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")
)

## Arguments

o 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).

## Value

Named numeric vector with either one or 5 values, as selected by the user.

## 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)))

## Examples

if(interactive()){

root_mean_squared_error(
o = runif(10),
p = runif(10)
)

}