Table 2. Algorithm 2: An implementation of Algorithm 1 in which practical adjustments are included.

Input (a) likelihood function ; (b) prior ; (c) number of active parameter vectors in use during nested sampling; (d) procedure for determining a region of parameter space that encloses a set of parameter vectors ; (e) fraction of to be estimated.

Output: an estimate of .

1: Let be a set of parameter vectors

2:

3:

4:Repeat

5:

6:

7:

8: if then

9:  ▹Estimated segment of

10:

11:  ▹Restricted prior

12:

13:

14: until:  ▹The stopping condition

return