*Continuing with bacterial group-a-palooza…*

I followed Ed’s suggestions and tried both a binomial distribution and a Poisson distribution for abundance such that the probability of a density of one species s in one group g in one plot r where there are S_g species in group gis

In the analysis I’m doing, interesting, the results do change a bit such that the original network only results are confirmed.

I am having one funny thing, though, which I can’t lock down. Namely, the no-group option always has the lowest AIC once I include abundances – and this is true both for binomial and Poisson distributions. Not sure what that is about. I’ve put the code for all of this here and made a sample script below. This doesn’t reproduce the behavior, but, still. Not quite sure what this blip is about.

For the sample script, we have five species and three possible grouping structures. It looks like this, where red nodes are species or groups and blue nodes are sites:

And the data looks like this

```
low med high 1 2 3
1 1 1 1 50 0 0
2 2 1 1 45 0 0
3 3 2 2 0 100 1
4 4 2 2 0 112 7
5 5 3 2 0 12 110
```

So, here’s the code:

And the results:

```
> aicdf
k LLNet LLBinomNet LLPoisNet AICpois AICbinom AICnet
low 5 0 0.00000 -20.54409 71.08818 60.00000 30
med 3 0 -18.68966 -23.54655 65.09310 73.37931 18
high 2 0 -253.52264 -170.73361 353.46723 531.04527 12
```

We see that the two different estimations disagree, with the binomial favorint disaggregation and poisson favoring moderate aggregation. Interesting. Also, the naive network only approach favors complete aggregation. Interesting. Thoughts?