Bayesian methodology
In general, Bayesian methods are characterized by the following concepts and procedures:1)The use of hierarchical models and marginalization over the values of nuisance parameters. In most cases, the computation is intractable, but good approximations can be obtained using Markov chain Monte Carlo methods.
2)The sequential use of the Bayes' formula: when more data become available after calculating a posterior distribution, the posterior becomes the next prior.
3) For the frequentist a hypothesis is a proposition (which must be either true or false), so that the frequentist probability of a hypothesis is either one or zero. In Bayesian statistics, a probability can be assigned to a hypothesis that can differ from 0 or 1 if the truth value is uncertain.
http://en.wikipedia.org/wiki/Bayesian_probability 豆瓣有人问过同样的问题：
http://www.douban.com/group/topic/16951058/
http://www.quora.com/What-is-the-difference-between-Bayesian-and-frequentist-statisticians 不存在所谓的客观概率，
我只接受主观概率这个概念。
信息学里的熵这个概念却用经典概率来定义...
跟牛顿力学的质量和力一样 互相定义。 不存在所谓的客观概率，
我只接受主观概率这个概念。
信息学里的熵这个概念却用经典概率来定义...
跟牛顿力学的质量和力一样 互相定义。
wayne 发表于 2013-3-6 16:32 http://bbs.emath.ac.cn/images/common/back.gif
牛顿力学的质量还有个重力质量和惯性质量的区别。相对论直接把2者等价了，当然是基于实验结果的。