Error Types

Error types used when comparing datasets

Keyword	Description
`RMSE`	Root mean squared error: $$\Delta x = \sqrt{\sum_{i=1}^{N} (x_i - x_i^{ref})^2 \frac{1}{N}}$$
`MAAPE`	Mean arctangent average percentage error: $$\Delta x = 100 \sum_{i=1}^{N} \arctan{\left\|\frac{x_i - x_i^{ref}}{x_i}\right\|}$$
`MAPE`	Mean average percentage error: $$\Delta x = 100 \sum_{i=1}^{N} \left\|\frac{x_i - x_i^{ref}}{x_i}\right\|$$
`Percent`	Basic percentage error: $$\Delta x = 100 \frac{\sum_{i=1}^{N} \left\|x_i - x_i^{ref}\right\|}{\sum_{i=1}^{N} \left\|y_i\right\|}$$
`RFactor`	EPSR-style r-factor, equivalent to the mean squared error: $$\Delta x = \sum_{i=1}^{N} (x_i - x_i^{ref})^2 \frac{1}{N}$$
`Euclidean`	Euclidean distance: $$\Delta x = \frac{\sum_{i=1}^{N} \left\|x_i - x_i^{ref}\right\|}{\sum_{i=1}^{N} \left\|x_i^2\right\|}$$