this is a question for your help. i use the ergm to model the formation of network.but it is always degeneracy.there are just 174 nodes(vertices), 304 deges. i use the code as follow
my.ergm.3 <- formula(gg04.1 ~ edges+nodecov("width")+
nodecov("depth")+nodecov("numbers")+gwesp(0.2,fixed=T)+gwdegree(2,fixed=T))
gg03.ergm.fit <- ergm(my.ergm.3,control = control.ergm(MCMLE.maxit = 20,
parallel =2,
parallel.type = "PSOCK",
MCMC.interval = 10000,
MCMC.burnin =10000,
MCMC.samplesize = 10000,
MCMLE.density.guard =5000)
,verbose=3)
the question is from the parameter -----gwesp(0.2,fixed=T) and gwdegree(2,fixed=T)),the speed is very low.and the error as follows: Estimating equations are not within tolerance region. Error in ergm.MCMLE(init, nw, model, initialfit = (initialfit <- NULL), : MCMLE estimation stuck. There may be excessive correlation between model terms, suggesting a poor model for the observed data. If target.stats are specified, try increasing SAN parameters.
i want to know if the code haves mistakes or i should how to correct the mistake. thank you very much
The code in and of itself looks good and does not seem to have any mistakes as far as I can tell. It is hard however, to give a definitive answer on this, since your example is not reproducable. I think the issue is rather in the data
The GWESP is similar to a
trianglesparameter (the number of closed triangles in a model, with the distinction that the GWESP is less susceptible to model degeneracy. If one of your parameters in the estimation does a similar thing to the GWESP (e.g. a homophily term), then there can be a high correlation between the parameters. In the error term, it then says you have a "poor model specification" since two terms in the estimation are highly correlated, making one of them redundant.I would suggest revisiting the theoretical foundations to see if your model specification is reasonable.