Root mean square error is commonly used in climatology, forecasting, and regression analysis to verify experimental results.

Why root mean square error is used?

The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed. ... RMSD is the square root of the average of squared errors.

When should RMSE be used?

Since the errors are squared before they are averaged, the RMSE gives a relatively high weight to large errors. This means the RMSE is most useful when large errors are particularly undesirable. Both the MAE and RMSE can range from 0 to ∞. They are negatively-oriented scores: Lower values are better.