Dear R experts,
I know this is not the appropriate place to post but I already tried eco
(has not used ME) and geo (not available unit Aug 5), so please forgive me.
I fitted my spatial data to a glm.nb model. I decided to detect and correct
for spatial autocorrelation using ME{spdep}. I received this warning after
I added the eigenvectors into the model. Can you help me understand what I
did wrong? Also, should I infer from the example below that spatial
autocorrelation is negligible since the pr(ZI) values are so high?
> tu1<-glm.nb(total.aeg~Total.number.of.units, data=inhdb, offset(x))
> tuME<-ME(total.aeg~Total.number.of.units, data=inhdb, family="poisson",
offset(x), listw=sw.nb, alpha=0.5)
> tuME
Eigenvector ZI pr(ZI)
0 NA NA 0.40
1 43 NA 0.39
2 19 NA 0.39
3 18 NA 0.36
4 34 NA 0.35
5 23 NA 0.41
6 25 NA 0.39
7 56 NA 0.36
8 51 NA 0.47
9 46 NA 0.41
10 36 NA 0.32
etc.....
> inhdb$eigen_43<-fitted(tuME)[,1]
> inhdb$eigen_19<-fitted(tuME)[,2]
> tuglmME<-glm.nb(total.aeg~Total.number.of.units+fitted(tuME), data=inhdb,
offset(x))
There were 27 warnings (use warnings() to see them)
Warning messages:
1: In theta.ml(Y, mu, sum(w), w, limit = control$maxit, trace =
control$trace > ... :
iteration limit reached
Thank you for your help!
Best,
Amy
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