Updating Subjective Probability.

Jeffrey's rule for revising a probability P to a new probability P* based on new probabilities P* (E[sub I]) on a partition {E[sub I]}[sub I = 1[sup n]] is P[sup *](A) = SIGMA P(A | E[sub I])P[sup *](E[sub I]). Jeffrey's rule is applicable if it is judged that P[sup *](A | E[sub I]) = P(A | E[sub I]) for all A and I. This article discusses some of the mathematical properties of this rule, connecting it with sufficient partitions, and maximum entropy updating of contingency tables. The main results concern simultaneous revision on two partitions. [ABSTRACT FROM AUTHOR]