climpred.metrics._median_absolute_error#
- climpred.metrics._median_absolute_error(forecast: Dataset, verif: Dataset, dim: str | List[str] | None = None, **metric_kwargs: Any) Dataset [source]#
Median Absolute Error.
The median of the absolute differences between forecasts and verification data. Applying the median function to absolute error makes it more robust to outliers.
- Parameters:
forecast – Forecast.
verif – Verification data.
dim – Dimension(s) to perform metric over.
metric_kwargs – see
xskillscore.median_absolute_error()
Notes
minimum
0.0
maximum
∞
perfect
0.0
orientation
negative
See also
Example
>>> HindcastEnsemble.verify( ... metric="median_absolute_error", ... comparison="e2o", ... alignment="same_verifs", ... dim="init", ... ) <xarray.Dataset> Dimensions: (lead: 10) Coordinates: * lead (lead) int32 1 2 3 4 5 6 7 8 9 10 skill <U11 'initialized' Data variables: SST (lead) float64 0.06077 0.06556 0.06368 ... 0.1131 0.142 0.1466 Attributes: prediction_skill_software: climpred https://climpred.readthedocs.io/ skill_calculated_by_function: HindcastEnsemble.verify() number_of_initializations: 64 number_of_members: 10 alignment: same_verifs metric: median_absolute_error comparison: e2o dim: init reference: []