, ▁while ▁similar ▁in ▁some ▁ways , ▁is ▁not ▁minim ax ▁worst - case ▁analysis , ▁as ▁it ▁does ▁not ▁evaluate ▁dec isions ▁over ▁all ▁possible ▁out comes , ▁while ▁( S n ied ov ich , ▁ 2 0 0 7 ) ▁arg ues ▁that ▁the ▁robust ness ▁analysis ▁can ▁be ▁seen ▁as ▁an ▁example ▁of ▁maxim in ▁( not ▁minim ax ), ▁applied ▁to ▁maxim izing ▁the ▁horizon ▁of ▁uncertainty . ▁This ▁is ▁discussed ▁in ▁criticism , ▁below , ▁and ▁elabor ated ▁in ▁the ▁classical ▁decision ▁theory ▁perspective . ▁ ▁Basic ▁example : ▁budget ▁ ▁As ▁a ▁simple ▁example , ▁consider ▁a ▁worker ▁with ▁uncertain ▁income . ▁They ▁expect ▁to ▁make ▁$ 1 0 0 ▁per ▁week , ▁while ▁if ▁they ▁make ▁under ▁$ 6 0 ▁they ▁will ▁be ▁unable ▁to ▁afford ▁lod ging ▁and ▁will ▁sleep ▁in ▁the ▁street , ▁and ▁if ▁they ▁make ▁over ▁$ 1 5 0 ▁they ▁will ▁be ▁able ▁to ▁afford ▁a ▁night ' s ▁entertain ment . ▁ ▁Using ▁the ▁info - g ap ▁absolute ▁error ▁model : ▁ ▁where ▁ ▁one ▁would ▁conclude ▁that ▁the ▁worker ' s ▁robust ness ▁function ▁ ▁is ▁$ 4 0 , ▁and ▁their ▁opportun eness ▁function ▁ ▁is ▁$ 5 0 : ▁if ▁they ▁are ▁certain ▁that ▁they ▁will ▁make ▁$ 1 0 0 , ▁they ▁will ▁neither ▁sleep ▁in ▁the ▁street ▁nor ▁fe ast , ▁and ▁like wise ▁if ▁they ▁make ▁within ▁$ 4 0 ▁of ▁$ 1 0 0 . ▁However , ▁if ▁they ▁er red