The Fifth International Workshop on Objective Bayesian Methodology will be held in Branson, Missouri, June 4-8, 2005. 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. There are three quite distinct statistical domains in which this development has taken place: parametric estimation, model selection, and prediction, Objective Bayesian methodology is of increasing importance today since application of Bayesian analysis is rapidly growing among nonspecialists, most of whom seek automatic or objective Bayesian procedures. This workshop will emphasize prediction, practical applications such as spatial-temporal models, multiple comparisons and goodness-of-fit. Bayesian methods usually are heavily depend on prior distributions. Although a prior distribution is an important component in the Bayesian paradigm, it is known that even in the absence of any relevant prior information, the Bayes method can produce reliable inference to many challenging problems by employing appropriate objective (noninformative) Bayesian analysis. The principal objectives are to facilitate the exchange of recent research developments in objective Bayesian methodology, to provide opportunities for new researchers, and to establish new collaborations that will channel efforts into pending problems and open new directions for investigation. An important consequence of this meeting will be to further crystallize objective prior methodology as an established area for statistical research.
Statisticians have traditionally embraced one of two main approaches, classical or "frequentist" methods and Bayesian methods. In recent years, advances in computing technology and breakthroughs in statistical theory have made Beyesian methods increasingly attractive, especially for difficult problems with many variables in fields such as meteorology, epidemiology, natural resources, etc. With this increased emphasis on Bayesian statistics, it has become increasingly important to bridge the differences between the two schools of statistical thinking. Objective Bayesians are dedicated to resolving these differences. The planned workshop will bring together 80-100 participants including leaders in the field of objective Bayesian statistics from around the world together with young researchers and students in a setting especially conducive to cooperation and exchange of ideas.
