where [X.sub.ui] is a vector of observable variables of the birth

probability function; [B.sup.u], [B.sup.h], and [Mathematical Expression Omitted] are the parameters to be estimated; [[Epsilon].sub.ui] and [[Epsilon].sub.hi] are the two stochastic terms in each equation.

The central notions on which we based our account are that of a body of background information which the individual's

probability function reflects at any given time, and an addition to that information which the rule of conditionalization transforms into an output consisting of an updated

probability function.

The assumed

probability functions, p(q|[[Theta]), for the three types of banks are as follows: q [element of] [-1,0] q [element of] (0,1] p(q|[[Theta].sub.1]) 0.6q + 0.6 0.35 p(q|[[Theta].sub.2]) 0.3q + 0.3 0.10 p(q|[[Theta].sub.3]) 0.2q + 0.2 0.10 q [element of] (1,2] q [element of] (2,3] p(q|[[Theta].sub.1]) 0.20 0.15 p(q|[[Theta].sub.2]) 0.45 0.30 p(q|[[Theta].sub.3]) 0.20 0.60

It is shown here how this result depends directly on the nature of the

probability functions at the optimum.

Each probability represented in the first term in brackets is derived using coefficients of the white

probability functions. The second term in brackets represents the part of the overall difference in occupations that is due to differences in coefficients of the

probability functions.

Logit estimates for the

probability functions Prob([A.sub.j] = J) and Prob([D.sub.j] = J), calculated for the pooled sample and separately by race, are available from the author on request.(8)

The same graph shows the correlation of ROSI with the weighting factor [W.sub.A], which varies depending on the defined

probability function.

Taking measurement up to the ratio level would thus seem desirable for further characterization of the value and

probability functions.

For each measurement C=10 and the

probability function parameters are: W= 0, Tm= 0.1 (sec) and M=0.85.

For all ([a.sub.i], [a.sub.j]) [member of] [0,1] x [0,1], the

probability functions [p.sub.i]([a.sub.i], [a.sub.j]), i, j = A, B (j [not equal to] i), satisfy:

In order to be coherent with the axioms of the probability calculus the personal

probability functions of ideally rational Bayesian agents must understand completely the logical structure of the propositions over which they are defined.

In addition to estimating the transition

probability functions with service hours included without interactions, we also estimate them with a series of interactions between service levels and disability measures.