posterior probability

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Related to Posterior distribution: Prior distribution

posterior probability

n
(Statistics) statistics the probability assigned to some parameter or to an event on the basis of its observed frequency in a sample, and calculated from a prior probability by Bayes' theorem. Compare prior probability See also empirical5
References in periodicals archive ?
In this method, inferences about unknown genetic interaction effects are based on their marginal posterior distribution in a Bayesian framework.
if 95% of the posterior distribution of predicted prevalence was >0.
The prior is combined with the likelihood function to form the posterior distribution, which summarizes the postdata information about the VAR parameters.
Within that framework, it is straightforward to obtain the posterior distribution for T.
Given that X [is less than or equal to] E, where E is a positive constant, the posterior distribution of [Lambda] has mean
Two Markov chains were initiated at overdispersed starting values and each chain ran for 1,000 iterations to allow for the Markov chains to converge to the posterior distribution.
I use the Metropolis-Hastings algorithm to generate draws from the posterior distribution.
Bayesian methods start with prior distributions for the parameters of interest (information available before the analysis), and integrate over the joint posterior distribution of all model parameters, capturing parameter uncertainty as well as the correlation structure among these parameters.
To reduce the storage space for the samples, the remaining 150,000 samples were thinned by a factor of 50, resulting in a total of 3,000 draws from the joint posterior distribution.
Given the data observed, application of Bayes rule enables estimation of the posterior distribution of both the size and time of attack, from which summary statistics such as the mean, standard deviation, and probability intervals of the attack size and time are easily estimated.
This posterior distribution may, in turn, be considered the prior distribution relative to a second estimator.
is estimated, the posterior distribution of [theta] can be obtained by using the Bayes rule, p([theta]|y, [?

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