| rmse {valmetrics} | R Documentation |
rmse
Description
Calculates the Root mean square error (RMSE) from observed and predicted values.
Usage
rmse(o, p)
Arguments
o |
A numeric vector. Observed values. |
p |
A numeric vector. Predicted values. |
Details
Interpretation: smaller is better. RMSE is sometimes abbreviated RMS, RMSD or RMSEP. A smaller value means a smaller error. RMSE is similar to mean absolute error (MAE), median absolute deviation (MAD) and root median squared error (RmdSE) but is more sensitive to large errors.
Value
Root mean square error (RMSE)
Author(s)
Kristin Piikki, Johanna Wetterlind, Mats Soderstrom and Bo Stenberg, E-mail: kristin.piikki@slu.se
References
Piikki K., Wetterlind J., Soderstrom M., Stenberg B. (2021). Perspectives on validation in digital soil mapping of continuous attributes. A review. Soil Use and Management. doi: 10.1111/sum.12694
Examples
obs<-c(1:10)
pred<-c(1, 1 ,3, 2, 4, 5, 6, 8, 7, 10)
rmse(o=obs, p=pred)