The analysis of nonstationary time series under a Bayesian paradigm integrates prior knowledge with flexible probability models to capture evolving dynamics. Unlike stationary processes, whose ...
Bayesian additive modelling has emerged as a powerful framework for analysing datasets characterised by large numbers of predictors and complex response patterns. At its core, the methodology employs ...