Bayesian Statistics 6: Proceedings of the Sixth Valencia International Meeting (eng)

Bernardo, J. M.

ISBN 10: 0198504853 / ISBN 13: 9780198504856

Editore: Clarendon Press, 1999

Riguardo questo articolo

Questo è un articolo print on demand.

Codice articolo e0c533dd9e16c353866f230b7caa8ac1

Dati bibliografici

• Titolo: Bayesian Statistics 6: Proceedings of the Sixth Valencia International Meeting (eng)
• Editore: Clarendon Press
• Data di pubblicazione: 1999
• Lingua: Inglese
• ISBN 10: 0198504853
• ISBN 13: 9780198504856
• Rilegatura: Rilegato
• Condizione: new
• Peso: 1,45 chilogrammi

Descrizione articolo

Riassunto

The Valencia International Meetings on Bayesian Statistics, held every four years, provide the main forum for researchers in the area to come together to present and discuss frontier developments in the field. The resulting Proceedings provide a definitive, up-to-date overview encompassing a wide range of theoretical and applied research. This sixth Proceedings is no exception, and will be an indispensable reference to all statisticians.

Contenuti

• 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