scoringrules.logs_t

scoringrules.logs_t(obs: ArrayLike, df: ArrayLike, location: ArrayLike = 0.0, scale: ArrayLike = 1.0, *, backend: Backend = None) → ArrayLike

Compute the logarithmic score (LS) for the Student’s t distribution.

This score is equivalent to the negative log likelihood of the t distribution.

Parameters:

obsarray_like

The observed values.

dfarray_like

Degrees of freedom parameter of the forecast t distribution.

locationarray_like

Location parameter of the forecast t distribution.

sigmaarray_like

Scale parameter of the forecast t distribution.

Returns:

scorearray_like

The LS between t(df, location, scale) and obs.

Examples

>>> import scoringrules as sr
>>> sr.logs_t(0.0, 0.1, 0.4, 0.1)