Projective Graph Residualization: Variation-Allocation Frontiers for Control-Function IV

תקציר מקורי באנגליתarXiv:2606.14636v2 Announce Type: replace Abstract: Control-function instrumental-variable estimators pass an estimated first-stage residual to an outcome model. The residual must retain the latent control direction while leaving enough treatment variation to identify the structural effect. These demands conflict when the systematic signal is locally smooth but discontinuous across unknown feature-graph boundaries: interpolation can erase the residual, whereas isotropic smoothing can move systematic variation across a boundary. We propose Adaptive Anisotropic Instrumental Heat Flow (A-IHF), which adapts edge conductance from pilot treatment contrasts, extracts a generated control with a complementary sparse resolvent, and tunes without outcomes. For a linear control-function regression, on