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docstring update OrderedProbit, ZeroInflatedBinomial, ZeroInflatedNeg…
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…ativeBinomial as in #5459
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mariyayb authored and aloctavodia committed Jul 13, 2022
1 parent b94b8b6 commit 7be9a19
Showing 1 changed file with 13 additions and 12 deletions.
25 changes: 13 additions & 12 deletions pymc/distributions/discrete.py
Original file line number Diff line number Diff line change
Expand Up @@ -1560,11 +1560,11 @@ class ZeroInflatedBinomial:
Parameters
----------
psi: float
psi : tensor_like of float
Expected proportion of Binomial variates (0 < psi < 1)
n: int
n : tensor_like of int
Number of Bernoulli trials (n >= 0).
p: float
p : tensor_like of float
Probability of success in each trial (0 < p < 1).
"""
Expand Down Expand Up @@ -1650,15 +1650,15 @@ def ZeroInfNegBinom(a, m, psi, x):
Parameters
----------
psi: float
psi : tensor_like of float
Expected proportion of NegativeBinomial variates (0 < psi < 1)
mu: float
mu : tensor_like of float
Poission distribution parameter (mu > 0).
alpha: float
alpha : tensor_like of float
Gamma distribution parameter (alpha > 0).
p: float
p : tensor_like of float
Alternative probability of success in each trial (0 < p < 1).
n: float
n : tensor_like of float
Alternative number of target success trials (n > 0)
"""

Expand Down Expand Up @@ -1846,18 +1846,19 @@ class OrderedProbit:
Parameters
----------
eta: float
eta : tensor_like of float
The predictor.
cutpoints: array
cutpoints : tensor_like array of floats
The length K - 1 array of cutpoints which break :math:`\eta` into
ranges. Do not explicitly set the first and last elements of
:math:`c` to negative and positive infinity.
sigma: float, default 1.0
sigma : tensor_like of float, default 1.0
Standard deviation of the probit function.
compute_p: boolean, default True
compute_p : boolean, default True
Whether to compute and store in the trace the inferred probabilities of each categories,
based on the cutpoints' values. Defaults to True.
Might be useful to disable it if memory usage is of interest.
Example
--------
.. code:: python
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