This function computes RMASE given prediction result versus evaluation set.
rmase(x, pred_bench, y, ...)# S3 method for predbvhar
rmase(x, pred_bench, y, ...)
# S3 method for bvharcv
rmase(x, pred_bench, y, ...)
RMASE vector corresponding to each variable.
Forecasting object to use
The same forecasting object from benchmark model
Test data to be compared. should be the same format with the train data.
not used
RMASE is the ratio of MAPE of given model and the benchmark one. Let \(MASE_b\) be the MAPE of the benchmark model. Then
$$RMASE = \frac{mean(MASE)}{mean(MASE_b)}$$
where \(MASE\) is the MASE of our model.
Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688.