stCEG (version 0.1.0)

compare_ceg_models: Compare Two Chain Event Graph Models Using Bayes Factors

Description

This function compares two fitted Chain Event Graph (CEG) models by evaluating their total log marginal likelihoods and computing the Bayes factor. The comparison identifies the preferred model and reports the strength of evidence using Jeffreys' scale.

Usage

compare_ceg_models(summary1, summary2)

Value

An invisible list of class ceg_model_comparison containing:

log_marginal_1

Log marginal likelihood of model 1.

log_marginal_2

Log marginal likelihood of model 2.

log_Bayes_factor

The log Bayes factor comparing model 1 to model 2.

Bayes_factor

The Bayes factor (on the original scale).

preferred_model

The model preferred based on the Bayes factor.

Arguments

summary1

An object of class summary.chain_event_graph, typically the output of summary() applied to a fitted CEG model.

summary2

Another object of class summary.chain_event_graph to compare with summary1.

Details

The Bayes factor is calculated as the ratio of marginal likelihoods of the two models: \(BF = \exp(\log BF)\). Interpretation of the Bayes factor is guided by Jeffreys' scale:

• < 1: Evidence against the alternative model

• 1–3: Weak evidence

• 3–10: Moderate evidence

• 10–30: Strong evidence

• 30–100: Very strong evidence

• > 100: Decisive evidence

The function prints the log marginal likelihoods, log Bayes factor, Bayes factor, and preferred model.

Examples

data <- homicides
event_tree <- create_event_tree(data, columns = c(1,2,4,5), "both")
coloured_tree <- ahc_colouring(event_tree)

tree_priors <- specify_priors(coloured_tree, prior_type = "Uniform", ask_edit = FALSE)
staged_tree <- staged_tree_prior(coloured_tree, tree_priors)
ceg <- create_ceg(staged_tree, view_table = TRUE)


# Define node groups and colours
node_groups <- list(c("s1", "s2"), c("s3", "s4"))
colours <- c("#BBA0CA", "#8AC6D0")

# Apply colours to the event tree
custom_tree <- update_node_colours(event_tree, node_groups, colours)
custom_coloured_tree <- ahc_colouring(custom_tree)

# Cannot run this whole chunk at once as specify_priors needs user input
custom_tree_priors <- specify_priors(custom_coloured_tree, prior_type = "Uniform", ask_edit = FALSE)
custom_staged_tree <- staged_tree_prior(custom_coloured_tree, custom_tree_priors)
ceg2 <- create_ceg(custom_staged_tree, view_table = TRUE)
model1_summary <- summary(ceg)
model2_summary <- summary(ceg2)
compare_ceg_models(model1_summary, model2_summary)