scoringrules.dssuv_ensemble

scoringrules.dssuv_ensemble(obs: Array, fct: Array, m_axis: int = -1, *, bias: bool = False, backend: Backend = None) → Array

Compute the Dawid-Sebastiani-Score for a finite univariate ensemble.

The Dawid-Sebastiani Score for an ensemble forecast is defined as

\[\text{DSS}(F_{ens}, y) = \frac{(y - \bar{x})^2}{\sigma^2} + 2 \log \sigma\]

where \(\bar{x}\) and \(\sigma\) are the mean and standard deviation of the ensemble members.

Parameters:

obsarray_like

The observed values.

fctarray_like, shape (…, m)

The predicted forecast ensemble, where the ensemble dimension is by default represented by the last axis.

m_axisint

The axis corresponding to the ensemble. Default is the last axis.

biasbool

Logical specifying whether the biased or unbiased estimator of the standard deviation should be used to calculate the score. Default is the unbiased estimator (bias=False).

backendstr

The name of the backend used for computations. Defaults to ‘numba’ if available, else ‘numpy’.

Returns:

score: Array

The computed Dawid-Sebastiani Score.