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Evaluate the Model Based on RMAPE (Relative MAPE)

Source: R/summary-forecast.R
rmape.Rd

This function computes RMAPE given prediction result versus evaluation set.

Usage

rmape(x, pred_bench, y, ...)

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

# S3 method for class 'bvharcv'
rmape(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

Value

RMAPE vector corresponding to each variable.

Details

RMAPE is the ratio of MAPE of given model and the benchmark one. Let \(MAPE_b\) be the MAPE of the benchmark model. Then

$$RMAPE = \frac{mean(MAPE)}{mean(MAPE_b)}$$

where \(MAPE\) is the MAPE of our model.

References

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