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Discrete
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.. currentmodule:: pymc
.. autosummary::
   :toctree: generated
   :template: distribution.rst

   Bernoulli
   BetaBinomial
   Binomial
   Categorical
   DiscreteUniform
   DiscreteWeibull
   Geometric
   HyperGeometric
   NegativeBinomial
   OrderedLogistic
   OrderedProbit
   Poisson

.. note::

   **OrderedLogistic and OrderedProbit:**
   The ``OrderedLogistic`` and ``OrderedProbit`` distributions expect the observed values to be 0-based, i.e., they should range from ``0`` to ``K-1``. Using 1-based indexing (like ``1, 2, 3,...K``) can result in errors.