Bayesian Statistics 5: Proceedings of the Fifth Valencia International Meeting, June 5-9, 1994 - Rilegato

Rilegato

ISBN 10: 0198523564 ISBN 13: 9780198523567

Casa editrice: OUP Oxford, 1996

Riassunto

The Valencia International Meetings on Bayesian Statistics, held every four years, provide the forum for researchers to come together 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 fifth Proceedings is no exception. In particular, it reflects a growing emphasis on computational issues, concerned with making Bayesian methods routinely available to applied practitioners, both statisticians and speciailists in other subject-matter, whose work depends on careful quantification of uncertainties. This book contains several invited papers by leading authorities.

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Recensione

In the preface, the editors say that they believe that "the Proceedings provide a definitive, up-to-date overview of current concerns and activity in Bayesian statistics, encompassing a wide range of theoretical and applied research." I concur with their belief, and I eagerly await publication of the proceedings of the next Valencia meeting. (The Statistician (1998), vol. 47, issue 2)

The range of topics is impressive. The excellent reputation of the conference, its proceedings and the subsequent contributions of this volume are presentative of the "state of the art" in the Bayesian world. (Metrika)

Contenuti

• Invited Papers (with discussion)
• C. Armero and M.J. Bayarri: Bayesian Questions and Answers in Queues
• J.O. Berger and L.R. Pericchi: The Intrinsic Bayes Factor for Linear Models
• D.A. Berry, A. Thor, C. Cirrincione, S. Edgerton, H. Muss, J. Marks E. Liu, W. Budman D. Wood, M. Perloof, W. Peters and I.C. Henderson: Scientific Inference and Predictions: Multiplicities and Convincing Stories: A Case Study in Breast Cancer Therapy
• P.S. Craig, M. Goldstein, A. H. Seheult, and J.A. Smith: Bayes Linear Strategies for Matching Hydrocarbon Reservoir History
• P. Diaconis and J. Kemperman: Some New Tools for Dirichlet Priors
• W. DuMouchel: Predictive Cross-Validation of Bayesian Meta-Analyses
• S.E. Fienberg and M.O. Finkelstein: Bayesian Statistics and the Law
• S. French: The Framing of Statistical Decision Theory: A Decision Analytic View
• A.E. Gelfand, S.K. Sahu and B.P. Carlin: Efficient Parametrizations for Generalized Linear Mixed Models
• E.J. Green, A.F.M. Smith and W.E. Strawderman: Construction of Thematic Maps from Satellite Imagery
• Local Sensitivity Analysis
• J.A. Hartigan: Bayesian Histograms
• N.L. Hjort: Bayesian Approaches to Non- and Semiparametric Density Estimation
• K.L. Mengersen and C.P. Robert: Testing for Mixtures: A Bayesian Entropic Approach
• C.N. Morris and C.L. Christiansen: Hierarchical Models for Ranking and for Identifying Extremes, with Applications
• N.G. Polson: Convergence of Markov Chain MonteCarlo Algorithms
• A.E. Raftery, D. Madigan and C.T. Volinsky: Accounting for Model Uncertainty in Survival Analysis Improves Predictive Performance
• N. Reid: Likelihood and Bayesian Approximation Methods
• N.D. Singpurwalla, S.P. Wilson and E.R. Fuller: Statistical Aspects of Failure Processes in Ceramics
• J.Q. Smith: Plausible Bayesian Games
• D.J. Spieghalter, A. Thomas and N.G. Best: Computation on Bayesian Graphical Models
• T.J. Sweeting: Approximate Bayesian Computation Based on Signed Roots of Log-Density Ratios
• A. Tversky and D.J. Koehler: Support Theory: A Nonextensional Representation of Probability Judgment
• M. West: Some Statistical Issues in Palaeoclimatology
• Contributed Papers
