ecpc: an R-package for generic co-data models for high-dimensional prediction

BACKGROUND: High-dimensional prediction considers data with more variables than samples. Generic research goals are to find the best predictor or to select variables. Results may be improved by exploiting prior information in the form of co-data, providing complementary data not on the samples, but on the variables. We consider adaptive ridge...

The Impact of Infrastructure Design on Cycling Safety

Increasing concerns about the safety of cyclists request for more research in how infrastructure can be improved to increase cycling safety. Literature in the prediction of bicycle crash risk however is very limited. Also the amount of available (exposure) data was often very limited. The aim of this study was to provide a better understanding...

Relations between the obstacle space of cycling infrastructure and bicycle crashes: An analysis of Amsterdam

The objective of this study is to strengthen literature about cyclist safety and help prevent bicycle crashes in the future. It looks into the gap about the relation between the obstacle space of cycling infrastructure (that involves the space that is available for cyclists to avoid crashes with the obstacles therein) and the visibility thereof,...