jax.scipy.stats.betabinom.logpmf

jax.scipy.stats.betabinom.logpmf(k, n, a, b, loc=0)

Beta-binomial log probability mass function.

JAX implementation of scipy.stats.betabinom logpmf

The beta-binomial distribution’s probability mass function is defined as

\[f(k, n, a, b) = {n \choose k}\frac{B(k+a,n-k-b)}{B(a,b)}\]

where \(B(a, b)\) is the beta() function. It is defined for \(n\ge 0\), \(a>0\), \(b>0\), and non-negative integers k.

Parameters:

• k (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, value at which to evaluate the PMF

• n (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, distribution shape parameter

• a (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, distribution shape parameter

• b (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, distribution shape parameter

• loc (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, distribution offset parameter

Returns:

array of logpmf values

Return type:

Array

See also

jax.scipy.stats.betabinom.pmf()