The primary quantity of interest is an estimate of R(N) as
defined in Equation 
. In particular it is the
posterior estimate,
that is of interest, as a function of N.
Using the form of R(N) in Equation this reduces to
using the result in Equation .
Since
is Gaussian, these are easy to evaluate. The expected value in
Equation can be estimated using samples from the
posterior. If there are S samples from the posterior,
then the approximation
is used for 
. This is a kernel density estimate as
outlined in Section .
