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, ...)
directional_accuracy_measures
```

An object of class `list`

of length 3.

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

- .actual
A vector of responses matching the fitted values (for forecast accuracy,

`new_data`

must be provided).- na.rm
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.

`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.