Bayesian Nonparametrics for Causal Inference and Missing Data

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Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian Nonparametrics for Causal Inference and Missing Data

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Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian nonparametric (BNP) methods can be used to flexibly model joint or conditional distributions as well as functional relationships. These methods along with causal and/or missingness assumptions can be used with the g-formula to infer causal effects.
  • 品牌: Taylor & Francis Ltd
  • 类别: 教育
  • 语言: English
  • 作者: Michael J. Daniels
  • 出版日期: 2023-08-24
  • 页数: 248
  • 出版社/标签: Taylor & Francis Ltd
  • 格式: Hardback
  • Fruugo ID: 343439514-752535515
  • ISBN: 9780367341008

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