Ranked abundance distribution
Hello,
On 17/12/2013, at 17:01 PM, Sol Noetinger wrote:
Hello,
Cluster II
RAD models, family poisson
No. of species 35, total abundance 100
par1 par2 par3 Deviance AIC BIC
Null 25.7004 Inf Inf
Preemption 0.1 27.8760 Inf Inf
Lognormal 0.21756 1.3473 4.7797 Inf Inf
Zipf 0.27724 -1.0959 4.9038 Inf Inf
Mandelbrot 0.64175 -1.3825 1 4.9181 Inf Inf
I read from the manual that to see which models fits better you use the AIC values.
What is the meaning of getting "infinite"?
It seems you can get infinite AIC and BIC when the distribution you selected is in conflict with the nature of your data. For instance, when you postulate a Poisson model (like in your case), but your data are not integers (counts). Was that the case with you? Distribution families that go along with non-integer (real) data are gaussian and Gamma. You can neither use quasipoisson nor other quasi models, because these do not have AIC.
Can I use the Deviance value to compare the models? And in case I can use the deviance, since there are very close values, should I run a test to see if the differences are significant?? in that case, which one?.
The models have different numbers of estimated parameters and they are not nested. Many people claim that you can use neither deviance nor AIC (and they are right). At least you must take into account the number of estimated parameters that varies from zero to three. Cheers, Jari Oksanen