prior distribution


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prior distribution

[¦Prī·ər ‚dis·trə′byü·shən]
(statistics)
A probability distribution on the set of all possible values of an unknown parameter of a statistical model that describes information available from sources other than a statistical investigation, in particular, expert judgment, past experience, or prior belief.
References in periodicals archive ?
the distribution of the parameters T posterior to the measurement of the data y --and Equation (4) can be expressed in words as "the posterior distribution is proportional to the prior distribution times the likelihood".
2000) to implement Markov Chain Monte Carlo (MCMC) sampling to make repeated draws from the "posterior distribution" of each parameter--the prior distribution was updated conditionally on the data and structural relationships of the model.
We therefore set the prior distribution for [theta] to be beta with a mean of 0.
The prior distribution is the primary "controversy" of Bayesian analysis.
We note that the marginal prior distributions turned out to be practically noninformative with these prior variances.
The prior distribution of p is chosen to be a Dirichlet distribution Di([a.
Another improvement in estimation can be a better development of the prior distribution for the probabilities of specific failure modes.
The paper considers the case where the new data used for the updating of the prior distribution has the form of a small-size statistical sample.
Nonparametric Tests: These do not assume any prior distribution, and thus are used extensively with non-normal data.
Normally the user has a great deal of available information for obtaining the prior distribution [pi]([[theta].