Implementing late-entering series in a PyMC state-space model

it’s just a question of passing nan

And making sure they are ignored during likelihood calculation instead of imputing them. How do I make sure they are ignored and not imputed? I did find this comment from another thread.

If you look here they are filtering out the rows and columns of the covariance matrix wherever nan values are there. I was wondering if I can reproduce this in PyMC and how.