From 7552bb137013986ed544102952b018c3458cd082 Mon Sep 17 00:00:00 2001
From: hyosubkim <32351455+hyosubkim@users.noreply.github.com>
Date: Wed, 9 Nov 2022 16:44:05 -0500
Subject: [PATCH 1/2] Updated pymc.DiscreteWeibull docstring

---
 pymc/distributions/discrete.py | 20 +++++++++++++++-----
 1 file changed, 15 insertions(+), 5 deletions(-)

diff --git a/pymc/distributions/discrete.py b/pymc/distributions/discrete.py
index ce88d8bd723..feaaf529293 100644
--- a/pymc/distributions/discrete.py
+++ b/pymc/distributions/discrete.py
@@ -462,15 +462,16 @@ def rng_fn(cls, rng, q, beta, size):
 
 
 class DiscreteWeibull(Discrete):
-    R"""Discrete Weibull log-likelihood
+    """Discrete Weibull log-likelihood.
 
     The discrete Weibull distribution is a flexible model of count data that
     can handle both over- and under-dispersion.
     The pmf of this distribution is
 
-    .. math:: f(x \mid q, \beta) = q^{x^{\beta}} - q^{(x + 1)^{\beta}}
+    .. math:: f(x \\mid q, \beta) = q^{x^{\beta}} - q^{(x + 1)^{\beta}}
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np
@@ -495,11 +496,20 @@ def DiscreteWeibull(q, b, x):
         plt.show()
 
     ========  ======================
-    Support   :math:`x \in \mathbb{N}_0`
-    Mean      :math:`\mu = \sum_{x = 1}^{\infty} q^{x^{\beta}}`
-    Variance  :math:`2 \sum_{x = 1}^{\infty} x q^{x^{\beta}} - \mu - \mu^2`
+    Support   :math:`x \\in \\mathbb{N}_0`
+    Mean      :math:`\\mu = \\sum_{x = 1}^{\\infty} q^{x^{\beta}}`
+    Variance  :math:`2 \\sum_{x = 1}^{\\infty} x q^{x^{\beta}} - \\mu - \\mu^2`
     ========  ======================
+
+    Parameters
+    ----------
+    q : tensor_like of float
+        Shape parameter (0 < q < 1).
+    beta : tensor_like of float
+        Shape parameter (beta > 0).
+
     """
+
     rv_op = discrete_weibull
 
     @classmethod

From 5967d1508db87367511af8d0a43eb1dd2352b2ad Mon Sep 17 00:00:00 2001
From: hyosubkim <32351455+hyosubkim@users.noreply.github.com>
Date: Wed, 9 Nov 2022 21:00:38 -0500
Subject: [PATCH 2/2] address review comments

---
 pymc/distributions/discrete.py | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/pymc/distributions/discrete.py b/pymc/distributions/discrete.py
index feaaf529293..509ab7f7593 100644
--- a/pymc/distributions/discrete.py
+++ b/pymc/distributions/discrete.py
@@ -462,13 +462,13 @@ def rng_fn(cls, rng, q, beta, size):
 
 
 class DiscreteWeibull(Discrete):
-    """Discrete Weibull log-likelihood.
+    R"""Discrete Weibull log-likelihood.
 
     The discrete Weibull distribution is a flexible model of count data that
     can handle both over- and under-dispersion.
     The pmf of this distribution is
 
-    .. math:: f(x \\mid q, \beta) = q^{x^{\beta}} - q^{(x + 1)^{\beta}}
+    .. math:: f(x \mid q, \beta) = q^{x^{\beta}} - q^{(x + 1)^{\beta}}
 
     .. plot::
         :context: close-figs
@@ -496,9 +496,9 @@ def DiscreteWeibull(q, b, x):
         plt.show()
 
     ========  ======================
-    Support   :math:`x \\in \\mathbb{N}_0`
-    Mean      :math:`\\mu = \\sum_{x = 1}^{\\infty} q^{x^{\beta}}`
-    Variance  :math:`2 \\sum_{x = 1}^{\\infty} x q^{x^{\beta}} - \\mu - \\mu^2`
+    Support   :math:`x \in \mathbb{N}_0`
+    Mean      :math:`\mu = \sum_{x = 1}^{\infty} q^{x^{\beta}}`
+    Variance  :math:`2 \sum_{x = 1}^{\infty} x q^{x^{\beta}} - \mu - \mu^2`
     ========  ======================
 
     Parameters
@@ -509,7 +509,6 @@ def DiscreteWeibull(q, b, x):
         Shape parameter (beta > 0).
 
     """
-
     rv_op = discrete_weibull
 
     @classmethod