Currently bayesplot offers are three functions for discrete PPCs: ppc_bars, ppc_bars_grouped, and ppc_rootogram.

In our preprint, we argue why bar graphs are usually not a good PPC, especially for binary observations.

Calibration plots

I suggest adding the binned calibration plot and PAV-adjusted calibration plot under a function called ppc_calibration. For ordinal or categorical data, it would possibly be clearer to have another function that produces calibration plots for 1-vs-others, or cumulative event probability.

Residual plots

Another missing function are residual plots, ppc_error_scatter_vs_x, and ppc_error_binned work on this field, but the scatter doesn't work for discrete observations, and ppc_error_binned doesn't currently support covariates on the x-axis.

• The confidence bands in these need work, but at the very least adding options for binned residual plots and PAV-adjusted residuals would be an improvement.