Multicollinearity-agnostic feature screening for non-Euclidean responses: a factor adjusted approach
In high-dimensional settings, multicollinearity is a pervasive issue that can substantially impair the performance of feature screening methods based on marginal Fr\'echet regression. Feature screening for non-Euclidean responses becomes unreliable when ultrahigh-dimensional predictors suffer from multicollinearity, be...