Seventh International Workshop on Objective Bayesian Methodology; Philadelphia, PA

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The investigator will coordinate a five-day Objective Bayes workshop to be held at the Wharton School of the University of Pennsylvania. This workshop will bring together leading researchers from around the world who are active in the area of objective prior methodology. It may be viewed as a continuation of previous international meetings convened over the past 12 years devoted to Objective Bayes theory and methodology. The main objectives of the meeting are to facilitate the exchange of recent research developments within this scientific community, to provide opportunities for new researchers and underrepresented groups to be knowledgeable and active in this important area of research, and to establish new collaborations that will channel efforts into pending problems and open new directions for investigation. Objective Bayesian methodology is, for the most part, oriented towards the development of prior distributions that can be used automatically, i.e., that do not require subjective input other than the specific probabilistic model chosen to describe the data. Accompanying the development of forms particularly suitable for particular types of applications is the study of computational techniques for their implementation and evaluation of both the theoretical and concrete implications of their use. Many of the topics proposed for the workshop reflect an emphasis on objective Bayesian methodology for general classes of practical applications such as spatial-temporal models, hierarchical random-effects models, multiple comparisons and goodness -of-fit. In the direction of specific applications there will be sessions on Bayesian applications in astrophysics and on Bayesian applications in Business and Marketing research. In a more theoretical direction, there will be sessions on the foundations of objective Bayes analysis, including a special retrospective examination of Harold Jeffreys' seminal contributions to the area, and on the unification of Bayesian and frequentist statistical methods. The principal behind these so-called objective Bayes methods also has a long history dating at least back to work of Laplace almost 200 years ago. But two much more recent developments have brought emphasis and importance to the use of these methods. One is the rapidly increasing massiveness and complexity of modern statistical data. This has put extreme and often unmanageable strains on the theory and implementation of conventional non-Bayesian methods. (At the same time such complexity almost completely denies any reasonable possibility of formulating reasonable subjective prior opinions needed for ordinary Bayesian analyses.) The other parallel factor is the development within the past two decades of a suite of mathematical and computational strategies for successfully computing appropriately structured objective Bayesian procedures in highly complex situations. Within this time span an expanding community of scholars has been investigating these objective Bayes models and methods. The current conference proposal is to organize a workshop devoted to the investigation of objective Bayes methods.