This function computes MASE given prediction result versus evaluation set.
mase(x, y, ...)# S3 method for predbvhar
mase(x, y, ...)
# S3 method for bvharcv
mase(x, y, ...)
MASE vector corresponding to each variable.
Forecasting object
Test data to be compared. should be the same format with the train data.
not used
Let \(e_t = y_t - \hat{y}_t\). Scaled error is defined by $$q_t = \frac{e_t}{\sum_{i = 2}^{n} \lvert Y_i - Y_{i - 1} \rvert / (n - 1)}$$ so that the error can be free of the data scale. Then
$$MASE = mean(\lvert q_t \rvert)$$
Here, \(Y_i\) are the points in the sample, i.e. errors are scaled by the in-sample mean absolute error (\(mean(\lvert e_t \rvert)\)) from the naive random walk forecasting.
Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688.