I think I understand how to use Tim Brandt's trick to set vary=False, linear=True and construct the gamma posterior from the remaining free parameters. Reading the note here, it also seems possible to do it for the jitter parameter instead.
However, in the GaussianProcess tutorial notebook, both the gamma and jitter parameters are defined with vary=False, linear=True. It is not obvious (at least not to me) how to derive posteriors for both gamma and jitter at the same time? The problem seems underdetermined - has anyone tried it, or is this by any chance a mistake in the Gaussian Process tutorial?
Hi radvel team!
I think I understand how to use Tim Brandt's trick to set
vary=False, linear=True
and construct the gamma posterior from the remaining free parameters. Reading the note here, it also seems possible to do it for the jitter parameter instead. However, in the GaussianProcess tutorial notebook, both the gamma and jitter parameters are defined withvary=False, linear=True
. It is not obvious (at least not to me) how to derive posteriors for both gamma and jitter at the same time? The problem seems underdetermined - has anyone tried it, or is this by any chance a mistake in the Gaussian Process tutorial?Thanks, René