Bergm (version 5.0.7)

evidence: Wrapper function for evidence estimation

Description

Function to estimate the evidence (marginal likelihood) with Chib and Jeliazkov's method or Power posteriors, based on the adjusted pseudolikelihood function.

Usage

evidence(evidence.method = c("CJ", "PP"), ...)

Arguments

evidence.method

vector Method to estimate the marginal likelihood. Options are: "CJ", in which case the marginal likelihood is estimated with Chib and Jeliazkov's method; "PP", in which case the marginal likelihood is estimated with Power posteriors.

...

further arguments to be passed. See evidenceCJ and evidencePP.

References

Bouranis, L., Friel, N., & Maire, F. (2018). Bayesian model selection for exponential random graph models via adjusted pseudolikelihoods. Journal of Computational and Graphical Statistics, 27(3), 516-528. https://arxiv.org/abs/1706.06344

Examples

if (FALSE) {
# Load the florentine marriage network:
data(florentine)
                                                
# MCMC sampling and evidence estimation:
CJE <- evidence(evidence.method = "CJ",
                formula     = flomarriage ~ edges + kstar(2),
                main.iters  = 30000,
                burn.in     = 2000,
                aux.iters   = 1000,
                num.samples = 25000,
                V.proposal  = 2.5,
                ladder      = 100,
                seed        = 1)
                                   
# Posterior summaries:
summary(CJE)

# MCMC diagnostics plots:
plot(CJE)
    
# Log-evidence (marginal likelihood) estimate:
CJE$log.evidence
}