Repository: arviz-devs/arviz

Issue:
Add docs references to arviz.ess docstring
Add links to the related functions and classes to all the places where they are mentioned in the [arviz.ess](https://arviz-devs.github.io/arviz/api/generated/arviz.ess.html) docstring.

## Sample PR:
You can see https://github.com/arviz-devs/arviz/pull/1816 for the function, `plot_autocorr`. 
> ⚠️ Always create a new branch for changes. Don't make any changes to the `main` branch. 

## Source File
Source file: https://github.com/arviz-devs/arviz/blob/main/arviz/stats/diagnostics.py#L65

## How to add links
Add the links in the docstring of doc. You can also check the docstring by going to the `[source]`. 

* Add links to the ArviZ functions and classes using [Cross-referencing with Sphinx](https://docs.readthedocs.io/en/stable/guides/cross-referencing-with-sphinx.html).
* Add links to the xarray functions and classes using [Intersphinx](https://docs.readthedocs.io/en/stable/guides/intersphinx.html).
* Add the rest of the external links using this [syntax](https://sublime-and-sphinx-guide.readthedocs.io/en/latest/references.html#links-to-external-web-pages).

## See also section
Add the following functions in the "See also" section:
1. [arviz.rhat](https://arviz-devs.github.io/arviz/api/generated/arviz.rhat.html)
2. [arviz.mcse](https://arviz-devs.github.io/arviz/api/generated/arviz.mcse.html)
3. [plot_ess](https://arviz-devs.github.io/arviz/api/generated/arviz.plot_ess.html)
4. [arviz.summary](https://arviz-devs.github.io/arviz/api/generated/arviz.summary.html)

See [Adding "see also" section](https://github.com/arviz-devs/arviz/wiki/ArviZ-Hacktoberfest-2021#adding-see-also-section) for more details. 

## Checking the preview of docs
For checking the preview of docs, you don't need t set up the project on your local machine. Just follow the [checking the preview guide](https://github.com/arviz-devs/arviz/wiki/ArviZ-Hacktoberfest-2021#how-to-check-the-preview-of-docs). 




Discussion:
I want to complete this, please assign it to me.
Here you go, Thank you. 

Resolving patch:
diff --git a/arviz/stats/diagnostics.py b/arviz/stats/diagnostics.py
--- a/arviz/stats/diagnostics.py
+++ b/arviz/stats/diagnostics.py
@@ -76,10 +76,10 @@ def ess(
     Parameters
     ----------
     data : obj
-        Any object that can be converted to an ``az.InferenceData`` object.
-        Refer to documentation of ``az.convert_to_dataset`` for details.
+        Any object that can be converted to an :class:`arviz.InferenceData` object.
+        Refer to documentation of :func:`arviz.convert_to_dataset` for details.
         For ndarray: shape = (chain, draw).
-        For n-dimensional ndarray transform first to dataset with ``az.convert_to_dataset``.
+        For n-dimensional ndarray transform first to dataset with :func:`arviz.convert_to_dataset`.
     var_names : str or list of str
         Names of variables to include in the return value Dataset.
     method : str, optional, default "bulk"
@@ -98,7 +98,7 @@ def ess(
         - "local"
     relative : bool
         Return relative ess
-        `ress = ess / n`
+        ``ress = ess / n``
     prob : float, or tuple of two floats, optional
         probability value for "tail", "quantile" or "local" ess functions.
     dask_kwargs : dict, optional
@@ -132,6 +132,13 @@ def ess(
       Section 15.4.2
     * Gelman et al. BDA (2014) Formula 11.8
 
+    See Also
+    --------
+    arviz.rhat : Compute estimate of rank normalized splitR-hat for a set of traces.
+    arviz.mcse : Calculate Markov Chain Standard Error statistic.
+    plot_ess : Plot quantile, local or evolution of effective sample sizes (ESS).
+    arviz.summary : Create a data frame with summary statistics.
+
     Examples
     --------
     Calculate the effective_sample_size using the default arguments:


Test patch: