▁an ▁info - g ap ▁model ▁der ives ▁from ▁the ▁information ▁about ▁the ▁uncertainty . ▁In ▁general ▁terms , ▁the ▁structure ▁of ▁an ▁info - g ap ▁model ▁of ▁uncertainty ▁is ▁chosen ▁to ▁define ▁the ▁smallest ▁or ▁strict est ▁family ▁of ▁sets ▁whose ▁elements ▁are ▁consistent ▁with ▁the ▁prior ▁information . ▁Since ▁there ▁is , ▁usually , ▁no ▁known ▁worst ▁case , ▁the ▁family ▁of ▁sets ▁may ▁be ▁un bounded . ▁ ▁A ▁common ▁example ▁of ▁an ▁info - g ap ▁model ▁is ▁the ▁fraction al ▁error ▁model . ▁The ▁best ▁estimate ▁of ▁an ▁uncertain ▁function ▁ ▁is ▁, ▁but ▁the ▁fraction al ▁error ▁of ▁this ▁estimate ▁is ▁unknown . ▁The ▁following ▁un bounded ▁family ▁of ▁nested ▁sets ▁of ▁functions ▁is ▁a ▁fraction al - error ▁info - g ap ▁model : ▁ ▁At ▁any ▁horizon ▁of ▁uncertainty ▁, ▁the ▁set ▁ ▁contains ▁all ▁functions ▁ ▁whose ▁fraction al ▁deviation ▁from ▁ ▁is ▁no ▁greater ▁than ▁. ▁However , ▁the ▁horizon ▁of ▁uncertainty ▁is ▁unknown , ▁so ▁the ▁info - g ap ▁model ▁is ▁an ▁un bounded ▁family ▁of ▁sets , ▁and ▁there ▁is ▁no ▁worst ▁case ▁or ▁greatest ▁deviation . ▁ ▁There ▁are ▁many ▁other ▁types ▁of ▁info - g ap ▁models ▁of ▁uncertainty . ▁All ▁info - g ap ▁models ▁obey ▁two ▁basic ▁ax i oms : ▁ ▁N est ing . ▁The ▁info - g ap ▁model ▁ ▁is ▁nested ▁if ▁ ▁implies ▁that : ▁ ▁Cont raction . ▁The ▁info - g ap ▁model ▁ ▁is ▁a ▁singleton ▁set