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

## Arguments

.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. |

An object of class `list`

of length 3.

## Details

`MDA()`

: Mean Directional Accuracy
`MDV()`

: Mean Directional Value
`MDPV()`

: Mean Directional Percentage Value

## References

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