mae {bvhar} | R Documentation |
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.
[Package bvhar version 2.0.1 Index]