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 factor analysis offers a probabilistic framework for uncovering latent structure in datasets where the number of observed variables greatly exceeds the sample size. By positing that ...