I have recently stated here that I was still puzzled by the eta parameter in LKJCholeskyCov.
I’ve now put together a notebook to test the effect of eta. The outcome is still somewhat inconclusive:
- Choosing eta seems voodoo, given that results are unaffected over a broad range of the parameter. I will usually leave it at
eta=1. - Even leaving eta free does not improve the result, and it seems to be challenging for the sampler.
- Instead of setting high eta, one could use an uncorrelated estimate (that’s expected).
I thought this is worth sharing for documentation. But did I miss anything?
Could someone again, in plain words, recap what the eta does technically? I got from the previous discussion that it has to do with normalization of the correlation matrix, but what does that mean for practical application?
Thank you!
Falk