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Bayesian Nonparametrics for Causal Inference and Missing Data|Michael J. Daniels

Bayesian Nonparametrics for Causal Inference and Missing Data

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Overview

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.

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Details

  • ISBN-13: 9780367341008
  • ISBN-10: 036734100X
  • Publisher: CRC Press
  • Publish Date: August 2023
  • Dimensions: 9.21 x 6.14 x 0.63 inches
  • Shipping Weight: 1.2 pounds
  • Page Count: 248

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