Bayesian statistics 9. Bernardo, José M. Bernardo, M.J. Bayarri and J.O. Berger (Book, 2011) [WorldCat.org]
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Bayesian statistics 9. Bernardo, José M. Bernardo, M.J. Bayarri and J.O. Berger

Author: Valencia International Meeting on Bayesian Statistics (9th)
Publisher: Oxford : Oxford University Press, 2011.
Edition/Format:   Print book : English
Summary:

Bayesian Statistics 9 covers the latest and last of the Valencia International Meetings on Bayesian Statistics. These proceedings include twenty-three edited and refereed paper followed by extensive  Read more...

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Document Type: Book
All Authors / Contributors: Valencia International Meeting on Bayesian Statistics (9th)
ISBN: 0199694583 9780199694587
OCLC Number: 789031144
Description: 712 pages : illustrations ; 24 cm
Contents: 1. Integrated Objective Bayesian Estimation and Hypothesis Testing ; 2. Dynamic Stock Selection Strategies: A Structured Factor Model Framework ; 3. Free Energy Sequential Monte Carlo, Application to Mixture Modelling ; 4. Moment Priors for Bayesian Model Choice with Applications to Directed Acyclic Graphs ; 5. Nonparametric Bayes Regression and Classification Through Mixtures of Product Kernels ; 6. Bayesian Variable Selection for Random Intercept Modeling of Gaussian and non-Gaussian Data. ; 7. External Bayesian Analysis for Computer Simulators ; 8. Optimization Under Unknown Constraints ; 9. Using TPA for Bayesian Inference ; 10. Nonparametric Bayesian Networks ; 11. Particle Learning for Sequential Bayesian Computation ; 12. Rotating Stars and Revolving Planets: Bayesian Exploration of the Pulsating Sky ; 13. Association Tests that Accommodate Genotyping Uncertainty ; 14. Bayesian Methods in Pharmacovigilance ; 15. Approximating Max-Sum-Product Problems using Multiplicative Error Bounds ; 16. What's the H in H-likelihood: A Holy Grail or an Achilles' Heel? ; 17. Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction ; 18. Bayesian Models for Sparse Regression Analysis of High Dimensional Data ; 19. Transparent Parametrizations of Models for Potential Outcomes ; 20. Modelling Multivariate Counts Varying Continuously in Space ; 21. Characterizing Uncertainty of Future Climate Change Projections using Hierarchical Bayesian Models ; 22. Bayesian Models for Variable Selection that Incorporate Biological Information ; 23. Parameter Inference for Stochastic Kinetic Models of Bacterial Gene Regulation: A Bayesian Approach to Systems Biology
Responsibility: editors, José M. Bernardo, M.J. Bayarri and J.O. Berger.

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Review from previous edition Review from previous edition ... this book presents a uniquely excellent overview of some of the most relevant and pressing current issues underlying research in Bayesian Read more...

 
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