Un-update Bayesian models to their prior-to-data state

As posteriors are priors that have been updated after observing some data, the goal of this function is to un-update the posteriors to obtain models representing the priors. These models can then be used to examine the prior predictive distribution, or to compare priors with posteriors.

Usage

unupdate(model, verbose = TRUE, ...)

# S3 method for class 'brmsfit'
unupdate(model, verbose = TRUE, ...)

# S3 method for class 'brmsfit_multiple'
unupdate(model, verbose = TRUE, newdata = NULL, ...)

Arguments

model

A fitted Bayesian model.

verbose

Toggle warnings.

...

Not used

newdata

List of data.frames to update the model with new data. Required even if the original data should be used.

Value

A model un-fitted to the data, representing the prior model.

Details

This function in used internally to compute Bayes factors.