Cross Validated Asked by calveeen on December 24, 2020

Given conditional posterior probabilities of $x$ random variables, can we find the joint distribution by multiplying the conditional posteriors together ? An example would be distribution $$p(x_1,x_2,x_3) = p(x_1|x_2,x_3)p(x_2|x_1,x_3)p(x_3|x_1,x_2) , ?$$ I know that the chain rule of probability would result in $$p(x_1,x_2,x_3) = p(x_1|x_2,x_3)p(x_2|x_3)p(x_3)$$

1 Asked on November 2, 2021 by data-man

0 Asked on November 2, 2021 by franziska

1 Asked on November 2, 2021 by s_haring

3 Asked on March 9, 2021 by pythonnoob

0 Asked on March 4, 2021 by bmurray

0 Asked on March 2, 2021 by pluviophile

1 Asked on March 2, 2021 by sleepy

chi squared test contingency tables ecology hypothesis testing statistical significance

0 Asked on March 1, 2021 by sedi

2 Asked on February 28, 2021 by peterbe

0 Asked on February 27, 2021 by user2991421

categorical data categorical encoding continuous data machine learning random forest

1 Asked on February 27, 2021 by mathslover

1 Asked on February 27, 2021 by misologie

1 Asked on February 25, 2021 by mcgurck

0 Asked on February 25, 2021 by la_haine

0 Asked on February 24, 2021 by zge

0 Asked on February 24, 2021 by diricksen

1 Asked on February 24, 2021 by zvisofer

Get help from others!

Recent Answers

- Peter Machado on Why fry rice before boiling?
- Joshua Engel on Why fry rice before boiling?
- Jon Church on Why fry rice before boiling?
- Lex on Does Google Analytics track 404 page responses as valid page views?
- haakon.io on Why fry rice before boiling?

© 2022 AnswerBun.com. All rights reserved. Sites we Love: PCI Database, MenuIva, UKBizDB, Menu Kuliner, Sharing RPP