mae {bvhar}

Evaluate the Model Based on MAE (Mean Absolute Error)

Description

This function computes MAE given prediction result versus evaluation set.

Usage

mae(x, y, ...)

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

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

Arguments

x

Forecasting object

y

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

...

not used

Details

Let e_t = y_t - \hat{y}_t. MAE is defined by

MSE = mean(\lvert e_t \rvert)

Some researchers prefer MAE to MSE because it is less sensitive to outliers.

Value

MAE vector corressponding 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.