Take the 2-minute tour ×
MathOverflow is a question and answer site for professional mathematicians. It's 100% free, no registration required.

Hello everyone.

I'm looking for a "simple" explanation of the concept of D-separation in a Bayesian Network.

As far as I know the definition is "two variables (nodes) in the network are D-Separated if the information is "blocked" between the two nodes by some evidence about the nodes in the middle.

But I can't pratically understand the concept.

I don't have enough rep to use images so these are the links to the images (just 25kbyte each one) from my dropbox folder.

Pattern 1: https://dl.dropbox.com/u/60525806/Run_NoEvidence%28Sum%20Propagate%20Normal%29.JPG Pattern 1: https://dl.dropbox.com/u/60525806/Run_noEvidence%28Sum%20Propagate%20Normal%29%20_2.JPG Pattern 3: https://dl.dropbox.com/u/60525806/Run_NoEvidence%28Sum%20Propagate%20Normal%29%20_3.JPG

What I would like to understand if in these three patterns:

  1. When there is NO evidence What (and why) nodes are D-separated from the each others
  2. In what cases EVIDENCE about a specific node cause two nodes to be separated

Thank you in advance for any help.

Regards

share|improve this question
add comment

1 Answer

up vote 2 down vote accepted

Try this tutorial http://www.andrew.cmu.edu/user/scheines/tutor/d-sep.html

share|improve this answer
    
thank you. I'll take a look later and of cource if it solves my doubts I'll accept your answer –  Manuel Jun 20 '12 at 14:20
add comment

Your Answer

 
discard

By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.