameterization approaches. The conference article has also been published.

Sophie Potts presented her work on the application of joint models for longitudinal and time-to-event data in the social sciences as a poster. The method, which originated in biostatistics, was applied to an example from family sociology. Sophie's novel application and accessible presentation was honoured with the ‘Best Student Poster Award’. The award-winning poster can now be admired in the corridor of our offices.

After almost two years of MWK-funded work, we have a sizable collection of shinys that help explain various statistical concepts. They are available on this page. Most have been created directly through specific lectures, but should also work individually as an aid to self-learning. Have fun while playing!