scoringrules.logs_binomial

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scoringrules.logs_binomial#

scoringrules.logs_binomial(obs: ArrayLike, n: ArrayLike, prob: ArrayLike, *, backend: Backend = None) → ArrayLike#

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

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

Parameters:
obsarray_like

The observed values.

narray_like

Size parameter of the forecast binomial distribution as an integer or array of integers.

probarray_like

Probability parameter of the forecast binomial distribution as a float or array of floats.

backendstr

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

Returns:
scorearray_like

The LS between Binomial(n, prob) and obs.

Examples

>>> import scoringrules as sr
>>> sr.logs_binomial(4, 10, 0.5)
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