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Showing content from https://www.pymc.io/projects/docs/en/stable/api/distributions/generated/pymc.Bernoulli.html below:

pymc.Bernoulli — PyMC 5.25.1 documentation

pymc.Bernoulli#
class pymc.Bernoulli(name, *args, **kwargs)[source]#

Bernoulli distribution.

The Bernoulli distribution describes the probability of successes (x=1) and failures (x=0). The pmf of this distribution is

\[f(x \mid p) = p^{x} (1-p)^{1-x}\]

(Source code, png, hires.png, pdf)

The bernoulli distribution can be parametrized either in terms of p or logit_p. The link between the parametrizations is given by

\[logit(p) = ln(\frac{p}{1-p})\]

Parameters:
ptensor_like of float

Probability of success (0 < p < 1).

logit_ptensor_like of float

Alternative log odds for the probability of success.

Methods


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