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 ...
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