Lots of goals, but lots of progress! Ask Brian about writing me a letter for a JSM travel award.
MMSBM – I coded the single network sampler to estimate the Dirichlet hyperparameter and so far things look okay.
***Found a pretty major mistake, so I think the gammas won’t go flying off into space – hooray!***
I have 3 different networks I’m working with, which I’m going to change to 2. More explanation below.
(1) membership probabilities generated with c(0.05, 0.05, 0.05) lambda. With fairly flat priors (\gamma ~ Gamma(1,1) and \xi ~ Dir(1,1,1)), we recovered these nicely and in 5000 iterations.
(2) membership probs generated with c(0.25, 0.25, 0.25) was much more of a challenge. For some reason, with \gamma ~ Gamma(1,1), our gamma parameters were just going off into oblivion. I actually couldn’t tell which was going off first, the \xi or the \gammas, but a prior of Gamma (1,2) was enough to keep things on track. Oops, spoke too soon. It keeps things on track about 30% of the time.
**I think the solution might be to bound the gamma, but I’m sure there’s a better explanation***
(3) I think it doesn’t really make sense to focus on networks generating with anything higher, actually. But the third network is generated with c(0.5, 0.5, 0.5) and I anticipate the same issue with gamma and xi. We’ll see if a Gamma(1,2) prior works on this one.
Hopefully Brian and Andrew can help me figure that out tomorrow.
HLSM – results have been put in the final paper. It’s been proofed and now the only things I need to do are (a) proof read that last section and (b) ready it for submission!!!
And as far as paper writing is concerned, I’ve “started” the MM chapter, but I have a ways to go. I am going to write the paper in more detail later this week…but I’m having a hard time jumping in to write when I don’t actually have results yet. But now that things are looking a little better, I think I might be ready to do a bit more. An introduction will be last, but that’s not too terribly taxing. I’ll probably need to dig up a few more papers depending on whether I focus on a blockmodel entrance or mm entrance…or something else entirely.