先验概率

Multi tool use在贝叶斯统计中,某一不确定量p的先验概率分布是在考虑"观测数据"前,能表达p不确定性的概率分布。它旨在描述这个不确定量的不确定程度,而不是这个不确定量的随机性。这个不确定量可以是一个参数,或者是一个隐含变量(英语:latent variable)。
在使用贝叶斯定理时,我们通过将先验概率与似然函数相乘,随后标准化,来得到后验概率分布,也就是给出某数据,该不确定量的条件分布。
先验概率通常是主观的猜测,为了使计算后验概率方便,有时候会选择共轭先验。如果后验概率和先验概率是同一族的,则认为它们是共轭分布,这个先验概率就是对应于似然函数的共轭先验。
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