▁as ▁cum ulative ▁fusion ▁of ▁belief s ▁from ▁independent ▁sources ▁which ▁can ▁be ▁mode led ▁with ▁the ▁cum ulative ▁fusion ▁operator . ▁ ▁D emp ster ' s ▁rule ▁of ▁combination ▁is ▁sometimes ▁interpreted ▁as ▁an ▁approximate ▁general isation ▁of ▁Bay es ' ▁rule . ▁In ▁this ▁interpretation ▁the ▁pri ors ▁and ▁condition als ▁need ▁not ▁be ▁specified , ▁unlike ▁traditional ▁Bay esian ▁methods , ▁which ▁often ▁use ▁a ▁symmetry ▁( min im ax ▁error ) ▁argument ▁to ▁assign ▁prior ▁prob abilities ▁to ▁random ▁variables ▁( e . g . ▁assigning ▁ 0 . 5 ▁to ▁binary ▁values ▁for ▁which ▁no ▁information ▁is ▁available ▁about ▁which ▁is ▁more ▁likely ). ▁However , ▁any ▁information ▁contained ▁in ▁the ▁missing ▁pri ors ▁and ▁condition als ▁is ▁not ▁used ▁in ▁D emp ster ' s ▁rule ▁of ▁combination ▁unless ▁it ▁can ▁be ▁obtained ▁indirect ly — and ▁arg u ably ▁is ▁then ▁available ▁for ▁calculation ▁using ▁Bay es ▁equations . ▁ ▁D emp ster – S ha fer ▁theory ▁allows ▁one ▁to ▁specify ▁a ▁degree ▁of ▁ignor ance ▁in ▁this ▁situation ▁instead ▁of ▁being ▁forced ▁to ▁supply ▁prior ▁prob abilities ▁that ▁add ▁to ▁unity . ▁This ▁sort ▁of ▁situation , ▁and ▁whether ▁there ▁is ▁a ▁real ▁distinction ▁between ▁risk ▁and ▁ignor ance , ▁has ▁been ▁extens ively ▁discussed ▁by ▁statist icians ▁and ▁econom ists . ▁See , ▁for ▁example , ▁the ▁contrast ing ▁views ▁of ▁Daniel ▁Ell s berg , ▁Howard ▁Ra iff a , ▁Kenneth ▁Ar row ▁and ▁Frank ▁Knight . ▁ ▁F ormal ▁definition