 Solution

The probabilistic graphical model is the following Directed acyclic graph. The shared hyperparameters lie outside the plate; the plate repeats the local variables for $s=1,\dots ,N$. The observed colour is shaded, and the known error variance $r_s$ is a square.

Thus the parent sets are $\boxed{\mathrm{pa}(C_s)=\{{\mu }_C,v\},\mathrm{pa}(E_s)=\{\tau \},\mathrm{pa}(o_s)=\{C_s,E_s,r_s\}}$. Independent hyperparameter prior factors are represented by the three root nodes. With the printed improper priors this is a factorization diagram; it becomes a normalized generative model after proper priors are supplied.