▁and ▁interpretation ▁of ▁a ▁bootstrap ▁distribution ▁does ▁not ▁involve ▁any ▁fid u cial ▁reasoning ; ▁the ▁same ▁is ▁true ▁for ▁the ▁concept ▁of ▁a ▁confidence ▁distribution . ▁But ▁the ▁notion ▁of ▁confidence ▁distribution ▁is ▁much ▁bro ader ▁than ▁that ▁of ▁a ▁bootstrap ▁distribution . ▁In ▁particular , ▁recent ▁research ▁suggests ▁that ▁it ▁en comp ass es ▁and ▁un ifies ▁a ▁wide ▁range ▁of ▁examples , ▁from ▁regular ▁paramet ric ▁cases ▁( including ▁most ▁examples ▁of ▁the ▁classical ▁development ▁of ▁Fish er ' s ▁fid u cial ▁distribution ) ▁to ▁bootstrap ▁distributions , ▁p - value ▁functions , ▁normal ized ▁lik elihood ▁functions ▁and , ▁in ▁some ▁cases , ▁Bay esian ▁pri ors ▁and ▁Bay esian ▁poster iors . ▁ ▁Just ▁as ▁a ▁Bay esian ▁posterior ▁distribution ▁contains ▁a ▁wealth ▁of ▁information ▁for ▁any ▁type ▁of ▁Bay esian ▁inference , ▁a ▁confidence ▁distribution ▁contains ▁a ▁wealth ▁of ▁information ▁for ▁construct ing ▁almost ▁all ▁types ▁of ▁frequent ist ▁infer ences , ▁including ▁point ▁estimates , ▁confidence ▁intervals ▁and ▁p - values , ▁among ▁others . ▁Some ▁recent ▁develop ments ▁have ▁highlight ed ▁the ▁prom ising ▁potential s ▁of ▁the ▁CD ▁concept , ▁as ▁an ▁effective ▁infer ential ▁tool . ▁ ▁The ▁history ▁of ▁CD ▁concept ▁▁ ▁Ne yman ▁( 1 9 3 7 ) ▁introduced ▁the ▁idea ▁of ▁" conf idence " ▁in ▁his ▁sem inal ▁paper ▁on ▁confidence ▁intervals ▁which ▁clar ified ▁the ▁frequent ist ▁repet ition ▁property . ▁According ▁to ▁F ras er , ▁the ▁seed ▁( idea ) ▁of ▁confidence ▁distribution ▁can