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?