Thanks Christian, Now I get a more informative trace: glm(n~.,data=mDat,family=poisson,control = glm.control(trace = TRUE)) Deviance = 23.48435924 Iterations - 1 Deviance = 22.23499386 Iterations - 2 Deviance = 22.21320309 Iterations - 3 Deviance = 22.20690862 Iterations - 4 Deviance = 22.20459309 Iterations - 5 Deviance = 22.20374125 Iterations - 6 Deviance = 22.20342787 Iterations - 7 Deviance = 22.20331259 Iterations - 8 Deviance = 22.20327018 Iterations - 9 Deviance = 22.20325458 Iterations - 10 Deviance = 22.20324884 Iterations - 11 Deviance = 22.20324673 Iterations - 12 Deviance = 22.20324595 Iterations - 13 Deviance = 22.20324566 Iterations - 14 Deviance = 22.4735046 Iterations - 15 Deviance = Inf Iterations - 16 Step halved: new deviance = 4.154792321e+266 Error: NA/NaN/Inf in foreign function call (arg 1) In addition: Warning message: step size truncated due to divergence
Actually, the expected counts can be fitted by a quotient between marginal counts, and my alternative calculation of the deviance yields 22.20324550. I guess, that I just have to accept that glm() is not garanteed to converge. best, svante Christian Ritz wrote: > Hi, > > try using the function 'glm.control' in the first place: > > > glm(n~., data = mDat, family = poisson, > control = glm.control(trace = TRUE)) > > > > Christian > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
