Equation (A16) is utilized when formulating the

marginal probability density functions for f ([x.sub.2]), f ([x.sub.3]), f ([y.sub.1+2] - [y.sub.1]) and f ([y.sub.1+2+3] - [y.sub.1+2]).

This study highlights the importance of education in determining attendance in a developing country; in Mexico, the

marginal probability that a high school graduate will attend a sporting event is four times that of someone with little schooling, while that of a college graduate is seven times higher.

The cleared historical data was input into the established GeNIe Bayesian network model to calculate the

marginal probability and conditional probability of the Bayesian network, and the passenger security during shipping was evaluated (Figure 3).

Thus, the

marginal probability density functions of cost and schedule are defined as

While the practical implications for CT scan services were somewhat less than for cardiac SSH competition, the

marginal probability of .207 represents a considerable predicted reaction.

The

marginal probability for GMI rating in the litigation probit regressions is 0.58%, but the

marginal probability in delisting regressions is very close to zero.

For instance, we may adopt the criterion that the best label value for Yi is simply the one corresponding to the highest

marginal probability obtained by summing over all other variables from the probability distribution associated with the pairwise MRF.

7) by averaging out with respect to the

marginal probability element P(dw) = dw/(2[pi]) for each [theta].

The

marginal probability coefficient of the first educational level (1-8 years) of decisionmaker is significant only for boiling method.

P(A) is the prior or

marginal probability of A (the probability of a cocaine-positive outcome).

Notwithstanding, as Multinomial Logit coefficients do not inform about the size and direction of the effects of marginal variations in the explanatory variables over the dependent variable, we calculate, additionally, the

marginal probability distribution functions corresponding to the both types of matches.

where m(x) is the

marginal probability of test result x, and r(x) is the conditional disease probability given x; m(x) and r(x) clearly depend on p as well as on data contained in the ROC curve.