The standard deviation of the errors or residuals, observed minus calculated, from a computational model:
\[{\rm{SEP}} = \sqrt \frac{\sum (Y_{o} - Y_{p})^{2}}{n - k}\] in which
\(Y_{o}\) is the observed value of
\(Y\),
\(Y_{p}\) is the predicted value of
\(Y\),
\(n\) is the number of observations, and
\(k\) is the number of terms in the model.
Note: Sometimes also labeled root mean square error of predication (RMSEP).
See also: standard error of estimates
Source:
PAC, 2016, 88, 239. 'Glossary of terms used in computational drug design, part II (IUPAC Recommendations 2015)' on page 257 (https://doi.org/10.1515/pac-2012-1204)