I have a multivariate distribution parametrized by a vector
mu and a Cholesky decomposed covariance matrix
sigma = L.L^T. Pretty much the same as in the docs.
Now I want to update the prior whenever I have new data available, but the examples do not cover how to do this for cases where the parameters are vector valued.
I looked at this question which discusses the problem but no clear solution is provided.
What is the right way to do this with PyMC?
Is it possible to apply
from_posterior to each axis of the trace samples and then join the Interpolated distributions? How would this join/concatenation work?