Chapman And Hall/Crc
Bayesian Nonparametrics For Causal Inference And Missing Data (Chapman & Hall/Crc Monographs On Statistics And Applied Probability)
Bayesian Nonparametrics For Causal Inference And Missing Data (Chapman & Hall/Crc Monographs On Statistics And Applied Probability)
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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.
- | Author: Michael J. Daniels, Antonio Linero, Jason Roy
- | Publisher: Chapman And Hall/Crc
- | Publication Date: Aug 23, 2023
- | Number of Pages: 262 pages
- | Language: English
- | Binding: Hardcover
- | ISBN-10: 036734100X
- | ISBN-13: 9780367341008
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