Running examples in ‘ergm.ego-Ex.R’ failed
The error most likely occurred in:

> ### Name: simulate.ergm.ego
> ### Title: Simulate from a 'ergm.ego' fit.
> ### Aliases: simulate.ergm.ego
> ### Keywords: models
> 
> ### ** Examples
> 
> 
> data(faux.mesa.high)
> fmh.ego <- as.egodata(faux.mesa.high)
Network does not have vertex attribute ‘vertex.names’ to use as ego ID; using 1..N.
> egofit <- ergm.ego(fmh.ego~edges+degree(0:3)+nodefactor("Race")+nodematch("Race")
+                +nodefactor("Sex")+nodematch("Sex")+absdiff("Grade"), 
+                popsize=network.size(faux.mesa.high))
Constructing pseudopopulation network.
Unable to match target stats. Using MCMLE estimation.
Starting maximum pseudolikelihood estimation (MPLE):
Evaluating the predictor and response matrix.
Maximizing the pseudolikelihood.
Finished MPLE.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Iteration 1 of at most 60:
Optimizing with step length 0.4429.
The log-likelihood improved by 1.3903.
Estimating equations are not within tolerance region.
Iteration 2 of at most 60:
Optimizing with step length 0.8492.
The log-likelihood improved by 1.5975.
Estimating equations are not within tolerance region.
Iteration 3 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.3538.
Estimating equations are not within tolerance region.
Iteration 4 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.6814.
Estimating equations are not within tolerance region.
Iteration 5 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 1.1097.
Estimating equations are not within tolerance region.
Iteration 6 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 1.9572.
Estimating equations are not within tolerance region.
Estimating equations did not move closer to tolerance region more than 1 time(s) in 4 steps; increasing sample size.
Iteration 7 of at most 60:
Optimizing with step length 0.7979.
The log-likelihood improved by 2.1539.
Estimating equations are not within tolerance region.
Iteration 8 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.3762.
Estimating equations are not within tolerance region.
Iteration 9 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.2392.
Estimating equations are not within tolerance region.
Iteration 10 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.2599.
Estimating equations are not within tolerance region.
Iteration 11 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0697.
Convergence test p-value: 0.9925. Not converged with 99% confidence; increasing sample size.
Iteration 12 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0493.
Convergence test p-value: 0.3045. Not converged with 99% confidence; increasing sample size.
Iteration 13 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0258.
Convergence test p-value: 0.3920. Not converged with 99% confidence; increasing sample size.
Iteration 14 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0341.
Convergence test p-value: < 0.0001. Converged with 99% confidence.
Finished MCMLE.
This model was fit using MCMC.  To examine model diagnostics and check
for degeneracy, use the mcmc.diagnostics() function.
> colMeans(egosim <- simulate(egofit, popsize=300,nsim=50,
+                        output="stats", control=control.simulate.ergm.ego(
+                        simulate.control=control.simulate.formula(MCMC.burnin=2e6))))
Note: Constructed network has size 205 different from requested 300. Simulated statistics may need to be rescaled.
Error in simulate.formula_lhs(object = fmh.ego ~ offset(netsize.adj) +  : 
  No applicable method for LHS of type ‘ergm_state_full’, ‘ergm_state_send’, ‘ergm_state_receive’, ‘ergm_state’.
Calls: colMeans ... eval -> eval -> <Anonymous> -> simulate.formula_lhs
Execution halted