Bayesian Statistics 6

• A definitive, up-to-date overview
• Encompasses a wide range of theoretical and applied research
• An indispensable reference for researchers in statistics

Readership: Graduate students and researchers in statistics. Researchers in related areas of engineering, AI, economics, medicine.

Edited by José M. Bernardo, Professor of Statistics, Universitat de Valencia, Spain, James O. Berger, Professor of Statistics, Duke University, USA, A. P. Dawid, Professor of Statistics, University College London, and Adrian F. M. Smith, Principal, Queen Mary and Westfield College, London

I. INVITED PAPERS (With discussion)
Bayesian Inference on Latent Structure in Time Series
Information Theory and the Risk of Bayes Procedures
Quantifying Surprise in the Data and Model Verification
Bayesian Methods in the Atmospheric Sciences
Nested Hypothesis Testing: The Bayesian Reference Criterion
Bayesian Models for Spatially Correlated Disease and Exposure Data
Bayesian Model Averaging and Model Search Strategies
Hierarchical Models for DNA Profiling Using Heterogeneous Databases
On the Dangers of Modelling Through Continuous Distributions: A Bayesian Perspective
Bayesian Methods in Signal and Image Processing
Functional Magnetic Resonance Imaging and Spatio-Temporal Inference
Simulation Methods for Model Criticism and Robustness Analysis
Exact Sampling for Bayesian Inference: Towards General Purpose Algorithms
Spatial Regression for Marked Point Processes
Bayesian Model Choice: What and Why?
Another Look at Conditionally Gaussian Markov Random Fields
Simulated Sintering: Markov Chain Monte Carlo With Spaces of Varying Dimensions
Markov Chain Monte Carlo Convergence Diagnostics: A Review
Issues in Service Quality Modelling
Simulation-Based Optimal Design
Regression and Classification Using Gaussian Process Priors
Uncertainy Analysis and other Inference Tools for Complex Computer Codes
Decision Models in Screening for Breast Cancer
Time-Varying Covariances: a Factor Stochastic Volatility Approach
Old and Recent Results on the Relationship Between Predictive Inference and Statistical Modelling either in Nonparametric or Parametric Form
Bayesian and Frequentist Approaches to Parametric Predictive Inference
Inference-Robust Institutional Comparisons: A Case Study of School Examination Results
Computationally Efficient Methods for Selecting Among Mixtures of Graphical Models
Spatial Dependence and Errors-in-Variables in Environmental Epidemiology
Robustifying Bayesian Procedures
II. CONTRIBUTED PAPERS
Pearson Type II Errors-in-Variables Models
Bayesian Analysis of Animal Abundance Data via MCMC
Convergence Assessment for Reversible Jump MCMC Simulations
Fixed-Lag Smoothing using Sequential Importance Sampling
The Nile Revisited: Changepoint Analysis with Autocorrelation
Non-Stationary Spatial Modelling
Bayesian Wavelet Analysis with a Model Complexity Prior
Bayesian Analysis of Cepheid Variable Data
A Bayesian Analysis of Stochastic Unit Root Models
Optimal Design for Quantal Bioassay via Monte Carlo Methods
Bayesian Estimation of a Location Parameter Using the Haar Basis
On the Different Structures of Posterior Distributions with Respect to the Prior Distribution
A Bayesian Proposal for the Analysis of Stationary and Nonstationary AR(1) Time Series
Bayes Sequential Decision Theory in Clinical Trials
Simplifying Complex Designs: Bayes Linear Experimental Design for Grouped Multivariate Exchangeable systems
Extremes of Mixed Environmental Processes
Graphical Diagnostics for the Bayes Linear Analysis of Hierarchical Linear Models with Applications to Educational Data