posterior probabilities

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posterior probabilities

[pä′stir·ē·ər präb·ə′bil·əd·ēz]
(statistics)
Probabilities of the outcomes of an experiment after it has been performed and a certain event has occurred.
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Model parameters with summaries of their prior and posterior probability distributions.
7: Computer for each class the posterior probability P ([C.
88, respectively, when the posterior probability was set at [PP.
prasina (section Hymenochlaenae)(Bayesian posterior probability = 0.
Note that the posterior probability is a monotone increasing function of the probability ratio (P(m)/Q(m)).
For GDP, typically we found the single break model is best, but at times the three break model has higher posterior probability.
Bayesian Model Averaging also utilizes a large number of regressions, but the models are weighted by a Bayesian posterior probability.
from the posterior probability density function, it is usually necessary to integrate the right-hand side of Equation (1) with respect to [theta].
By structuring the problem of valuing ER in terms of an economic surplus payoff matrix (as in Table 1), and prior, joint, conditional, and posterior probability matrices, BDT may facilitate calculation of the value of information generated by ER messages from various sources.
For example, for group 1, the mean posterior probability was .
iii) Bayesian Inference of Likelihood with posterior probability of phylogenies approximated by sampling trees from the posterior probability distribution.
They then show that there is a strong and statistically robust correlation between low macroeconomic volatility and high asset prices: the estimated posterior probability of being in a low volatility state explains 30 to 60 percent of the post war variation in the log price-dividend ratio, depending on the measure of consumption analyzed.

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