Is it possible to obtain various joint distributions instead of marginals? For example, in the Monty Hall example, I'd want something like: g.jq(guest_door='A') to display the joint distribution P(monty_door, prize_door | guest_door='A'). I realize this doesn't scale well when the number of left-over variables is large, and I'm okay if there isn't a magic one-liner function jq to prepare this information.
Is it possible to obtain various joint distributions instead of marginals? For example, in the Monty Hall example, I'd want something like:
g.jq(guest_door='A')
to display the joint distributionP(monty_door, prize_door | guest_door='A')
. I realize this doesn't scale well when the number of left-over variables is large, and I'm okay if there isn't a magic one-liner functionjq
to prepare this information.