FIGURE B.1 Mathematical definition of BTRA event tree and solution for tree probabilities. This defines a BTRA event tree and shows how to completely evaluate all probabilities for every path. This definition applies whether or not the tree includes all agents, or just one of them.

FIGURE B.2 Mathematical definition of BTRA risk analysis. This shows how to completely evaluate all cost consequences and risk (expected cost). The paths here have one extra, final stage that BTRA does not: This stage eliminates the necessity for separate notation for consequence distributions, with each of its outcomes resulting in a scalar cost consequence. A Monte Carlo sampling to estimate these computed parameters would proceed by randomly selecting a path p_G−1={a₁,a₂,…,a_G−1} (the probability of this path could be computed by but this is not essential) and collecting this result as a sample statistic.