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Bayesian Statistics 5: Proceedings of the Fifth Valencia International Meeting, June 5-9, 1994 [Kõva köide]

Edited by (Professor of Statistics, Department of M), Edited by (Professor of Statistics, Department of Decision Analysis, Generalidad Valenciana, Spain), Edited by (Professor of Statistics, University College of London), Edited by (Professor of Statistics, Purdue University)
  • Formaat: Hardback, 826 pages, kõrgus x laius x paksus: 241x162x45 mm, kaal: 1195 g, line figures, tables
  • Ilmumisaeg: 09-May-1996
  • Kirjastus: Oxford University Press
  • ISBN-10: 0198523564
  • ISBN-13: 9780198523567
Teised raamatud teemal:
Bayesian Statistics 5: Proceedings of the Fifth Valencia International Meeting, June 5-9, 1994Suurem pilt
  • Formaat: Hardback, 826 pages, kõrgus x laius x paksus: 241x162x45 mm, kaal: 1195 g, line figures, tables
  • Ilmumisaeg: 09-May-1996
  • Kirjastus: Oxford University Press
  • ISBN-10: 0198523564
  • ISBN-13: 9780198523567
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780198523567.html
Märksõnad:
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.

Arvustused

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 *

Invited Papers (with discussion) ; Bayesian Questions and Answers in
Queues ; The Intrinsic Bayes Factor for Linear Models ; Scientific Inference
and Predictions: Multiplicities and Convincing Stories: A Case Study in
Breast Cancer Therapy ; Bayes Linear Strategies for Matching Hydrocarbon
Reservoir History ; Some New Tools for Dirichlet Priors ; Predictive
Cross-Validation of Bayesian Meta-Analyses ; Bayesian Statistics and the Law
; The Framing of Statistical Decision Theory: A Decision Analytic View ;
Efficient Parametrizations for Generalized Linear Mixed Models ; Construction
of Thematic Maps from Satellite Imagery ; Local Sensitivity Analysis ;
Bayesian Histograms ; Bayesian Approaches to Non- and Semiparametric Density
Estimation ; Testing for Mixtures: A Bayesian Entropic Approach ;
Hierarchical Models for Ranking and for Identifying Extremes, with
Applications ; Convergence of Markov Chain MonteCarlo Algorithms ; Accounting
for Model Uncertainty in Survival Analysis Improves Predictive Performance ;
Likelihood and Bayesian Approximation Methods ; Statistical Aspects of
Failure Processes in Ceramics ; Plausible Bayesian Games ; Computation on
Bayesian Graphical Models ; Approximate Bayesian Computation Based on Signed
Roots of Log-Density Ratios ; Support Theory: A Nonextensional Representation
of Probability Judgment ; Some Statistical Issues in Palaeoclimatology ;
Contributed Papers ; A note on Histogram Approximation in Bayesian Density
Estimation ; Influence Diagrams under Partial Information ; Mixtures, Bayes
and Archaeology ; On Bayes Factors for Nonparametric Alternatives ; Proper
Scoring Rules for Fractiles ; Sequential Diagrams and Influence Diagrams: A
Complementary Relationship for Modeling and Solving Decision Problems ; A
comparison of Sequential Learning Methods for Incomplete Data ; Intrinsic
Priors via Kullback-Leibler Geometry ; Conditional External Bayesianity in
Decomposable Influence Diagrams ; Diagnostic Geometry for Bayes Linear
Prediction Systems ; Spherically Symmetric Bayes Estimators for a Linear
Subspace of a Normal Law ; Bayesian Analysis of Longitudinal Data Studies ;
Efficient Metropolis Jumping Rules ; Variable Selection and Model Comparison
in Regression ; Learning in Graphical Gaussian Models ; On Inference for
Outputs of Computationally Expensive Algorithms with Uncertainty on the
Inputs ; Iterative Rescaling for Bayesian Quadrature ; Hierarchical Modelling
for Classifying Binary Data ; A Bayes Decision-Theoretic Approach to
Dimensionality Reduction in Screen Design ; Robust Bayesian Analysis: An
Interactive Approach ; Adaptive Bayesian Replacement Strategies ;
Hierarchical Image Reconstruction Using Markov Randop Fields ; A Belief
Function Approach to Likelihood Updating in a Gaussian Linear Model ;
Bayesian Hierarchical Nonparametric Inference for Change-Point Problems ; A
Bayesian Analysis of Non-Stationary AR Series ; A Bayesian Algorithm for
Image Reconstruction with Variable Hyperparameter ; Stochastic Deformable
Temnplates and Object Tracking ; Prior Beliefs About Fit ; The Geometry of
Bayesian Inference ; Choosing an Appropriate Covariance Function in Bayesian
Smoothing ; Intrinsic Bayes Factors for Model Selection with Autoregressive
Data ; Bayes Factors, Nuisance Parameters and Imprecise Tests ; Graphical
Methods for Simulation-Based Bayesian Inference ; Bayesian Approaches to the
Population Modelling of a Monotonic Dose-Response Relation ; Bayes Linear
Adjustment for Variance Matrices ; Models for Shape Deformation ; On
Improving a Model for Combining Experts' Forecasts