Update Bayesian_for_LGM_PMIP

Bayesian_for_LGM_PMIP

@@ -118,6 +118,8 @@ with Model() as model: # model specifications in PyMC3 are wrapped in a with-sta
     
     # Inference! 4 jobs in parallel (convergence check)
     # By default, the sampling method is NUTS
+    # The following line will not work with PyMC3 older than 3.8. If you use an
+    # older version, replace "cores=4" by "njobs=4"
     trace = sample(progressbar=False, draws=2000, cores=4)
 
 # Extract the data of the trace
@@ -222,7 +224,7 @@ posterior = np.random.choice(prior_S, size=8000, p=weight)
 post_median = np.median(posterior)
 post_std = np.std(posterior)
 
-# Compute 90% minimum width interval . Careful, different than 5-95%
+# Compute 90% minimum width interval. Careful, different than 5-95%
 #post_stats_95 = stats.hpd(posterior, alpha=0.1)
 #post_stats_33 = stats.hpd(posterior, alpha=0.33)