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.

Author: Michael J. Daniels, Antonio Linero, Jason Roy
Binding Type: Hardcover
Publisher: CRC Press
Published: 08/23/2023
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Prob
Pages: 248
Weight: 1.2lbs
Size: 9.21h x 6.14w x 0.63d
ISBN: 9780367341008