Bayesian nonparametrics for causal inference and missing data

Bayesian nonparametrics for causal inference and missing data

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the impor...

Full description

Bibliographic Details
Main Authors: Daniels, M. J. (Michael Joseph) (Author), Linero, Antonio (Author), Roy, Jason (Jason Allen) (Author)
Format: Book
Language:English
Published: Boca Raton, FL CRC Press, an imprint of Taylor & Francis Group, LLC 2024.
Series:Chapman & Hall/CRC monographs on statistics & applied probability 173
Subjects:
Bayesian statistical decision theory.
Missing observations (Statistics)