Function to estimate the evidence (marginal likelihood) with Chib and Jeliazkov's method or Power posteriors, based on the adjusted pseudolikelihood function.
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.
Examples
## Not run:# 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
## End(Not run)
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