jax.scipy.stats.bernoulli.cdf

jax.scipy.stats.bernoulli.cdf(k, p)

Bernoulli cumulative distribution function.

JAX implementation of scipy.stats.bernoulli cdf

The Bernoulli cumulative distribution function is defined as:

\[f_{cdf}(k, p) = \sum_{i=0}^k f_{pmf}(k, p)\]

where \(f_{pmf}(k, p)\) is the Bernoulli probability mass function jax.scipy.stats.bernoulli.pmf().

Parameters:

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

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

• loc – arraylike, distribution offset

Returns:

array of cdf values

Return type:

Array

See also

• jax.scipy.stats.bernoulli.logpmf()

• jax.scipy.stats.bernoulli.pmf()

• jax.scipy.stats.bernoulli.ppf()