Changes

In [[Bayesian Probability]], '''Bayesian model selection''' is a method for choosing the best [[hypothesis]] (model) out of a set of competing models which best explains some observed data. Best here is measured by the [[Bayesian posterior odds]] ratio of the winner compared against all other candidates in the competition.  The '''posterior odds ratio''' is the product of the [[Bayes Factor]] and the [[Bayes prior]] odds ratio.

In [[Bayesian Probability]], '''Bayesian model selection''' is a method for choosing the best [[hypothesis]] posed as a [[probabilistic likelihood model]] out of a set of competing models which best explains some observed data. Best here is measured by the [[Bayesian posterior odds]] ratio of the winner compared against all other candidates in the competition.  The '''posterior odds ratio''' is the product of the [[Bayes Factor]] and the [[Bayes prior]] odds ratio.

[[category:Probability]]

[[category:Probability]]