Viewing posts for the category Note

Idea - Using compression to extract building blocks

So, initially when I was using CTW the problem was with VQ, in particular, independence of the quantization from the inference in the Markovian model. I solved that using HMMs so that the quantization is learned simultaneously with the structure.

Comparing HMMs state-by-state and Choosing Initial Values for Emission Means

I just realized that I can meaningfully compare many HMMs if I sort the states. If I put in initial emission distribution means so that for a univariate case the first state is the one with the lowest mean whereas the last one is the one with the highest mean, then I can ensure that I get the same state labeling for all trained models. This naturally extends to the multivariate case.

Big poop - Journal paper is wrong!

I have just noticed that the first journal paper we are planning to send in with Hannah contains a huge error: I keep mentioning predictors, but I should be talking about random effects!

lme4 and P-values

There is a lot of stuff online about eliciting p-values for lme4 linear mixed-effects regression model coefficients (just google it). I opted for MCMCglmm because I like MCMC , and because lme4 has deprecated its own MCMC implementation.