Bayesian Statistics 8

Hardcover | July 19, 2007

EditorJ.M. Bernardo, M.J. Bayarri, J.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. Covering a broad range of applications and models, includinggenetics, computer vision and computation, the resulting proceedings provide a definitive, up-to-date overview encompassing a wide range of theoretical and applied research. This eighth proceedings includes edited and refereed versions of 20 invited papers plus extensive and in-depth discussionalong with 19 extended four page abstracts of the best presentations offering a wide perspective of the developments in Bayesian statistics over the last four years.

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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. Covering a broad range of applications and models, includinggenetics, computer vision and computation, t...

Format:HardcoverDimensions:688 pages, 9.21 × 6.14 × 1.65 inPublished:July 19, 2007Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199214654

ISBN - 13:9780199214655

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Table of Contents

Bishop, C. M. and Lasserre, J.: Generative or Discriminative? Getting the Best of Both WorldsBrooks, S. P., Manolopoulou, I. and Emerson, B. C.: Assessing the Effect of Genetic Mutation - A Bayesian Framework for Determining Population History from DNA Sequence DataGhosh, J. K. and Chakrabarti, A.: Some Aspects of Bayesian Model Selection for PredictionClyde, M. A. and Wolpert, R. L.: Nonparametric Function Estimation Using Overcomplete DictionariesDel Moral, P., Doucet, A. and Jasra, A.: Sequential Monte Carlo for Bayesian ComputationGamerman, D., Salazar, E. and Reis, E. A.: Dynamic Gaussian Process Priors, with Applications to The Analysis of Space-time DataGelfand, A. E., Guindani, M. and Petrone, S.: Bayesian Nonparametric Modelling for Spatial Data Using Dirichlet ProcessesGhahramani, Z., Griffiths, T. L. and Sollich, P.: Bayesian Nonparametric Latent Feature ModelsGir'on, F. J., Moreno, E. and Casella, G.: Objective Bayesian Analysis of Multiple Changepoints for Linear ModelsHolmes, C. C. and Pintore, A.: Bayesian Relaxation: Boosting, The Lasso, and other L normsLittle, R. J. A. and Zheng, H.: The Bayesian Approach to the Analysis of Finite Population SurveysMerl, D. and Prado, R.: Detecting selection in DNA sequences: Bayesian Modelling and InferenceMira, A. and Baddeley, A.: Deriving Bayesian and frequentist estimators from time-invariance estimating equations: a unifying approachM"uller, P., Parmigiani, G. and Rice, K.: FDR and Bayesian Multiple Comparisons RulesRaftery, A., Newton, M., Satagopan, J. and Krivitsky, P.: Estimating the Integrated Likelihood via Posterior Simulation Using the Harmonic Mean Identity.Rousseau, J.: Approximating Interval Hypothesis: p-values and Bayes FactorsSchack, R.: Bayesian Probability in Quantum MechanicsSchmidler, S. C.: Fast Bayesian Shape Matching Using Geometric AlgorithmsSkilling, J.: Nested Sampling for Bayesian ComputationsSun, D. and Berger, J. O.: Objective Bayesian Analysis for the Multivariate Normal ModelCONTRIBUTED PAPERSAlmeida, C. and Mouchart, M.: Bayesian Encompassing Specification Test Under Not Completely Known Partial ObservabilityBernardo, J. M. and P'erez, S.: Comparing Normal Means: New Methods for an Old ProblemCano, J. A., Kessler, M. and Salmer'on, D.: Integral Priors for the One Way Random Effects ModelCarvalho, C. M. and West, M.: Dynamic Matrix-Variate Graphical ModelsCowell, R. G., Lauritzen, S.L. and Mortera, J.: A Gamma Model for DNA Mixture AnalysesDenham, R. J. and Mengersen, K.: Geographically Assisted Elicitation of Expert Opinion for Regression ModelsDuki'c, V. and Dignam, J.: Hierarchical Multiresolution Hazard Model for Breast Cancer RecurrenceHutter, M.: Bayesian Regression of Piecewise Constant FunctionsHutter, M.: Bayesian Regression of Piecewise Constant FunctionsKokolakis, G. and Kouvaras, G.: Partial Convexification of Random Probability MeasuresMa, H. and Carlin, B. P.: Bayesian Multivariate Areal WomblingMadrigal, A. M.: Cluster Allocation Design NetworksMertens, B. J. A.: Logistic Regression Modelling of Proteomic Mass Spectra in a Case-Control Study on Diagnosis for Colon CancerMoller, J. and Mengersen, K.: Ergodic Averages Via Dominating ProcessesPerugia, M.: Bayesian Model Diagnostics Based on Artificial Autoregressive ErrorsShort, M. B., Higdon, D. M. and Kronberg, P. P.: Estimation of Faraday Rotation Measures of the Near Galactic Sky, Using Gaussian Process ModelsSpitzner, D. J.: An Asymptotic Viewpoint on High-Dimensional Bayesian TestingWallstrom, T. C.: The Marginalization Paradox and Probability Limits Xing, E. P. and Sohn, K.-A.: A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space

Editorial Reviews

`... this collection provides an excellent overview of current research in Bayesian statistics ... Given the high quality of most papers in this volume, and the range of interesting applications, this is a must for academic libraries. I would advise researchers in Statistics, OR, and relatedfields to have a look at the volume, as it provides a fast overview of recent developments in Bayesian statistics. Some of the applications might also provide useful examples for teaching statistics at the postgraduate level.'Journal of the Operational Research Society