Bayes' theorem

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theorem

(the'o-rem) [Gr. theorema, principle arrived at by speculation]
A proposition that can be proved by use of logic, or by argument, from information previously accepted as being valid.

Bayes' theorem

See: Bayes' theorem.
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References in periodicals archive ?
Ghosh, "Bayesian variable selection and estimation for group lasso," Bayesian Analysis, vol.
Apply Bayesian estimation model to estimate missing diameters (Figure 4).
Therefore, we plan to use the three-phase dependency analysis Bayesian network structure learning method to construct the network including maize genes and carotenoid components.
A set of variables X = {[X.sub.1], [X.sub.2], ..., [X.sub.n]} of Bayesian network consists of the following components [37] S is a network structure which denotes the conditional independent assertion in variable set X, P is a set of local probability distributions associated with each variable, [X.sub.i] denotes the variable node, and [pa.sub.i] denotes the father node of [X.sub.i] in S.
All of these software packages provide programs for Bayesian modeling through posterior simulation given a specified model and data.
Table I presents the DIC values for each growth curve fitted via Bayesian approach to average weight of Mengali sheep from birth to two years of age for both sexes and type of births.
The Crude Rate of mortality from cancer of the mouth for the year 2012 was adopted, as standard for comparison for the application of smoothing by the Bayesian models (10,11,14).
[10.] Guerin, F.; Dumon, B.; Usureau, E.2003.Reliability estimation by bayesian methode: definition of prior distribution using dependability study.
Bayesian stepwise discriminant analysis was used to analyze the etiological infections of CT, UU, C.
The remainder of this paper is outlined as follows: first, the T-S fuzzy gate fault tree and Bayesian network are briefly reviewed.
As a special case of Bayesian network, the naive Bayesian classifier does not need the predetermination of network structure [13].
When modal data is used as evidence in a Bayesian damage detection algorithm, many studies have suggested different ways to take variance for prediction error model of frequency and mode shape data types [26-30].