climpred.metrics._median_absolute_error

climpred.metrics._median_absolute_error(forecast: xarray.Dataset, verif: xarray.Dataset, dim: Optional[Union[str, List[str]]] = None, **metric_kwargs: Any) xarray.Dataset[source]

Median Absolute Error.

median(|f - o|)

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

Notes

minimum

0.0

maximum

perfect

0.0

orientation

negative

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:                     []