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单词 Bayesian theorem
释义

Bayesian theorem

英语百科

Bayes' rule

In probability theory and applications, Bayes's rule relates the odds of event A_1 to the odds of event A_2, before (prior to) and after (posterior to) conditioning on another event B. The odds on A_1 to event A_2 is simply the ratio of the probabilities of the two events. The prior odds is the ratio of the unconditional or prior probabilities, the posterior odds is the ratio of conditional or posterior probabilities given the event B. The relationship is expressed in terms of the likelihood ratio or Bayes factor, \Lambda. By definition, this is the ratio of the conditional probabilities of the event B given that A_1 is the case or that A_2 is the case, respectively. The rule simply states: posterior odds equals prior odds times Bayes factor (Gelman et al., 2005, Chapter 1).

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更新时间:2025/6/22 8:55:32