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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

It seems as if Bayesian statistics are everywhere these days, and having been trained strictly in the frequentist school it can be difficult to make a start with actually using these statistics in everyday work. This book is an intermediate treatment of Bayesian models of many different kinds with an admirable focus on actually using the models in applied situations. Models for data with spatial and temporal correlation are covered, as well as multilevel, SEM, and survival models. There is a very practical focus to the book, with real examples throughout as well as WinBUGS code for each application. Also commendable is the focus on model fit and checking, with a dedicated chapter as well as material throughout relating to model assumptions and techniques for use where standard assumptions are not met.
机译:如今,似乎贝叶斯统计数据无处不在,并且经过在频频教育学校的严格培训,很难在日常工作中真正使用这些统计数据。本书是对许多不同类型的贝叶斯模型的中间处理,令人钦佩的是侧重于在实际情况下实际使用模型。涵盖了具有时空相关性的数据模型以及多层,SEM和生存模型。这本书非常注重实践,提供了完整的实际示例以及每个应用程序的WinBUGS代码。同样值得称赞的是,它着重于模型拟合和检查,并有专门的章节以及与模型假设和不符合标准假设的使用技术有关的材料。

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  • 来源
    《Journal of applied statistics》 |2012年第8期|p.1845|共1页
  • 作者

    Chris Beeley;

  • 作者单位

    Institute of Mental Health, Nottingham, UK;

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  • 原文格式 PDF
  • 正文语种 eng
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