Bayes factor

E700155

The Bayes factor is a Bayesian model comparison metric that quantifies how much more strongly data support one statistical model or hypothesis over another.

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Label Occurrences
Bayes factor canonical 1

Statements (48)

Predicate Object
instanceOf Bayesian model comparison metric
likelihood ratio
statistical measure
alternativeName Bayesian evidence ratio NERFINISHED
appliedIn biostatistics
econometrics
machine learning
physics
psychology
approximatedBy BIC difference
compares two hypotheses
two statistical models
computedBy Laplace approximation NERFINISHED
Monte Carlo methods
bridge sampling
reversible jump MCMC
contrastsWith frequentist hypothesis tests
p-values
definedAs ratio of marginal likelihoods of two models
dependsOn likelihood function
prior distributions
domain statistical inference
hasFormula B_10 = p(y | M_1) / p(y | M_0)
hasProperty can accumulate evidence for the null model
can be computed analytically in simple models
often requires numerical integration
penalizes model complexity via marginalization
sensitive to prior specification
interpretedAs how much data update prior odds to posterior odds
interpretedUsing Jeffreys scale NERFINISHED
Kass and Raftery scale NERFINISHED
introducedBy Harold Jeffreys NERFINISHED
invariantUnder reparameterization of model parameters
measures strength of evidence in data for one model over another
quantifies relative evidence from data
relatedTo Bayesian Information Criterion NERFINISHED
marginal likelihood
posterior odds
prior odds
symbol B_10
K
usedFor hypothesis testing
model comparison
usedIn Bayesian statistics NERFINISHED
usedTo assess evidence for alternative hypothesis
assess evidence for null hypothesis
select between nested models
select between non-nested models

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Bayesian Occam factor relatedTo Bayes factor