Past exam of the mathematics course of the University of Cambridge / 2014 / iii / Paper 35 / 3 / d

Table of contents
- Solution d

Solution

Divide the two normal distribution predictive densities to obtain the Bayes factor

B_{01} (y) = \frac{V _{1}}{V _{0}} exp [- \frac{y ^{2}}{2} (\frac{1}{V _{0}} - \frac{1}{V _{1}})] .

At

y = 0

this becomes

B_{01} (0) = \frac{n _{0} / n + c ^{2}}{n _{0} / n + 1} .

The wider prior distribution spreads its predictive mass over more possible means, giving the narrower model more Bayesian model evidence for observations very near zero. Away from zero, the exponential term opposes that factor.

 Ancestors (10)

 View article source

 Discussion (0)

There are no discussions about this article yet.

 Articles by others on the same topic (0)

There are currently no matching articles.

  See all articles in the same topic Create my own version