root_mean_squared_error {spatialRF} | R Documentation |
RMSE and normalized RMSE
Description
Computes the rmse or normalized rmse (nrmse) between two numeric vectors of the same length representing observations and model predictions.
Usage
root_mean_squared_error(
o,
p,
normalization = c("rmse", "all", "mean", "sd", "maxmin", "iq")
)
Arguments
o |
Numeric vector with observations, must have the same length as |
p |
Numeric vector with predictions, must have the same length as |
normalization |
character, normalization method, Default: "rmse" (see Details). |
Details
The normalization methods go as follows:
-
"rmse"
: RMSE with no normalization. -
"mean"
: RMSE dividied by the mean of the observations (rmse/mean(o)). -
"sd"
: RMSE dividied by the standard deviation of the observations (rmse/sd(o)). -
"maxmin"
: RMSE divided by the range of the observations (rmse/(max(o) - min(o))). "
iq"
: RMSE divided by the interquartile range of the observations (rmse/(quantile(o, 0.75) - quantile(o, 0.25)))
Value
Named numeric vector with either one or 5 values, as selected by the user.
Examples
if(interactive()){
root_mean_squared_error(
o = runif(10),
p = runif(10)
)
}