 Mean squared prediction error

For a predictor $\hat{f}$ and an independent response $Y^{\ast }$ at covariate $X^{\ast }$, mean squared prediction error is $\mathbb{E}[(Y^{\ast }-\hat{f}(X^{\ast }){)}^2]$.