If: \begin{align} Y&=h(z,\theta)+\epsilon\\ \theta&\sim \text{Unknown Distribution}\\ \epsilon &\sim N(0,\sigma^2) \end{align} My book states: $ f_{y|(\theta,\sigma)}=f_{\epsilon|\theta,\sigma}(y-h(z,\theta)|\theta,\sigma ) $ I don't follow why.
(This is in context of something like Bayesian Regression).