Synonym: Root Mean Square Deviation (RMSD) = Root Mean Square Error (RMSE)
A number characterizing the model prediction quality ( goodness of fit ) between the datasets of a given variable and its estimator
:
RMSD(x, \hat x) = \sqrt{MSE(x, \hat x)} = \sqrt{ \frac{1}{n} \sum_{i=1}^n (x_i - \hat x_i)^2 } |
where
| a variable represented by data set | |
estimator of variable | |
discrete set of numerical samples of variable | |
discrete set of predictors for the corresponding samples of variable | |
| Mean Square Error (MSE) |
The RMSD is a square root of Mean Square Error (MSE) between the datasets of a given variable and its estimator
.
The key benefit of using RMSD instead of MSE is that it is expressed in the same units as the base property () while MSE is expressed in square units of the base property.
The terms RMSE and RMSD are used in mathematics and engineering interchangeably.
See also
Statistics / Mean Square Error (MSE)