• A. Andreev and E. Arjas: A note on Histogram Approximation in Bayesian Density Estimation
• C. Bielza, D. Rios-Insua and S. Rios-Insua: Influence Diagrams under Partial Information
• C.E. Buck and C.D. Litton: Mixtures, Bayes and Archaeology
• C. Carota and G. Parmigiani: On Bayes Factors for Nonparametric Alternatives
• J.L. Cervera and J. Munoz: Proper Scoring Rules for Fractiles
• Z. Covaliu: Sequential Diagrams and Influence Diagrams: A Complementary Relationship for Modeling and Solving Decision Problems
• R.G. Cowell, A.P. Dawid and P. Sebastiani: A comparison of Sequential Learning Methods for Incomplete Data
• J. Dmochowski: Intrinsic Priors via Kullback-Leibler Geometry
• A.E. Faria and J.W. Smith: Conditional External Bayesianity in Decomposable Influence Diagrams
• M. Farrow and M. Goldstein: Diagnostic Geometry for Bayes Linear Prediction Systems
• D. Fourdrinier and M.T. Wells: Spherically Symmetric Bayes Estimators for a Linear Subspace of a Normal Law
• D. Gamerman and A.F.m. Smith: Bayesian Analysis of Longitudinal Data Studies
• A. Gelman, G.O. Roberts and W.R. Gilks: Efficient Metropolis Jumping Rules
• J. Geweke: Variable Selection and Model Comparison in Regression
• P. Giudici: Learning in Graphical Gaussian Models
• R.G. haylock and A. O;Hagan: On Inference for Outputs of Computationally Expensive Algorithms with Uncertainty on the Inputs
• M.C. Kennedy and A. O'Hagan: Iterative Rescaling for Bayesian Quadrature
• G.E. Kokolakis and P. Dellaportas: Hierarchical Modelling for Classifying Binary Data
• D.J. Laws, R.J. Boys and K.D. Glazebrook: A Bayes Decision-Theoretic Approach to Dimensionality Reduction in Screen Design
• B. Liseo, L. Petrella and G. Salinetti: Robust Bayesian Analysis: An Interactive Approach
• T.A. Mazzuchi and R. Soyer: Adaptive Bayesian Replacement Strategies
• N.J. McMillan and L.M. Berliner: Hierarchical Image Reconstruction Using Markov Randop Fields
• P.M. Meehan, A.P. Dempster and E.N. Brown: A Belief Function Approach to Likelihood Updating in a Gaussian Linear Model
• A. Mira and S. Petrone: Bayesian Hierarchical Nonparametric Inference for Change-Point Problems
• J.C. Naylos and J.M. Marriot: A Bayesian Analysis of Non-Stationary AR Series
• J. Nunez and J. Llacer: A Bayesian Algorithm for Image Reconstruction with Variable Hyperparameter
• D.B. Phillips and A.F.M. Smith: Stochastic Deformable Temnplates and Object Tracking
• D.J. Poirier: Prior Beliefs About Fit
• J.F. Shortle and M.B. Mendel: The Geometry of Bayesian Inference
• M.P. Upsdell: Choosing an Appropriate Covariance Function in Bayesian Smoothing
• J.A. Varshavsky: Intrinsic Bayes Factors for Model Selection with Autoregressive Data
• I. Verdinelli and L. Wasserman: Bayes Factors, Nuisance Parameters and Imprecise Tests
• P. Vounatsou and A.F.M. Smith: Graphical Methods for Simulation-Based Bayesian Inference
• S. Walker and J. Wakefield: Bayesian Approaches to the Population Modelling of a Monotonic Dose-Response Relation
• D.J. Wilkinson and M. Goldstein: Bayes Linear Adjustment for Variance Matrices
• A.G. Wilson and V.E. Johnson: Models for Shape Deformation
• M.P. Wiper and L.I. Pettit: On Improving a Model for Combining Experts' Forecasts

Dettagli dell'edizione

• Editore: OUP Oxford
• Data di pubblicazione: 1996
• Lingua: Inglese
• ISBN 10: 0198523564
• ISBN 13: 9780198523567
• Rilegatura: Copertina rigida
• Numero di pagine: 826
• Redattore: Bernardo J. M., Berger J. O., Dawid A. P., Smith A. F. M.
• Contatto del produttore: Oxford University Press; https://corp.oup.com/; ; WMF Platz 1; Geislingen/Steige; Baden-W?rttemberg; 73312; Germania