Bayesian Statistics 7: Proceedings of the Seventh Valencia International Meeting

Hardcover | October 28, 2003

EditorJose M. Bernardo, A. Philip Dawid, James O. Berger

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The Valencia International Meetings on Bayesian Statistics, held every four years, provide the main forum for researchers in the area of Bayesian Statistics to come together to present and discuss frontier developments in the field. The resulting Proceedings provide a definitive, up-to-dateoverview encompassing a wide range of theoretical and applied research. This seventh Proceedings containing 23 invited articles and 31 contributed papers is no exception, and will be an indispensable reference to all statisticians.

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The Valencia International Meetings on Bayesian Statistics, held every four years, provide the main forum for researchers in the area of Bayesian Statistics to come together to present and discuss frontier developments in the field. The resulting Proceedings provide a definitive, up-to-dateoverview encompassing a wide range of theoret...

Professor Jose M. Bernardo Professor of Statistics, Universidad de Valencia, Spain A. Philip Dawid Professor of Statistics, University College London, UK AWARDS: 2002 DeGroot Prize for a Published Book in Statistical Science (Cowell et al.) 2001 Royal Statistical Society: Guy Medal in Silver 1978 Royal Statistical Society: ...

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Format:HardcoverDimensions:764 pages, 9.21 × 6.14 × 1.72 inPublished:October 28, 2003Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198526156

