 Reciprocal-predictor regression

A reciprocal-predictor linear regression uses $\mathbb{E}(Y\mid v)=\alpha +\beta /v$ for nonzero predictor $v$. It remains linear in its coefficients. Its flattening shape can suit a saturating response over a positive predictor range; residual checks and cross-validation must assess adequacy, and extrapolation toward zero is hazardous.