id_plot_ppc: Plot Posterior Predictive Distribution for 'idealstan'...

In saudiwin/idealstan: Robust Measurement with 'Stan'

Plot Posterior Predictive Distribution for idealstan Objects

Description

This function is the generic method for generating posterior distributions from a fitted idealstan model. Functions are documented in the actual method.

Usage

id_plot_ppc(object, ...)

Arguments

object	A fitted idealstan object
...	Other arguments passed on to bayesplot::ppc_bars()

Details

This function is a wrapper around bayesplot::ppc_bars(), bayesplot::ppc_dens_overlay() and bayesplot::ppc_violin_grouped() that plots the posterior predictive distribution derived from id_post_pred() against the original data. You can also subset the posterior predictions over legislators/persons or bills/item sby specifying the ID of each in the original data as a character vector. Only persons or items can be specified, not both.

If you specify a value for group that is either a person ID or a group ID (depending on whether a person or group-level model was fit), then you can see the posterior distributions for those specific persons. Similarly, if an item ID is passed to item, you can see how well the model predictions compare to the true values for that specific item.

saudiwin/idealstan documentation built on April 11, 2025, 4:37 p.m.