Mallows's C_p

In statistics, Mallows's ${\textstyle {\boldsymbol {C_{p}}}}$, named for Colin Lingwood Mallows, is used to assess the fit of a regression model that has been estimated using ordinary least squares. It is applied in the context of model selection, where a number of predictor variables are available for predicting some outcome, and the goal is to find the best model involving a subset of these predictors. A small value of ${\textstyle C_{p}}$ means that the model is relatively precise.

Mallows's C_p has been shown to be equivalent to Akaike information criterion in the special case of Gaussian linear regression.