MSE(x, \hat x) = \frac{1}{n} \sum_{i=1}^n (x_i - \hat x_i)^2 |
where
x | a variable under study |
---|---|
\hat x | predictor of variable x |
\{ x_1, \, x_2, \, x_3 , ... x_N \} | discrete set of numerical samples of variable x |
\{ \hat x_1, \, \hat x_2, \, \hat x_3 , ... \hat x_N \} | discrete set of predictors for the corresponding samples of variable x |