Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

Partial Least Squares (PLS) regression extracts a few outcome-aligned directions in a high-dimensional X and is widely used across applied science, but inference on the resulting fit is either expensive, biased and discouraged, or absent.