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Bayesian inference

Bayesian statistics
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Posterior = Likelihood × Prior ÷ Evidence
Background
Bayesian inference Bayesian probability Bayes' theorem Bernstein–von Mises theorem Coherence Cox's theorem Cromwell's rule Principle of indifference Principle of maximum entropy
Model building
Weak prior ... Strong prior Conjugate prior Linear regression Empirical Bayes Hierarchical model
Posterior approximation
Markov chain Monte Carlo Laplace's approximation Integrated nested Laplace approximations Variational inference Approximate Bayesian computation
Estimators
Bayesian estimator Credible interval Maximum a posteriori estimation
Evidence approximation
Evidence lower bound Nested sampling
Model evaluation
Bayes factor Model averaging Posterior predictive
v t e

Bayesian inference (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən)^[1] is a type of statistical inference. In Bayesian inference, evidence or information is available, Bayes' theorem is used to change (or update) the probability of a hypothesis. Bayesian inference uses a prior distribution to estimate posterior probabilities. Bayesian inference is an important to statistics, mathematical statistics, decision theory, and sequential analysis. Bayesian inference is used in science, engineering, philosophy, medicine, sport, and law.

↑ "Bayesian". Merriam-Webster Dictionary.

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Bayesiaanse statistiek AF استدلال بايزي Arabic Inferencia bayesiana AST Inferència bayesiana Catalan Anwythiad Bayesaidd CY Bayesiansk statistik Danish Bayessche Inferenz German Συμπέρασμα του Μπέυζ Greek Bayesian inference English Inferencia bayesiana Spanish

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