High-dimensional factor models provide a principled framework for analysing vast panels of time series by capturing their pervasive co-movements through a small number of latent factors. These models ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results