Bayesian Nonparametrics For Causal Inference And Missing Data (Chapman & Hall/Crc Monographs On Statistics And Applied Probability)

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