▁uncertainty ▁model ▁measures ▁how ▁distant ▁other ▁values ▁of ▁the ▁parameter ▁are ▁from ▁the ▁estimate : ▁as ▁uncertainty ▁increases , ▁the ▁set ▁of ▁possible ▁values ▁increase ▁– ▁if ▁one ▁is ▁this ▁uncertain ▁in ▁the ▁estimate , ▁what ▁other ▁parameters ▁are ▁possible ? ▁Rob ust ness / o pport un eness ▁model ▁Given ▁an ▁uncertainty ▁model ▁and ▁a ▁minimum ▁level ▁of ▁desired ▁outcome , ▁then ▁for ▁each ▁decision , ▁how ▁uncertain ▁can ▁you ▁be ▁and ▁be ▁assured ▁ach ieving ▁this ▁minimum ▁level ? ▁( This ▁is ▁called ▁the ▁robust ness ▁of ▁the ▁decision .) ▁Con vers ely , ▁given ▁a ▁desired ▁wind fall ▁outcome , ▁how ▁uncertain ▁must ▁you ▁be ▁for ▁this ▁des irable ▁outcome ▁to ▁be ▁possible ? ▁( This ▁is ▁called ▁the ▁opportun eness ▁of ▁the ▁decision .) ▁Dec ision - making ▁model ▁To ▁decide , ▁one ▁optim izes ▁either ▁the ▁robust ness ▁or ▁the ▁opportun eness , ▁on ▁the ▁basis ▁of ▁the ▁robust ness ▁or ▁opportun eness ▁model . ▁Given ▁a ▁desired ▁minimum ▁outcome , ▁which ▁decision ▁is ▁most ▁robust ▁( can ▁stand ▁the ▁most ▁uncertainty ) ▁and ▁still ▁give ▁the ▁desired ▁outcome ▁( the ▁robust - s atisf icing ▁action )? ▁Alternatively , ▁given ▁a ▁desired ▁wind fall ▁outcome , ▁which ▁decision ▁requires ▁the ▁least ▁uncertainty ▁for ▁the ▁outcome ▁to ▁be ▁achiev able ▁( the ▁opport une - wind fall ing ▁action )? ▁ ▁Mod els ▁ ▁Info - g ap ▁theory ▁models ▁uncertainty ▁ ▁( the ▁horizon ▁of ▁uncertainty ) ▁as ▁nested ▁subsets ▁ ▁around ▁a ▁point ▁estimate ▁ ▁of