ISBN - 13:9780198526155

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Table of Contents

Arellano-Valle, R. B., Iglesias, P. L. and Vidal I.: Bayesian Inference for Elliptical Linear Models: Conjugate Analysis and Model ComparisonBlei, D. M., Jordan, M. I. and Ng, A. Y.: Hierarchical Bayesian Models for Applications in Information RetrievalCarlin, B. P. and Banerjee, S.: Hierarchical Multivariate CAR Models for Spatio- Temporally Correlated Survival DataChib, S.: On Inferring Effects of Binary Treatments with Unobserved ConfoundersChipman, H. A., George, E. I. and McCulloch, R. E.: Bayesian Treed Generalized Linear ModelsDavy, M. and Godsill, S. J.: Bayesian Harmonic Models for Musical Signal AnalysisDobra, A., Fienberg, S. E. and Trottini, M.: Assessing the Risk of Disclosure of Confidential Categorical Data.Genovese, C. and Wasserman, L: Bayesian and Frequentist Multiple Testing . . . . . . . . 145Gutierrez-Pena, E. and Nieto-Barajas, L. E.: Nonparametric Inference for Mixed Poisson ProcessesHigdon, D., Lee, H. and Holloman, C. : Markov chain Monte Carlo-based approaches for inference in computationally intensive inverse problemsJohnson, V. E., Graves, T. L., Hamada, M. S. and Shane, C.: Reese A Hierarchical Model for Estimating the Reliability of Complex SystemsLauritzen, S. L.: Rasch Models with Exchangeable Rows and ColumnsLinde, A. Van Der and Osius, G.: Discrimination Based on an Odds Ratio ParameterizationLiu, J. S., Zhang, J. L., Palumbo, M. J. and Charles, E.: Lawrence Bayesian Clustering with Variable and Transformation SelectionsMengersen, K. L. and Robert, C. P.: Iid Sampling using Self-Avoiding Population Monte Carlo: The Pinball SamplerNewton, M. A., Yang H., Gorman, P., Tomlinson, I. and Roylance, R.: A Statistical Approach to Modeling Genomic Aberrations in Cancer CellsPapaspiliopoulos, O., Roberts, G. O. and Skold, M.: Non-Centered Parameterisations for Hierarchical Models and Data AugmentationPena, D., Rodriguez, J. and Tiao, G. C.: Identifying Mixtures of Regression Equations by the SAR procedureQuintana, J. M., Lourdes V., Aguilar, O. and Liu, J.: Global GamblingSalinetti, G.: New Tools for Consistency in Bayesian NonparametricsSchervish, M. J., Seidenfeld T. and Kadane, J. B.: Measures of Incoherence: How not to Gamble if you MustWolpert, R. L., Ickstadt, K. and Hansen, M. B.: A Nonparametric Bayesian Approach to Inverse ProblemsZohar, R. and Geiger, D.: A Novel Framework for Tracking Groups of ObjectsII. CONTRIBUTED PAPERSAusin, M. C., Lillo, R. E., Ruggeri, F. and Wiper, M. P. : Bayesian Modeling of Hospital Bed Occupancy Times using a Mixed Generalized Erlang DistributionBeal, M. J. and Ghahramani, Z.: The Variational Bayesian EM Algorithm for Incomplete Data: With Application to Scoring Graphical Model StructuresBernardo, J. M. and Juarez, M. A.: Intrinsic EstimationChoy S. T. B., Chan J. S. K. and YamH. K.: Robust Analysis of Salamander Data, Generalized Linear Model with Random EffectsDaneshkhah, A. and Smith, Jim Q.: A Relationship Between Randomised Manipulation and Parameter IndependenceDethlefsen, C.: Markov Random Field Extensions using State Space ModelsErosheva, E. A.: Bayesian Estimation of the Grade of Membership ModelEsteves, L. G., Wechsler, S., Iglesias, P. L. and Pereira, A. L.: A Variant Version of the Polya-Eggenberger Urn ModelFerreira, A. R., West, M., Lee, H. K. H., Higdon, D. and Bi, Z.: Multi-scale Modelling of 1-D Permeability FieldsFraser, D. A. S., Reid, N., Wong, A. and Yi, G. Y.: Direct Bayes for Interest ParametersGarside, L. M. and Wilkinson, D. J.: Dynamic Lattice-Markov Spatio-Temporal Models for Environmental DataGebousk'y, P., Karn'y, M. and Quinn, A.: Lymphoscintigraphy of Upper Limbs: A Bayesian FrameworkGiron, F. J., Martinez, M. L., Moreno, E. and Torres, F.: Bayesian Analysis of Matched Pairs in the Presence of CovariatesJamieson, L. E. and Brooks, S. P.: State Space Models for Density Dependence in Population EcologyLavine, M.: A Marginal Ergodic TheoremLefebvre, T., Gadeyne, K., Bruyninckx, H. and Schutter, J. D.: Exact Bayesian Inference for a Class of Nonlinear Systems with Application to Robotic AssemblyLeucari, V. and Consonni, G.: Compatible Priors for Causal Bayesian NetworksMertens, B. J. A.: On the Application of Logistic Regression Modeling in Microarray StudiesNeal, R. M.: Dens ity Modeling and Clustering Using Dirichlet Diffusion TreesPettit, L. I. and Sugden, R. A.: Outl ier Robust Estimation of a Finite Population TotalPolson, N. G. and Stroud, J. R.: Bayesian Inference f or Derivative PricesRasmussen, C. E.: Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian IntegralsRodriguez, A., Alvarez, G. and Sanso, B.: Objective Bayesian Comparison of Laplace Samples from Geophysical DataScott, S. L. and Smyth, P.: The Markov Modulated Poisson Process and Markov Poisson Cascade with Applications to Web Traffic ModelingSmith, E. L. and Walshaw, D.: Modelling Bivariate Extremes in a RegionVehtari, and Lampinen, J.: Expected Utility Estimation via Cross-ValidationVirto, M., Martin, J., Rios-Insua, D. and Moreno-Diaz, A.: A Method for Sequential Optimization in Bayesian AnalysisWakefield, J. C., Zhou, C. and Self, S. G.: Modelling Gene Expression Data over Time: Curve Clustering with Informative Prior DistributionsWest, M: Bayesian Factor Regression Models in the Large p, Small n ParadigmZheng, P. and Marriott, J. M.: A Bayesian Analysis of Smooth Transitions in TrendTamminen, T. and Lampinen. J: Bayesian Object Matching with Hierarchical Priors and Markov Chain Monte Carlo