valmetrics (version 1.0.0)

rmse: 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.

Value

Root mean square error (RMSE)

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.

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

Examples

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

# }

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