Mention in release notes

Author: AlexAndorra

RELEASE-NOTES.md

@@ -18,7 +18,8 @@
   - The `size` kwarg behaves like it does in Aesara/NumPy. For univariate RVs it is the same as `shape`, but for multivariate RVs it depends on how the RV implements broadcasting to dimensionality greater than `RVOp.ndim_supp`.
   - An `Ellipsis` (`...`) in the last position of `shape` or `dims` can be used as short-hand notation for implied dimensions.
 - Add `logcdf` method to Kumaraswamy distribution (see [#4706](https://github.com/pymc-devs/pymc3/pull/4706)).
-- ...
+- The `OrderedMultinomial` distribution has been added for use on ordinal data which are _aggregated_ by trial, like multinomial observations, whereas `OrderedLogistic` only accepts ordinal data in a _disaggregated_ format, like categorical
+  observations (see [#4773](https://github.com/pymc-devs/pymc3/pull/4773)).
 
 ### Maintenance
 - Remove float128 dtype support (see [#4514](https://github.com/pymc-devs/pymc3/pull/4514)).

pymc3/distributions/multivariate.py

@@ -718,7 +718,7 @@ class OrderedMultinomial:
     R"""
     Wrapper class for Ordered Multinomial distributions.
 
-    Useful for regression on ordinal data values whose values range
+    Useful for regression on ordinal data whose values range
     from 1 to K as a function of some predictor, :math:`\eta`, but
      which are _aggregated_ by trial, like multinomial observations (in
      contrast to `pm.OrderedLogistic`, which only accepts ordinal data