0 %" ▁border =" 0 " ▁| ▁( 7 ) ▁|   ▁for ▁some ▁ ▁  ▁  ▁  ▁      ▁▁      ▁| } ▁ ▁In ▁other ▁words , ▁for ▁any ▁given ▁decision , ▁info - g ap ' s ▁analysis ▁yields ▁the ▁same ▁results ▁for ▁all ▁total ▁regions ▁of ▁uncertainty ▁that ▁contain ▁. ▁This ▁applies ▁to ▁both ▁the ▁robust ness ▁and ▁opportun eness ▁models . ▁ ▁This ▁is ▁illustrated ▁in ▁the ▁picture : ▁the ▁robust ness ▁of ▁a ▁given ▁decision ▁does ▁not ▁change ▁not with standing ▁an ▁increase ▁in ▁the ▁region ▁of ▁uncertainty ▁from ▁ ▁to ▁ ▁. ▁ ▁In ▁short , ▁by ▁d int ▁of ▁foc using ▁exclus ively ▁on ▁the ▁immediate ▁neighborhood ▁of ▁the ▁estimate ▁ ▁info - g ap ' s ▁robust ness / o pport un eness ▁models ▁are ▁inher ently ▁local . ▁ ▁For ▁this ▁reason ▁they ▁are ▁-- ▁ ▁in ▁principle ▁-- ▁in cap able ▁of ▁incorpor ating ▁in ▁the ▁analysis ▁of ▁▁ ▁and ▁ ▁regions ▁of ▁uncertainty ▁that ▁lie ▁outside ▁the ▁neighborhood s ▁ ▁and ▁ ▁of ▁the ▁estimate ▁, ▁respectively . ▁ ▁To ▁illustrate , ▁consider ▁a ▁simple ▁numerical ▁example ▁where ▁the ▁total ▁region ▁of ▁uncertainty ▁is ▁ ▁the ▁estimate ▁is ▁▁ ▁and ▁for ▁some ▁decision ▁ ▁we ▁obtain ▁. ▁The ▁picture ▁is ▁this : ▁ ▁where ▁the ▁term ▁ ▁" No ▁man ' s ▁land " ▁  ▁refers ▁to ▁the ▁part ▁of ▁the ▁total ▁region ▁of ▁uncertainty ▁that ▁is ▁outside ▁the ▁region ▁. ▁ ▁Note ▁that ▁in ▁this ▁case ▁the ▁robust