sampler.gibbs: Gibbs sampling for node assignments

In SBMSplitMerge: Inference for a Generalised SBM with a Split Merge Sampler

Description

Gibbs sampling for node assignments

Usage

sampler.gibbs(currsbm, edges, sbmmod, sigma)

Arguments

currsbm	the current state of the sampler
edges	an edges object
sbmmod	an sbmmod model
sigma	random walk parameter for theta

Value

next state of currsbm object

Note

This requires a block model with a fixed kappa

Examples

model <- sbmmod(multinom(1, 3), param_gamma(1,1,1,1), edges_pois())
trueSBM <- model$r(10)
Edges <- redges(trueSBM, model$edge)
gibbs_out <- sampler(Edges, model, algorithm="gibbs", 10, sigma=0.1)
eval_plots(gibbs_out)

SBMSplitMerge documentation built on July 1, 2020, 5:23 p.m.