Heather Kharouba <kharouba at ...> writes:
I am new to glmmADMB and would like to use the beta distribution with
glmmadmb. However, I keep running into the same error. The response
variable is AUC (area under the curve data) from species distribution
models which is continuous and ranges from 0 to 1. The fixed variables
are
the number of variables used to build the model (continuous), spatial
extent of the distribution model (continuous), model type (factor) and
taxonomic group (categorical) and the random effect is study.
Here's the model:
model1<-glmmadmb(AUC~variables+log_area+model+taxa+(1|study),
family="beta", verbose=TRUE, data=auc);
A snapshot of the data:
study taxa AUC model variables log_area
Araujo et al. 2005 BIRD 0.9156878 GAM 7 16.21771
Araujo et al. 2005 BIRD 0.9288596 GAM 7 16.21771
Araujo et al. 2005 BIRD 0.9254065 GAM 7 16.21771
Araujo et al. 2005 BIRD 0.8825593 GAM 7 16.21771
Araujo et al. 2005 BIRD 0.9388894 GAM 7 16.21771
Araujo et al. 2005 BIRD 0.9061483 GAM 7 16.21771
When I run the model I get this error:
Error in glmmadmb(AUC ~ variables + log_area + model + taxa + (1 |
study),
:
The function maximizer failed (couldn't find STD file)
I'm using glmm ADMB version 0.7.2.2 with R version 2.14.2 on a Mac OS X
Version 10.6.8. I've tried including
admb.opts=admbControl(shess=FALSE,noinit=FALSE) and still get the same
error. I'm guessing there's something wrong with either the response
variable or with the overall data structure?
My first guess would be that you have AUC values that are
exactly equal to 0 or 1; they will give infinite/NaN log-likelihoods
in the beta model. Beyond that, I'm not sure. It would be useful
to know a little bit more about your data -- how many total observations?
How many studies?
Does fitting the model without the random effect work, i.e.
model2 <- glmmadmb(AUC~variables+log_area+model+taxa,
family="beta", verbose=TRUE, data=auc)
?