An International Workshop on Bayesian Data Analysis

摘要贝叶斯统计方法在过去的10年里，随着基于模拟的计算方法的广泛采用，包括马尔可夫链蒙特卡罗技术作为进步的引擎，在能力、科学相关性和适用性方面取得了相当大的进步。尖端的贝叶斯建模现在正在广泛的领域进行，包括生物信息学，计算机科学，工程，流行病学，机器学习和统计学。思想的跨学科转移很重要，但越来越难以实现，因为每个领域的文献都在不断涌现，而且对类似概念使用不同的术语，这阻碍了搜索引擎帮助一个领域的工作人员在其他学科中保持最新的能力。贝叶斯方法本身对于研究是很重要的，但是为了获得最大的科学相关性(1)对建模的仔细关注和(2)对适合上下文的方法的需求也是至关重要的。在这个项目中，加州大学圣克鲁斯分校（UCSC）新成立的应用数学与统计学系（AMS）的统计小组将于2003年8月8日至10日（周五至周日）在UCSC举办贝叶斯数据分析国际研讨会，作为2003年8月3日至7日在加州旧金山附近举行的联合统计会议（JSM）之后举行的一种卫星会议，来解决这些问题。我们的目标是汇集来自世界各地各学科的约100名对贝叶斯建模和数据分析感兴趣的人，其中包括约30名受邀参与者（领先的贝叶斯研究人员）作为演讲者和讨论者，以促进对常见问题的多学科讨论和跨学科思想的转移（其中许多人将是年轻的研究人员）。研讨会的重点将是贝叶斯数据分析：从科学或决策中的实际问题开始，用统计术语阐述该问题，使用贝叶斯方法解决原始问题，并讨论解决方案的统计和实质性优势和弱点，并充分关注现实环境与贝叶斯模型构建，检查和重新制定之间的相互作用。国家科学基金会的资金将主要用于为年轻研究人员、少数民族和其他代表性不足的群体提供部分旅行和当地费用支持。

An International Workshop on Bayesian Data AnalysisPI: David DraperProposal: DMS 0311766 AbstractBayesian statistical methods have gained considerably in power, scientific relevance, and applicability over the last 10 years, with the widespread adoption of simulation-based computation methods involving Markov chain Monte Carlo techniques as the engine of progress. Cutting-edge Bayesian modeling is now going on in a wide variety of fields, including bioinformatics, computer science, engineering, epidemiology, machine learning, and statistics. Interdisciplinary transfer of ideas is important but increasingly difficult to achieve, as the literatures in each field burgeon and the use of different terms for similar concepts hampers the ability of search engines to help workers in one field keep up-to-date in other disciplines. Bayesian methodology is important to study in its own right, but for greatest scientific relevance (1) careful attention to modeling and (2) the need for methodology to be appropriate to context are also crucial.In this project the Statistics Group within the newly-forming Department of Applied Mathematics and Statistics (AMS) at the University of California, Santa Cruz (UCSC), will address these issues by hosting an International Workshop on Bayesian Data Analysis at UCSC from Friday through Sunday 8-10 August 2003, as a kind of satellite meeting to be held right after the Joint Statistical Meetings (JSM) nearby in San Francisco, CA, from August 3--7, 2003. Our objectives are to bring together about 100 people interested in Bayesian modeling and data analysis from a wide variety of disciplines around the world, including about 30 invited participants (leading Bayesian researchers) as speakers and discussants, to promote multidisciplinary discussion of common problems and interdisciplinary transfer of ideas (many of these people will be young researchers). The focus of the Workshop will be Bayesian data analysis: starting with a real problem in science or decision-making, formulating this problem in statistical terms, using Bayesian methods to solve the original problem, and discussing the strengths and weaknesses of the solution both statistically and substantively, with plenty of attention to the interplay between the real-world context and the Bayesian model building, checking, and reformulating. NSF funding will be principally used to provide partial travel and local expenses support for young researchers, minorities, and other under-represented groups.