Bayesian Statistics 9

Front Cover
JosÚ M. Bernardo, M. J. Bayarri, James O. Berger
OUP Oxford, Oct 6, 2011 - Mathematics - 706 pages
0 Reviews
The Valencia International Meetings on Bayesian Statistics - established in 1979 and held every four years - have been the forum for a definitive overview of current concerns and activities in Bayesian statistics. These are the edited Proceedings of the Ninth meeting, and contain the invited papers each followed by their discussion and a rejoinder by the authors(s). In the tradition of the earlier editions, this encompasses an enormous range of theoretical and applied research, high lighting the breadth, vitality and impact of Bayesian thinking in interdisciplinary research across many fields as well as the corresponding growth and vitality of core theory and methodology. The Valencia 9 invited papers cover a broad range of topics, including foundational and core theoretical issues in statistics, the continued development of new and refined computational methods for complex Bayesian modelling, substantive applications of flexible Bayesian modelling, and new developments in the theory and methodology of graphical modelling. They also describe advances in methodology for specific applied fields, including financial econometrics and portfolio decision making, public policy applications for drug surveillance, studies in the physical and environmental sciences, astronomy and astrophysics, climate change studies, molecular biosciences, statistical genetics or stochastic dynamic networks in systems biology.

What people are saying - Write a review

We haven't found any reviews in the usual places.


Integrated Objective Bayesian Estimation and Hypothesis Testing
A Structured Factor Model Framework
Free Energy Sequential Monte Carlo Application to Mixture Modelling
Moment Priors for Bayesian Model Choice with Applications to Directed Acyclic Graphs
Nonparametric Bayes Regression and Classification Through Mixtures of Product Kernels
Bayesian Variable Selection for Random Intercept Modelling of Gaussian and NonGaussian Data
External Bayesian Analysis for Computer Simulators
Optimization Under Unknown Constraints
Association Tests that Accommodate Genotyping Uncertainty
Bayesian Methods in Pharmacovigilance
Approximating MaxSumProduct Problems using Multiplicative Error Bounds
A Holy Grail or an Achilles Heel?
Sparse Bayesian Regularization and Prediction
Bayesian Models for Sparse Regression Analysis of High Dimensional Data
Transparent Parametrizations of Models for Potential Outcomes
Modelling Multivariate Counts Varying Continuously in Space

Using TPA for Bayesian Inference
Nonparametric Bayesian Networks
Particle Learning for Sequential Bayesian Computation
Bayesian Exploration of the Pulsating Sky
Characterizing Uncertainty of Future Climate Change Projections using Hierarchical Bayesian Models
Bayesian Models for Variable Selection that Incorporate Biological Information
A Bayesian Approach to Systems Biology

Other editions - View all

Common terms and phrases

About the author (2011)

M. J. Bayarri is Professor of Statistics at Universitat de Valencia. J. M. Bernardo is Professor of Statistics at Universitat de Valencia. James O. Berger is the Arts and Sciences Professor of Statistics at Duke University. A. P. Dawid is Professor of Statistics at the University ofCambridge. David Heckerman is the Senior Director of the Science Research Group for Microsoft. Sir Adrian F M Smith is the Director General of Science and Research at the UK Department of Business, Innovation and Skills. Mike West is the Arts and Sciences Professor of Statistical Science at DukeUniversity.

Bibliographic information