scoringrules.logs_hypergeometric#
- scoringrules.logs_hypergeometric(obs: ArrayLike, m: ArrayLike, n: ArrayLike, k: ArrayLike, *, backend: Backend = None) ArrayLike#
Compute the logarithmic score (LS) for the hypergeometric distribution.
This score is equivalent to the negative log likelihood of the hypergeometric distribution
- Parameters:
- obsarray_like
The observed values.
- marray_like
Number of success states in the population.
- narray_like
Number of failure states in the population.
- karray_like
Number of draws, without replacement. Must be in 0, 1, …, m + n.
- backendstr
The name of the backend used for computations. Defaults to ‘numba’ if available, else ‘numpy’.
- Returns:
- scorearray_like
The LS between obs and Hypergeometric(m, n, k).
Examples
>>> import scoringrules as sr >>> sr.logs_hypergeometric(5, 7, 13, 12)