2007, Oxford University Press (Oxford Science Publications), hbk
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 2007. Bayesian Statistics 8 [top]
Edited by J. M. Bernando, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, and M. West
Published in 2007 in Great Britain in hardback, 678pp, ISBN 9780199214655
About this book: The 8th Valencia International Meeting on Bayesian Statistics was held in Benidorm (Alicante, Spain), 150 kilometres south of Valencia, from June 2nd to June 6th, 2006. These proceedings contain the 20 invited papers with their discussions and synopses of 19 contributed papers (of which five were presented orally and 14 as posters). The papers cover a broad range of topics: Foundational Issues in Statistics (several authors look at this); Disciplinary interface foundations are investigated in two papers; research in Bayesian nonparametrics is evident throughout the proceedings: several papers focus on extending and applying variants of Dirichlet process models and mixtures; flexible models for Bayesian nonparametric regression and function fitting are the primary focus of two papers; and the growth and development of objective Bayesian methods in the last several years is reflected in several papers. Some of the papers look at theory and methods for model assessment and testing; whilst others are concerned primarily with computational questions. Biomedical applications of Bayesian methods continue to represent a major area of success and growth of more realistic, complex statistical modelling. Bayesian research and applications in spatial statistics have expanded substantially over the last decade, and several authors address aspects of this. Social and policy sciences employ Bayesian methods and several papers look at this population survey sampling (Little, Zheng)
CONTENTS
I. INVITED PAPERS (with discussion)
Bishop, C. M. and Lasserre, J.: Generative or Discriminative?
Getting the Best of Both Worlds
Brooks, S. P., Manolopoulou, I. and Emerson, B. C.: Assessing the
Effect of Genetic Mutation  A Bayesian Framework for Determining Population History from DNA Sequence Data
Chakrabarti, A. and Ghosh, J. K.: Some Aspects of Bayesian Model
Selection for Prediction
Clyde, M. A. and Wolpert, R. L.: Nonparametric Function
Estimation Using Overcomplete Dictionaries
Del Moral, P., Doucet, A. and Jasra, A.: Sequential Monte Carlo for
Bayesian Computation
Gamerman, D., Salazar, E. and Reis, E. A.: Dynamic Gaussian
Process Priors, with Applications to The Analysis of Spacetime Data
Gelfand, A. E., Guindani, M. and Petrone, S.: Bayesian Nonparametric Modelling for Spatial Data Using Dirichlet Processes
Ghahramani, Z., Griths, T. L. and Sollich, P.: Bayesian Nonparametric Latent Feature Models
Giron, F. J., Moreno, E. and Casella, G.: Objective Bayesian
Analysis of Multiple Changepoints for Linear Models
Holmes, C. C. and Pintore, A.: Bayesian Relaxation: Boosting,
The Lasso, and other L norms
Little, R. J. A. and Zheng, H.: The Bayesian Approach to the
Analysis of Finite Population Surveys
Merl, D. and Prado, R.: Detecting selection in DNA sequences: Bayesian Modelling and Inference
Mira, A. and Baddeley, A.: Deriving Bayesian and frequentist
estimators from timeinvariance estimating equations:
a unifying approach
Muller, P., Parmigiani, G. and Rice, K.: FDR and Bayesian Multiple
Comparisons Rules
Raftery, 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: pvalues and
Bayes Factors
Schack, R.: Bayesian Probability in Quantum Mechanics
Schmidler, S. C.: Fast Bayesian Shape Matching Using Geometric
Algorithms
Skilling, J.: Nested Sampling for Bayesian Computations
Sun, D. and Berger, J. O.: Objective Bayesian Analysis for the
Multivariate Normal Model
II. CONTRIBUTED PAPERS (synopsis)
Almeida, C. and Mouchart, M.: Bayesian Encompassing Specification
Test Under Not Completely Known Partial Observability
Bernardo, J. M. and Perez, S.: Comparing Normal Means:
New Methods for an Old Problem
Cano, J. A., Kessler, M. and Salmeron, D.: Integral Priors for the
One Way Random Effects Model
Carvalho, C. M. and West, M.: Dynamic MatrixVariate Graphical
Models
Cowell, R. G., Lauritzen, S.L. and Mortera, J.: A Gamma Model
for DNA Mixture Analyses
Denham, R. J. and Mengersen, K.: Geographically Assisted Elicitation
of Expert Opinion for Regression Models
Dukic, V. and Dignam, J.: Hierarchical Multiresolution Hazard Model
for Breast Cancer Recurrence
Hutter, M.: Bayesian Regression of Piecewise Constant Functions
Jirsa, L., Quinn, A. and Varga, F.: Identification of Thyroid Gland
Activity in Radiotherapy
Kokolakis, G. and Kouvaras, G.: Partial Convexification of Random
Probability Measures
Ma, H. and Carlin, B. P.: Bayesian Multivariate Areal Wombling
Madrigal, A. M.: Cluster Allocation Design Networks
Mertens, B. J. A.: Logistic Regression Modelling of Proteomic Mass
Spectra in a CaseControl Study on Diagnosis for Colon Cancer
Mller, J. and Mengersen, K.: Ergodic Averages Via Dominating
Processes
Perugia, M.: Bayesian Model Diagnostics Based on Artificial
Autoregressive Errors
Short, M. B., Higdon, D. M. and Kronberg, P. P.: Estimation
of Faraday Rotation Measures of the Near Galactic Sky, Using
Gaussian Process Models
Spitzner, D. J.: An Asymptotic Viewpoint on HighDimensional
Bayesian Testing
Wallstrom, 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 
Bayesian Statistics: Other Works
