Measure of average percentage‐weighted directional accuracy in forecast tasks.
Details
$$ \mathrm{MDPV} = \frac{1}{n-1} \sum_{i=2}^n \left\lvert\frac{y_i - y_{i-1}}{y_{i-1}}\right\rvert \times \begin{cases} +1, & \text{if }\mathrm{sign}(y_i - y_{i-1}) = \mathrm{sign}(\hat y_i - \hat y_{i-1}),\\ -1, & \text{otherwise.} \end{cases} $$
Dictionary
This mlr3::Measure can be instantiated via the dictionary mlr3::mlr_measures or with the associated sugar function mlr3::msr():
Meta Information
Task type: “regr”
Range: \((-\infty, \infty)\)
Minimize: FALSE
Average: macro
Required Prediction: “response”
Required Packages: mlr3, mlr3forecast
References
Blaskowitz, Herwartz H (2011). “On economic evaluation of directional forecasts.” International Journal of Forecasting, 27(4), 1058–1065.
See also
Chapter in the mlr3book: https://mlr3book.mlr-org.com/chapters/chapter2/data_and_basic_modeling.html#sec-eval
Package mlr3measures for the scoring functions. Dictionary of Measures: mlr3::mlr_measures
as.data.table(mlr_measures)for a table of available Measures in the running session (depending on the loaded packages).Extension packages for additional task types:
mlr3proba for probabilistic supervised regression and survival analysis.
mlr3cluster for unsupervised clustering.
Other Measure:
mlr_measures_fcst.mda,
mlr_measures_fcst.mdv
Super class
mlr3::Measure -> MeasureMDPV