Titlebook: Case Studies in Bayesian Statistics; Volume V Constantine Gatsonis,Robert E. Kass,Mike West Conference proceedings 2002 Springer Science+Bu

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Hidden Markov Models for Analysis of Biological Rhythm Datasinor approaches sufficiently account for the net result of periodic secretion and an appropriate elimination mechanism. This pa-per discusses methods for data analysis that achieve improved modeling. The underlying biological rhythm for a group of subjects is modeled as periodically varying transit

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Conference proceedings 2002an Imperfect Randomized Experiment J. Barnard, C. Frangakis, J. Hill, and D. Rubin report on the analysis of the data from a randomized study conducted to evaluate the New YorkSchool Choice Scholarship Pro- gram. The focus ofthe paper is on Bayesian methods for addressing the analytic challenges pos

Onerous

School Choice in NY City: A Bayesian Analysis of an Imperfect Randomized Experimentplemented) and the rigorous data collection and compliance-encouraging efforts. In fact, this study benefits from the authors’ previous experiences with the analysis of data from the Milwaukee Parental Choice Program, which, although randomized, was relatively poorly implemented as an experiment..At

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Bayesian Protein Structure Predictionion based on non-local sequence interactions. We demonstrate this idea by presenting a simple model for .-strand pairing and a Markov chain Monte Carlo (MCMC) algorithm for inference. We apply the approach to prediction of 3-dimensional contacts for two example proteins.