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Zusatztext ... 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 related fields 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. Informationen zum Autor M. J. Bayarri is Professor of Statistics at Universitat de València. J. M. Bernardo is Professor of Statistics at Universitat de València. James O. Berger is the Arts and Sciences Professor of Statistics at Duke UniversityA. P. Dawid is Professor of Statistics at the University of Cambridge.David Heckerman is the Senior Director of the eScience Research Group for Microsoft.Sir Adrian F M Smith is the Director General of Science and Research at the UK Department of Business, Innovation and Skills. Mike West is the Arts and Sciences Professor of Statistical Science at Duke University. Klappentext Bayesian Statistics 9 covers the latest and last of the Valencia International Meetings on Bayesian Statistics. These proceedings include twenty-three edited and refereed paper followed by extensive and in-depth discussion, offering a wide perspective on the developments in Bayesian statistics over the last four years. Zusammenfassung The Valencia International Meetings on Bayesian Statistics - established in 1979 and held every four years - have been the forum for a definitive overview of current concerns and activities in Bayesian statistics. These are the edited Proceedings of the Ninth meeting, and contain the invited papers each followed by their discussion and a rejoinder by the authors(s). In the tradition of the earlier editions, this encompasses an enormous range of theoretical and applied research, high lighting the breadth, vitality and impact of Bayesian thinking in interdisciplinary research across many fields as well as the corresponding growth and vitality of core theory and methodology.The Valencia 9 invited papers cover a broad range of topics, including foundational and core theoretical issues in statistics, the continued development of new and refined computational methods for complex Bayesian modelling, substantive applications of flexible Bayesian modelling, and new developments in the theory and methodology of graphical modelling. They also describe advances in methodology for specific applied fields, including financial econometrics and portfolio decision making, public policy applications for drug surveillance, studies in the physical and environmental sciences, astronomy and astrophysics, climate change studies, molecular biosciences, statistical genetics or stochastic dynamic networks in systems biology. Inhaltsverzeichnis 1: J. M. Bernardo: Integrated Objective Bayesian Estimation and Hypothesis Testing 2: C. M. Carvalho, H. F. Lopes, O. Aguilar: Dynamic Stock Selection Strategies: A Structured Factor Model Framework 3: Chopin, N. and Jacob, P.: Free Energy Sequential Monte Carlo, Application to Mixture Modelling 4: Consonni G. and La Rocca, L.: Moment Priors for Bayesian Model Choice with Applications to Directed Acyclic Graphs 5: Dunson, D. B. and Bhattacharya, A.: Nonparametric Bayes Regression and Classification Through Mixtures of Product Kernels 6: Frühwirth-Schnatter, S. and Wagner, H.: Bayesian Variable Selection for Random Intercept Modeling of Gaussian and non-Gaussian Data. 7: Goldstein, M.: External Bayesian Analysis for Computer Simulators 8: Gramacy, R. B. and Lee, H. K. H.: Optimization Under Unknown Constraints 9: Huber, M. and Schott, S.: Using TPA for Bayesian Inference 10: Ickstadt, K., Bornkamp, B., Grzegorczyk, M., Wiecorek, J., Sherriff, M. R., Grec...
