Bayesian Statistics 9 /
Bernardo, Jose M., ed.
Bayesian Statistics 9 / Edited by Jose M. Bernardo, M.J. Bayarri and J.O. Berger - USA: Oxford University Press, 2011. - 706 p.
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
0199694583
519.542 / BER/B
Bayesian Statistics 9 / Edited by Jose M. Bernardo, M.J. Bayarri and J.O. Berger - USA: Oxford University Press, 2011. - 706 p.
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
0199694583
519.542 / BER/B