Refine GRW docstrings and fix typos in release notes

RELEASE-NOTES.md

@@ -2,26 +2,38 @@
 
 ## PyMC3 3.9.x (on deck)
 
+### Maintenance
+- Mentioned the way to do any random walk with `theano.tensor.cumsum()` in `GaussianRandomWalk` docstrings (see [#4048](https://github.com/pymc-devs/pymc3/pull/4048)).
+
+### Documentation
+
+### New features
+
+## PyMC3 3.9.3 (11 August 2020)
+
 ### Maintenance
 - Fix an error on Windows and Mac where error message from unpickling models did not show up in the notebook, or where sampling froze when a worker process crashed (see [#3991](https://github.com/pymc-devs/pymc3/pull/3991)).
+- Require Theano >= 1.0.5 (see [#4032](https://github.com/pymc-devs/pymc3/pull/4032)).
 
 ### Documentation
-- Notebook on [multilevel modeling](https://docs.pymc.io/notebooks/multilevel_modeling.html) has been rewritten to showcase ArviZ and xarray usage for inference result analysis (see [#3963](https://github.com/pymc-devs/pymc3/pull/3963))
+- Notebook on [multilevel modeling](https://docs.pymc.io/notebooks/multilevel_modeling.html) has been rewritten to showcase ArviZ and xarray usage for inference result analysis (see [#3963](https://github.com/pymc-devs/pymc3/pull/3963)).
 
 ### New features
-- Introduce optional arguments to `pm.sample`: `mp_ctx` to control how the processes for parallel sampling are started, and `pickle_backend` to specify which library is used to pickle models in parallel sampling when the multiprocessing cnotext is not of type `fork`. (see [#3991](https://github.com/pymc-devs/pymc3/pull/3991))
+- Introduce optional arguments to `pm.sample`: `mp_ctx` to control how the processes for parallel sampling are started, and `pickle_backend` to specify which library is used to pickle models in parallel sampling when the multiprocessing context is not of type `fork` (see [#3991](https://github.com/pymc-devs/pymc3/pull/3991)).
 - Add sampler stats `process_time_diff`, `perf_counter_diff` and `perf_counter_start`, that record wall and CPU times for each NUTS and HMC sample (see [ #3986](https://github.com/pymc-devs/pymc3/pull/3986)).
-- Extend `keep_size` argument handling for `sample_posterior_predictive` and `fast_sample_posterior_predictive`, to work on arviz InferenceData and xarray Dataset input values. (see [PR #4006](https://github.com/pymc-devs/pymc3/pull/4006) and [Issue #4004](https://github.com/pymc-devs/pymc3/issues/4004).
-- SMC-ABC: add the wasserstein and energy distance functions. Refactor API, the distance, sum_stats and epsilon arguments are now passed `pm.Simulator` instead of `pm.sample_smc`. Add random method to `pm.Simulator`. Add option to save the simulated data. Improves LaTeX representation [#3996](https://github.com/pymc-devs/pymc3/pull/3996)
-- SMC-ABC: Allow use of potentials by adding them to the prior term. [#4016](https://github.com/pymc-devs/pymc3/pull/4016)
+- Extend `keep_size` argument handling for `sample_posterior_predictive` and `fast_sample_posterior_predictive`, to work on ArviZ `InferenceData` and xarray `Dataset` input values (see [PR #4006](https://github.com/pymc-devs/pymc3/pull/4006) and issue [#4004](https://github.com/pymc-devs/pymc3/issues/4004)).
+- SMC-ABC: add the Wasserstein and energy distance functions. Refactor API, the distance, sum_stats and epsilon arguments are now passed `pm.Simulator` instead of `pm.sample_smc`. Add random method to `pm.Simulator`. Add option to save the simulated data. Improved LaTeX representation [#3996](https://github.com/pymc-devs/pymc3/pull/3996).
+- SMC-ABC: Allow use of potentials by adding them to the prior term. [#4016](https://github.com/pymc-devs/pymc3/pull/4016).
+
+_NB: The `docs/*` folder is still removed from the tarball due to an upload size limit on PyPi._
 
 ## PyMC3 3.9.2 (24 June 2020)
 ### Maintenance
 - Warning added in GP module when `input_dim` is lower than the number of columns in `X` to compute the covariance function (see [#3974](https://github.com/pymc-devs/pymc3/pull/3974)).
 - Pass the `tune` argument from `sample` when using `advi+adapt_diag_grad` (see issue [#3965](https://github.com/pymc-devs/pymc3/issues/3965), fixed by [#3979](https://github.com/pymc-devs/pymc3/pull/3979)).
 - Add simple test case for new coords and dims feature in `pm.Model` (see [#3977](https://github.com/pymc-devs/pymc3/pull/3977)).
 - Require ArviZ >= 0.9.0 (see [#3977](https://github.com/pymc-devs/pymc3/pull/3977)).
-- Fixed issue [#3962](https://github.com/pymc-devs/pymc3/issues/3962) by making change in the `_random()` method of `GaussianRandomWalk` class, refer to PR [#3985]. Further testing revealed a new issue which is being tracked [#4010](https://github.com/pymc-devs/pymc3/issues/4010) 
+- Fixed issue [#3962](https://github.com/pymc-devs/pymc3/issues/3962) by making a change in the `_random()` method of `GaussianRandomWalk` class (see PR [#3985](https://github.com/pymc-devs/pymc3/pull/3985)). Further testing revealed a new issue which is being tracked by [#4010](https://github.com/pymc-devs/pymc3/issues/4010).
 
 _NB: The `docs/*` folder is still removed from the tarball due to an upload size limit on PyPi._
 

pymc3/distributions/timeseries.py

@@ -208,6 +208,10 @@ def logp(self, value):
 class GaussianRandomWalk(distribution.Continuous):
     r"""Random Walk with Normal innovations
 
+    Note that this is mainly a user-friendly wrapper to enable an easier specification
+    of GRW. You are not restricted to use only Normal innovations but can use any
+    distribution: just use `theano.tensor.cumsum()` to create the random walk behavior.
+
     Parameters
     ----------
     mu: tensor