Summary
Statistical models — probabilistic descriptions of the processes that give rise to observed data — are an integral component of modern science across various disciplines, enabling researchers to learn from the data they collect and make predictions about future events. This research addresses the important challenges of model selection and model combination within the Bayesian statistical framework. Model selection involves choosing, from a collection of candidate models, the single model that best describes the data, while model combination involves constructing a hybrid model that outperform
