Targeted empirical Bayes for more supervised joint factor analysis
用于更强监督联合因子分析的目标经验贝叶斯方法
Joint Bayesian factor models are popular for characterizing relationships between multivariate correlated predictors and a response variable. Standard models assume that all variables, including both the predictors and the response, are conditionally independent given latent factors. In marginalizing out these factors, one obtains a low rank plus diagonal factorization for the joint covariance, which implies a linear regression for the response given the predictors. Although…