  One of the most useful sensitivity analysis techniques of decision analysis
is the computation of value of information (or clairvoyance), the difference in
value obtained by changing the decisions by which some of the uncertainties are
observed. In this paper, some simple but powerful extensions to previous
algorithms are introduced which allow an efficient value of information
calculation on the rooted cluster tree (or strong junction tree) used to solve
the original decision problem.
