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Template
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Bayesian statistics
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From Wikipedia, the free encyclopedia
Part of a series on
Bayesian statistics
Posterior
=
Likelihood
×
Prior
÷
Evidence
Background
Bayesian inference
Bayesian probability
Bayes' theorem
Bernstein–von Mises theorem
Coherence
Cox's theorem
Cromwell's rule
Likelihood principle
Principle of indifference
Principle of maximum entropy
Model building
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
(
Schwarz criterion
)
Model averaging
Posterior predictive
Mathematics portal
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Bayesian statistics
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