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Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data
Hardcover
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Prob
Medical ReferenceProbability & Statistics
ISBN13: 9781439869390
Publisher: CRC Press
Published: Apr 1 2015
Pages: 196
Weight: 0.90
Height: 0.60 Width: 6.20 Depth: 9.20
Language: English
This book shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. He covers a range of PIMs, including models for misclassified data and models involving instrumental variables. He also includes real data applications of PIMs that have recently appeared in the literature.
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