Computes the rmse or normalized rmse (nrmse) between two numeric vectors of the same length representing observations and model predictions.
root_mean_squared_error(
o,
p,
normalization = c("rmse", "all", "mean", "sd", "maxmin", "iq")
)
Numeric vector with observations, must have the same length as p
.
Numeric vector with predictions, must have the same length as o
.
character, normalization method, Default: "rmse" (see Details).
Named numeric vector with either one or 5 values, as selected by the user.
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)))
if(interactive()){
root_mean_squared_error(
o = runif(10),
p = runif(10)
)
}