scoringrules.logs_exponential

scoringrules.logs_exponential(obs: ArrayLike, rate: ArrayLike, *, backend: Backend = None) → ArrayLike

Compute the logarithmic score (LS) for the exponential distribution.

This score is equivalent to the negative log likelihood of the exponential distribution

Parameters:

obsarray_like

The observed values.

ratearray_like

Rate parameter of the forecast exponential distribution.

backendstr

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

Returns:

scorearray_like

The LS between Exp(rate) and obs.

Examples

>>> import scoringrules as sr
>>> sr.logs_exponential(0.8, 3.0)