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...

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Detalles Bibliográficos
Autores principales: Daniels, M. J. (Michael Joseph) (Autor), Linero, Antonio (Autor), Roy, Jason (Jason Allen) (Autor)
Formato: Libro
Lenguaje:English
Publicado: Boca Raton, FL CRC Press, an imprint of Taylor & Francis Group, LLC 2024.
Colección:Chapman & Hall/CRC monographs on statistics & applied probability 173
Materias:
Bayesian statistical decision theory.
Missing observations (Statistics)