rmase {bvhar}

Evaluate the Model Based on RMASE (Relative MASE)

Description

This function computes RMASE given prediction result versus evaluation set.

Usage

rmase(x, pred_bench, y, ...)

## S3 method for class 'predbvhar'
rmase(x, pred_bench, y, ...)

## S3 method for class 'bvharcv'
rmase(x, pred_bench, y, ...)

Arguments

x

Forecasting object to use

pred_bench

The same forecasting object from benchmark model

y

Test data to be compared. should be the same format with the train data.

...

not used

Details

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.

Value

RMASE vector corresponding to each variable.

References

Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679–688.