above, an induced measure on Pt, which will be denoted μk and we define
the set of priors
M (P*)
{∑
к
Xkμk: ʌ ∈Δ
It is easy to check that this definition agrees with that given above for the
case P * = {p', p'}
7.1 Consistent updating with multiple priors
The definition of consistent updating with a unique measure μ can be ex-
tended in a straightforward fashion to the case of a given λ∈M (P*) . For
each k,i,t we may define μlt k as above and set
X = ∑ Wh
к
and similarly for μt+ 1 k and λ^+ 1 k For all i,t,p,k,
μltlι,k (E (P)) = μlt+ι,k(E (P))
then for all i,t,p
⅛+ 1 (E (p)) = ‰ (E (p))
so that consistent Bayesian updating for each μk is sufficient to ensure con-
sistent Bayesian updating for all λ ∈ M (P*) . Necessity is trivial.
Now, by the definition of μk, we obtain: 5
Proposition 2 Consistent Bayesian updating for all X ∈ M (P*) holds if
and only if, for any p,p',p'' such that p ∈ Pt, p' ∈ P * ,p" ∈ P ',
μ (p Λ p' Λ p") = μ (p Λ p') Λ μ (p'')
5By additivity, the condition includes the special cases
P (p λ p") = P (p) λ P (p")
and
p (p' Λ p") = p (p') Λ p (p").
For the first choose p ∈ P∖ p' ∈ P*,p'' ∈ P l,, apply the condition first with p,p',p'',
then with p, -∣p', p'' and add. Similarly for the second.
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