Seventh International Workshop on Objective Bayesian Methodology; Philadelphia, PA

调查人员将协调在宾夕法尼亚大学沃顿商学院举行的为期五天的客观贝叶斯研讨会。这次研讨会将汇集世界各地活跃在客观先前方法论领域的顶尖研究人员。它可以被视为过去12年来专门讨论客观贝叶斯理论和方法的以往国际会议的延续。会议的主要目的是促进在这一科学界内交流最近的研究进展，为新的研究人员和代表性不足的群体提供机会，使他们在这一重要的研究领域拥有知识和活跃，并建立新的合作，将努力引导到悬而未决的问题上，并为调查开辟新的方向。客观贝叶斯方法在很大程度上倾向于开发可自动使用的先验分布，即，除了选择描述数据的特定概率模型外，不需要主观输入。在开发特别适用于特定类型应用程序的表格的同时，还研究了实施表格的计算技术，并评估了表格使用的理论和具体影响。为讲习班提出的许多专题反映了对诸如时空模型、分层随机效应模型、多重比较和拟合优度等一般实际应用类别的客观贝叶斯方法的重视。在具体应用方面，将有关于天体物理学中的贝叶斯应用以及商业和营销研究中的贝叶斯应用的会议。在更多的理论方面，将有关于客观贝叶斯分析基础的会议，包括对哈罗德·杰弗里斯对该领域的开创性贡献的特别回顾审查，以及关于贝叶斯统计方法和频率统计方法的统一。这些所谓的客观贝叶斯方法背后的原理也有很长的历史，至少可以追溯到大约200年前拉普拉斯的工作。但最近的两个发展使这些方法的使用变得更加强调和重要。其一是现代统计数据的海量和复杂性迅速增加。这给传统的非贝叶斯方法的理论和实施带来了极端的、往往难以管理的压力。(与此同时，这种复杂性几乎完全否定了提出普通贝叶斯分析所需的合理主观先验意见的任何合理可能性。)另一个并行因素是在过去20年内开发了一套数学和计算策略，用于在高度复杂的情况下成功计算适当结构的客观贝叶斯过程。在这段时间内，越来越多的学者一直在研究这些客观的贝叶斯模型和方法。目前会议的提议是组织一次专门研究客观贝叶斯方法的研讨会。

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.