`ppc_error_scatter_avg()` should be able to plot residuals as function of predicted y, not y

(Notation below: $y$ is data value, $y_{pred}$ is predicted value, with $y_{pred}$ computed as $stat(y_{rep})$ from posterior draws.)

The usual residual analysis plots $y - y_{pred}$ on the vertical axis with $y_{pred}$ on the horizontal axis.

But ppc_error_scatter_avg() plots $y - y_{pred}$ on the vertical axis with $y$ on the horizontal axis. This is confusing and difficult to interpret (for me, but I'm not alone: https://stats.stackexchange.com/a/146002).

I would be great if ppc_error_scatter_avg() plotted $y_{pred}$ on the horizontal axis, either by default or with that as an option. (Or maybe there's already an easy way to do that; sorry if I missed it.)

Thanks for considering!

P.S. My comment here assumes that $y_{pred}$ is computed as $stat(y_{rep})$ from posterior draws. But the related thread regarding residuals https://github.com/stan-dev/bayesplot/pull/349 seems to suggest that residuals are computed as $stat(y - y_{rep})$, with $stat(y_{rep})$ not separately, explicitly computed. Hmmm...?

Start at the ppc_error_scatter_avg() entry point and review the related residuals discussion in pull request #349. Determine whether the horizontal axis should use y_pred directly or whether the residual definition also needs clarification. Done means the plot supports the requested predicted-y presentation with documented, interpretable behavior.