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 ?
Here, P([phi]) is the prior distribution of the individual model parameters and hyperparameters, P(D|[phi]) is the likelihood, and P(D) can be treated as a normalization factor.
Uncertainty about the true values of the GARCH parameters was incorporated into the analysis through a non-informative joint prior distribution.
There are four main steps in the presented method: (1) Firstly, to provide the active contour analysis with an enabled environment, we weaken the background interference by a prior distribution based on a seed-based method.
Assume that the conjugate prior distribution of [theta] is the Gamma prior distribution [GAMMA]([alpha], [beta]), with pdf
Another possible choice for the prior distribution of [[eta].
The structured spatial term is assigned the Gaussian Conditional Autoregression (CAR) prior distribution and period effect is assigned the Gaussian prior.
For the model error [delta](x), we need to select the prior distribution for each hyper-parameter in the above formulation.
At the first step, that is, k = 1, n samples of the four parameters are generated randomly from the prior distribution, based on the Gaussian distribution of specified means and standard deviations.
When p varies from lot-to-lot at random and is distributed as gamma distribution which is the natural conjugate prior for sampling from the Poisson distribution, the density function of prior distribution of p is given by
For each producer in Stage 3, the prior distribution is given such that E([Q.