Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data

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 PIM

Paul Gustafson is a professor in the Department of Statistics at the University of British Columbia. He is the statistics editor for Epidemiology as well as an associate editor for the Journal of the American Statistical Association (Applications and Case Studies Section) and Statistics in Medicine. His current research focuses on identification issues in Bayesian analysis.