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Applied Bayesian hierarchical methods

机译:应用贝叶斯分层方法

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摘要

The Bayesian approach to model and interpret data is quite natural and intuitive. At any given time, the knowledge is not complete by any means but is in a progressive path. New data arrive with additional information. When the additional information brings in new aspects, then the prior knowledge is updated to a new level. When the additional information is just a redundancy, the prior knowledge is validated with higher precision. This idea is the central theme of the Bayesian, and hence the Bayesian is more practical. The Bayesian approach is appreciated and applied in all professional and personal life. The following three books are excellent sources for learning or applying them.
机译:贝叶斯建模和解释数据的方法是非常自然和直观的。在任何给定时间,知识都不会以任何方式完成,而是会逐步发展。新数据会附带其他信息。当附加信息带来新的方面时,现有知识将被更新到一个新的水平。当附加信息只是冗余时,将以更高的精度验证先验知识。这个想法是贝叶斯理论的中心主题,因此贝叶斯理论更为实用。贝叶斯方法受到赞赏并应用于所有职业和个人生活。以下三本书是学习或应用它们的绝佳资源。

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