simulate.mmsbm: Simulate a complete sociomatrix from an 'mmsbm' object

In NetMix: Dynamic Mixed-Membership Network Regression Model

Simulate a complete sociomatrix from an mmsbm object

Description

The function generates one sample network from the posterior predictive of the model represented by a fitted mmsbm object.

Usage

## S3 method for class 'mmsbm'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  new.data.dyad = NULL,
  new.data.monad = NULL,
  ...
)

Arguments

object	An object of class mmsbm, a result of a call to mmsbm
nsim	Number of networks to simulate
seed	RNG seed.
new.data.dyad	An optional data.frame object. If not NULL, use these dyadic predictor values instead of those used to fit the original model.
new.data.monad	An optional data.frame object. See new.data.dyad.
...	Currently ignored

Value

List of length nsim of simulated networks. If new.data.dyad = NULL, each element is a vector of length nrow(object$dyadic.data). Else, vector of length nrow(new.data.dyad). If seed is not NULL, return object includes its value as attribute "seed".

Author(s)

Santiago Olivella ([e-mail]), Adeline Lo ([e-mail]), Tyler Pratt ([e-mail]), Kosuke Imai ([e-mail])

Examples

library(NetMix)
## Load datasets
data("lazega_dyadic")
data("lazega_monadic")
## Estimate model with 2 groups
lazega_mmsbm <- mmsbm(SocializeWith ~ Coworkers,
                      ~  School + Practice + Status,
                      senderID = "Lawyer1",
                      receiverID = "Lawyer2",
                      nodeID = "Lawyer",
                      data.dyad = lazega_dyadic,
                      data.monad = lazega_monadic,
                      n.blocks = 2,
                      mmsbm.control = list(seed = 123, 
                                           conv_tol = 1e-2,
                                           hessian = FALSE))

## Simulate 5 new networks
lazega_sim <- simulate(lazega_mmsbm, nsim = 5, seed = 123)

NetMix documentation built on Nov. 16, 2022, 5:15 p.m.