bayesian criterion
1Bayesian probability — Bayesian statistics Theory Bayesian probability Probability interpretations Bayes theorem Bayes rule · Bayes factor Bayesian inference Bayesian network Prior · Posterior · Likelihood …
2Bayesian experimental design — provides a general probability theoretical framework from which other theories on experimental design can be derived. It is based on Bayesian inference to interpret the observations/data acquired during the experiment. This allows accounting for… …
3Bayesian inference — is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. The name Bayesian comes from the frequent use of Bayes theorem in the inference process. Bayes theorem… …
4Bayesian — refers to methods in probability and statistics named after the Reverend Thomas Bayes (ca. 1702 ndash;1761), in particular methods related to: * the degree of belief interpretation of probability, as opposed to frequency or proportion or… …
5Bayesian information criterion — In statistics, in order to describe a particular dataset, one can use non parametric methods or parametric methods. In parametric methods, there might be various candidate models with different number of parameters to represent a dataset. The… …
6Bayesian network — A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). For example …
7Bayesian model comparison — A common problem in statistical inference is to use data to decide between two or more competing models. Frequentist statistics uses hypothesis tests for this purpose. There are several Bayesian approaches. One approach is through Bayes… …
8Deviance information criterion — The deviance information criterion (DIC) is a hierarchical modeling generalization of the AIC (Akaike information criterion) and BIC (Bayesian information criterion, also known as the Schwarz criterion). It is particularly useful in Bayesian… …
9Information criterion — may refer to: *Akaike information criterion, a measure of the goodness fit of an estimated statistical model *Bayesian information criterion also known as the Schwarz information criterion, a statistical criterion for model selection *Hannan… …
10The Intuitive Criterion — DefinitionThe Intuitive Criterion, first described in 1987 Cho and Kreps article, is a refinement of the solution concept that allows the modeller to choose between multiple perfect Bayesian equilibria.Formally, we can eliminate a particular… …
