2. a proper prior distribution p( | ) , and 3. a large, negative s, the posterior distribution of s is proportional to the prior distribution for s, so that p( s |y) / p( s | ) .
2. a proper prior distribution p( | ) , and 3. a large, negative s, the posterior distribution of s is proportional to the prior distribution for s, so that p( s |y) / p( s | ) .
something. 2. Recognize the the prior affects the inferences and choose a good one. 3. Assess the robustness of your conclusions to a range of prior distributions.