SMC stabilize covariance matrix (#3573)

* stabilize covariance

* add release note

* fix test

RELEASE-NOTES.md

@@ -13,6 +13,7 @@
 ### Maintenance
 - Moved math operations out of `Rice`, `TruncatedNormal`, `Triangular` and `ZeroInflatedNegativeBinomial` `random` methods. Math operations on values returned by `draw_values` might not broadcast well, and all the `size` aware broadcasting is left to `generate_samples`. Fixes [#3481](https://github.com/pymc-devs/pymc3/issues/3481) and [#3508](https://github.com/pymc-devs/pymc3/issues/3508)
 - Parallelization of population steppers (`DEMetropolis`) is now set via the `cores` argument. ([#3559](https://github.com/pymc-devs/pymc3/pull/3559))
+- SMC: stabilize covariance matrix [3573](https://github.com/pymc-devs/pymc3/pull/3573)
 
 ## PyMC3 3.7 (May 29 2019)
 

pymc3/step_methods/smc_utils.py

@@ -44,9 +44,11 @@ def _calc_covariance(posterior, weights):
     Calculate trace covariance matrix based on importance weights.
     """
     cov = np.cov(posterior, aweights=weights.ravel(), bias=False, rowvar=0)
+    cov = np.atleast_2d(cov)
+    cov += 1e-6 * np.eye(cov.shape[0])
     if np.isnan(cov).any() or np.isinf(cov).any():
         raise ValueError('Sample covariances not valid! Likely "draws" is too small!')
-    return np.atleast_2d(cov)
+    return cov
 
 
 def _tune(acc_rate, proposed, step):