Bayesian Multi-Group Functional Factor Models with Parameter-Expanded Cumulative Shrinkage Priors
采用参数扩展累积收缩先验的贝叶斯多组函数型因子模型
Functional data consist of trajectories observed over a continuous domain, such as time, space, or wavelength. Here we consider curves observed on different groups of subjects and propose a Bayesian multi-group functional factor analysis framework that jointly models the data via an explicit decomposition into group-specific mean functions and latent components that capture both common and distinct latent structures across the groups. We represent these functional components…