Regression Diagnostics

Wed, 11 Nov 2026 14:00:00 +1100

the exact \(t\) and \(F\) theory on estimation & inference is bought with assumptions: a linear mean, uncorrelated errors of constant variance, gaussian noise. diagnostics are how those assumptions are audited after the fit, and nearly all of them run through one matrix — the hat matrix \(\mathbf{H}\), whose diagonal measures how much each observation can pull the fit and whose complement \(\mathbf{I} - \mathbf{H}\) carries the residuals. 𐃏

Residuals on Aayush Bajaj's Augmenting Infrastructure

Regression Diagnostics