Text

Author: penelopeysm

usage/predictive-distributions/index.qmd

@@ -111,6 +111,8 @@ predicted_X = vcat([predictive_samples[Symbol("X[$i]")] for i in 1:N]...)
 density(predicted_X, label="Posterior predictive")
 ```
 
+Depending on your data, you may naturally want to create different visualisations: for example, perhaps `X` is some time-series data, and you can plot each prediction individually as a line against time.
+
 ## Prior predictive distribution
 
 Alternatively, if we use the prior distribution of the parameters, we obtain the *prior predictive distribution*: