Update and tidy release notes

RELEASE-NOTES.md

@@ -11,29 +11,17 @@
   Gaussian Process implementation for efficient inference, along with
   lower-level functions such as `cartesian` and `kronecker` products.
 - Added `Coregion` covariance function.
-- Add new 'pairplot' function, for plotting scatter or hexbin matrices of sampled parameters.
-  Optionally it can plot divergences.
+- Add new 'pairplot' function, for plotting scatter or hexbin matrices of sampled parameters. Optionally it can plot divergences.
 - Plots of discrete distributions in the docstrings
 - Add logitnormal distribution
+- New function `pm.sample_prior` which generates test data from a model in the absence of data.
 
 ### Fixes
 
 - `VonMises` does not overflow for large values of kappa. i0 and i1 have been removed and we now use log_i0 to compute the logp.
 - The bandwidth for KDE plots is computed using a modified version of Scott's rule. The new version uses entropy instead of standard
 deviation. This works better for multimodal distributions. Functions using KDE plots has a new argument `bw` controlling the bandwidth.
 
-=======
-- Add `logit_p` keyword to `pm.Bernoulli`, so that users can specify the logit
-  of the success probability. This is faster and more stable than using
-  `p=tt.nnet.sigmoid(logit_p)`.
-- Add `random` keyword to `pm.DensityDist` thus enabling users to pass custom random method
-  which in turn makes sampling from a `DensityDist` possible. 
-
-### Fixes
-
-- `VonMises` does not overflow for large values of kappa. i0 and i1 have been removed and we now use
-   log_i0 to compute the logp.
-
 ### Deprecations
 
 - DIC and BPIC calculations have been removed