Suppose that in a Bayesian network containing an unobserved variable
$Y$, all the variables in the Markov blanket ${MB}(Y)$ have been
observed.
1. Prove that removing the node $Y$ from the network will not affect
the posterior distribution for any other unobserved variable in
the network.
2. Discuss whether we can remove $Y$ if we are planning to use (i)
rejection sampling and (ii) likelihood weighting.
Three possible structures for a Bayesian network describing genetic inheritance of handedness.
Suppose that in a Bayesian network containing an unobserved variable
$Y$, all the variables in the Markov blanket ${MB}(Y)$ have been
observed.
1. Prove that removing the node $Y$ from the network will not affect
the posterior distribution for any other unobserved variable in
the network.
2. Discuss whether we can remove $Y$ if we are planning to use (i)
rejection sampling and (ii) likelihood weighting.
Three possible structures for a Bayesian network describing genetic inheritance of handedness.
