A collection of accuracy measures based on the accuracy of the prediction's direction (say, increasing or decreasing).

MDA(.resid, .actual, na.rm = TRUE, reward = 1, penalty = 0, ...)

MDV(.resid, .actual, na.rm = TRUE, ...)

MDPV(.resid, .actual, na.rm = TRUE, ...)




A vector of residuals from either the training (model accuracy) or test (forecast accuracy) data.


A vector of responses matching the fitted values (for forecast accuracy, new_data must be provided).


Remove the missing values before calculating the accuracy measure

reward, penalty

The weights given to correct and incorrect predicted directions.


Additional arguments for each measure.


An object of class list of length 3.


MDA(): Mean Directional Accuracy MDV(): Mean Directional Value MDPV(): Mean Directional Percentage Value


Blaskowitz and H. Herwartz (2011) "On economic evaluation of directional forecasts". International Journal of Forecasting, 27(4), 1058-1065.