rmse

0th

Percentile

rmse

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)

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. 10.1111/sum.12694

Aliases
  • rmse
Examples
# NOT RUN {
obs<-c(1:10)
pred<-c(1, 1 ,3, 2, 4, 5, 6, 8, 7, 10)
rmse(o=obs, p=pred)

# }
Documentation reproduced from package valmetrics, version 1.0.0, License: MIT + file LICENSE

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