View source: R/root_mean_squared_error.R
root_mean_squared_error | R Documentation |
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") )
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). |
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)))
Named numeric vector with either one or 5 values, as selected by the user.
if(interactive()){ root_mean_squared_error( o = runif(10), p = runif(10) ) }
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