extra updates

Author: OriolAbril

docs/source/conf.py

@@ -81,7 +81,8 @@
     "SMC_kernel": ":ref:`SMC Kernel <smc_kernels>`",
     "Aesara_Op": ":class:`Aesara Op <aesara.graph.op.Op>`",
     "tensor_like": ":term:`tensor_like`",
-    "numpy_Generator": ":class:`~numpy.random.Generator`"
+    "numpy_Generator": ":class:`~numpy.random.Generator`",
+    "Distribution": ":ref:`Distribution <api_distributions>`",
 }
 
 # Show the documentation of __init__ and the class docstring

pymc/distributions/timeseries.py

@@ -217,20 +217,21 @@ def rng_fn(
 
 
 class GaussianRandomWalk(distribution.Continuous):
-    r"""Random Walk with Normal innovations
+    r"""Random Walk with Normal innovations.
 
     Parameters
     ----------
-    mu : tensor_like of float
-        innovation drift, defaults to 0.0
-    sigma : tensor_like of float, optional
-        sigma > 0, innovation standard deviation, defaults to 1.0
-    init_dist : unnamed distribution
-        Univariate distribution of the initial value, created with the `.dist()` API.
+    mu : tensor_like of float, default 0
+        innovation drift
+    sigma : tensor_like of float, default 1
+        sigma > 0, innovation standard deviation.
+    init_dist : Distribution
+        Unnamed univariate distribution of the initial value. Unnamed refers to distributions
+         created with the ``.dist()`` API.
 
         .. warning:: init will be cloned, rendering them independent of the ones passed as input.
 
-    steps : int, optional
+    steps : tensor_like of int, optional
         Number of steps in Gaussian Random Walk (steps > 0). Only needed if shape is not
         provided.
     """