Tag: cpcr

Calibrated Principal Component Regression arXiv:2510.19020v1 Announce Type: new Abstract: We propose a new method for statistical inference in generalized linear models. In the overparameterized regime, Principal Component Regression (PCR) reduces variance by projecting high-dimensional data to a low-dimensional principal subspace before fitting. However, PCR incurs truncation bias whenever the true regression vector has mass outside…