https://doi.org/10.1351/goldbook.10151
In calibration for \(N\) calibration data where \(c_{i}\) is an observed value and \(\hat c_{i}\) is the value predicted by the calibration function. \[E_{\rm{MSEC}} = \frac{\sum\limits_{i\,=\,1}^{i\,=\,N} (\hat c_{i} - c_{i})^2}{N}\]
Note: Mean squared error of calibration is the square of the root mean squared error of calibration.