Correct docs for Bernoulli, Poisson, Negative Binomial, Geometric and HyperGeometric (#5958)

* update docs for Bernoulli, Poisson, Negative Binomial, Geometric  and add missing plot context in HyperGeometric

* correct spacing

Co-authored-by: SangamSwadiK <[email protected]>

Author: SangamSwadiK

pymc/distributions/discrete.py

@@ -338,6 +338,7 @@ class Bernoulli(Discrete):
     .. math:: f(x \mid p) = p^{x} (1-p)^{1-x}
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np
@@ -367,9 +368,9 @@ class Bernoulli(Discrete):
 
     Parameters
     ----------
-    p: float
+    p : tensor_like of float
         Probability of success (0 < p < 1).
-    logit_p: float
+    logit_p : tensor_like of float
         Alternative log odds for the probability of success.
     """
     rv_op = bernoulli
@@ -569,6 +570,7 @@ class Poisson(Discrete):
     .. math:: f(x \mid \mu) = \frac{e^{-\mu}\mu^x}{x!}
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np
@@ -593,7 +595,7 @@ class Poisson(Discrete):
 
     Parameters
     ----------
-    mu: float
+    mu : tensor_like of float
         Expected number of occurrences during the given interval
         (mu >= 0).
 
@@ -686,6 +688,7 @@ class NegativeBinomial(Discrete):
            (\alpha/(\mu+\alpha))^\alpha (\mu/(\mu+\alpha))^x
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np
@@ -733,13 +736,13 @@ def NegBinom(a, m, x):
 
     Parameters
     ----------
-    alpha: float
+    alpha : tensor_like of float
         Gamma distribution shape parameter (alpha > 0).
-    mu: float
+    mu : tensor_like of float
         Gamma distribution mean (mu > 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)
     """
     rv_op = nbinom
@@ -854,6 +857,7 @@ class Geometric(Discrete):
     .. math:: f(x \mid p) = p(1-p)^{x-1}
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np
@@ -877,7 +881,7 @@ class Geometric(Discrete):
 
     Parameters
     ----------
-    p: float
+    p : tensor_like of float
         Probability of success on an individual trial (0 < p <= 1).
     """
 
@@ -963,6 +967,7 @@ class HyperGeometric(Discrete):
     .. math:: f(x \mid N, n, k) = \frac{\binom{k}{x}\binom{N-k}{n-x}}{\binom{N}{n}}
 
     .. plot::
+        :context: close-figs
 
         import matplotlib.pyplot as plt
         import numpy as np