egttools.distributions.multivariate_hypergeometric_pdf¶
- multivariate_hypergeometric_pdf(*args, **kwargs)¶
Overloaded function.
multivariate_hypergeometric_pdf(m: typing.SupportsInt | typing.SupportsIndex, k: typing.SupportsInt | typing.SupportsIndex, n: typing.SupportsInt | typing.SupportsIndex, sample_counts: collections.abc.Sequence[typing.SupportsInt | typing.SupportsIndex], population_counts: typing.Annotated[numpy.typing.NDArray[numpy.uint64], “[m, 1]”]) -> float
Calculate the probability mass function of a multivariate hypergeometric distribution.
This function returns the probability of observing sample_counts when drawing a sample of size n from a population of size m.
- mint
Population size.
- kint
Number of categories in the population.
- nint
Sample size.
- sample_countslist[int]
Counts for each category in the sample. Must sum to n.
- population_countsnumpy.ndarray
Counts for each category in the population. Must sum to m.
- float
Probability of observing sample_counts.
egttools.distributions.binom egttools.distributions.comb
multivariate_hypergeometric_pdf(m: typing.SupportsInt | typing.SupportsIndex, k: typing.SupportsInt | typing.SupportsIndex, n: typing.SupportsInt | typing.SupportsIndex, sample_counts: typing.Annotated[numpy.typing.NDArray[numpy.uint64], “[m, 1]”], population_counts: typing.Annotated[numpy.typing.NDArray[numpy.uint64], “[m, 1]”]) -> float
Calculate the probability mass function of a multivariate hypergeometric distribution.
This function returns the probability of observing sample_counts when drawing a sample of size n from a population of size m.
- mint
Population size.
- kint
Number of categories in the population.
- nint
Sample size.
- sample_countsnumpy.ndarray
Counts for each category in the sample. Must sum to n.
- population_countsnumpy.ndarray
Counts for each category in the population. Must sum to m.
- float
Probability of observing sample_counts.
egttools.distributions.binom egttools.distributions.comb