My code looked like
gw1_sup <- ergm(supnet ~ edges + nodefactor("work") + nodefactor("income") + nodefactor("edu") + nodefactor("religious") + nodefactor("gender") + nodecov("age") + edgecov(sup_loca2_net, "distance") + edgecov(kin_sup,"kinweight") + gwidegree(.1, T) + gwesp(.1, T) + gwdsp(.1, T), control = control.ergm(MCMC.samplesize = 1e+4, MCMC.burnin = 100, MCMC.interval = 1e+3, seed = 567, SAN=2), eval.loglik = T, verbose = T)
and it worked quite well without "edgecov(sup_loca2_net, "distance")", but once I put that in, they model went wrong and the error says:"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 parameter".
I wonder if there is a way to figure out which model should I use or what adjustment I should do to make this model work?
