Exercise 13.MRBL askes you to prove that removing an observed variable Y from a Bayes net has no effect on the posterior disribution of any variable X that is outside Y ’s Markov blanket, provided that every variable in Y ’s markov blanket is observed. In this question, we consider the effect of removing Y on inference algorithms that estimate the posterior for X from samples. What is the effect of removing Y on (i) rejection sampling and (ii) likelihood weighting? Consider both correctness and efficiency.