bayes_factor: Compare models with a Bayes factor

In RprobitB: Bayesian Probit Choice Modeling

Compare models with a Bayes factor

Description

Estimates both marginal likelihoods with bridge sampling and compares the first model with the second model using bridgesampling::bridge_sampler() and bridgesampling::bf().

Usage

bayes_factor(
  model1,
  model2,
  log = FALSE,
  repetitions = 1L,
  ghk_draws = 500L,
  progress = interactive()
)

Arguments

model1, model2	[RprobitB_fit] Fitted models to compare.
log	[logical(1)] Return the logarithm of the Bayes factor?
repetitions	[integer(1)] Number of independent bridge-sampling repetitions.
ghk_draws	[integer(1)] Number of draws of the GHK simulator for multivariate normal probabilities of more than three dimensions, see oeli::pmvnorm().
progress	[logical(1)] Show progress?

Value

A bf_bridge object from bridgesampling. Values greater than one favor model1; values below one favor model2.

References

\insertRef

Gronau2020RprobitB

Examples

### Simulate and fit the correctly specified model
set.seed(1)
correct_model <- fit(
  choice ~ x + z | 0,
  dgp_parameters = list(beta = c(x = 1, z = 0.5)),
  iterations = 500,
  chains = 1
)
simulated_data <- as.data.frame(correct_model$data)

### Fit the same data again, but omit the relevant regressor z
misspecified_model <- fit(
  choice ~ x | 0,
  data = simulated_data,
  iterations = 500,
  chains = 1
)

### A Bayes factor greater than one favors the correct first model
bayes_factor(correct_model, misspecified_model)

RprobitB documentation built on Sept. 20, 2026, 9:07 a.m.