Symposium on Case Studies in Bayesian Statistics

案例研究贝叶斯统计九是该系列的第九个讲习班，开始于1991年。这些研讨会是在奇数年举行的卡内基梅隆大学在初秋。第九期讲习班计划于2007年10月19日至20日举行。系列研讨会的最高目标是通过在特定应用环境中检查贝叶斯方法来推进统计实践。讲习班的目的是探讨统计理论和实践在实质性科学研究中的相互作用;通过突出需要非标准方法的科学问题，促进贝叶斯统计的持续发展;为科学家和统计人员提供一个深入介绍其工作的机会，突出科学背景和分析方法;并鼓励通过有据可查和经同行审查的案例研究传播研讨会上提出的结论。随着它的发展，这个研讨会系列已成为贝叶斯统计年轻研究人员的重要会议。讲习班的目的是鼓励青年研究人员，包括研究生，介绍他们的应用工作;提供一个小型会议的气氛，以促进青年研究人员与资深同事的互动;使青年研究人员了解合作研究中的重要挑战和机会;并吸收妇女、代表人数不足的少数群体和残疾人参加，他们可能会从小型讲习班的环境中受益。除了我们传统的海报会议，我们的研讨会包括一个专门由年轻研究人员介绍的会议。会议还将在讲习班开始时举办一个短期课程。今年的主题是序贯马尔可夫链蒙特卡罗方法。贝叶斯统计的案例研究IX是1991年开始的系列研讨会的第九次。这些研讨会是在奇数年举行的卡内基梅隆大学在初秋。第九期讲习班计划于2007年10月19日至20日举行。系列研讨会的最高目标是通过在特定应用环境中检查贝叶斯方法来推进统计实践。讲习班的目的是探讨统计理论和实践在实质性科学研究中的相互作用;通过突出需要非标准方法的科学问题，促进贝叶斯统计的持续发展;为科学家和统计人员提供一个深入介绍其工作的机会，突出科学背景和分析方法;并鼓励通过有据可查和经同行审查的案例研究传播研讨会上提出的结论。大多数统计会议允许非常有限的时间（如20分钟）用于介绍论文。虽然这对于那些只稍微偏离已知和理解的研究来说是可以的，但对于更雄心勃勃的研究来说，这是一个主要的阐述问题。贝叶斯统计学是统计学中的一个新的运动，它需要探索研究的科学背景、统计建模和计算以及结论，以及所有必要的警告。因此，贝叶斯统计案例研究研讨会的组织给研究人员和讨论者充足的时间（3小时）来介绍和讨论两个严重的贝叶斯经验论文。还有一个特别会议，年轻的研究人员介绍他们的工作，海报会议，和短期课程（今年是顺序马尔可夫链蒙特卡罗方法，一个重要的新贝叶斯计算技术）。会议支持年轻的研究人员，妇女和服务不足的少数民族参加会议。

Case Studies in Bayesian Statistics IX is the ninth workshop in the series that was begun in 1991. The workshops are held in odd years at Carnegie Mellon University in early fall. The ninth workshop is planned for October 19-20, 2007. The highest level goal of the workshop series is to advance statistical practice by examining Bayesian methods in specific applied contexts. The objectives of the workshop are to explore the interplay of statistical theory and practice in the context of substantive scientific research; promote the continued development of Bayesian statistics by highlighting problems in the sciences that require non-standard approaches; provide an opportunity for scientists and statisticians to present their work in depth, highlighting both the scientific background and the analytical approaches; and encourage dissemination of the findings presented at the workshop via well documented and peer reviewed case studies. As it has evolved, this workshop series has become an important meeting for younger researchers in Bayesian statistics. The workshop aims to encourage young researchers, including graduate students, to present their applied work; provide a small meeting atmosphere to facilitate the interaction of young researchers with senior colleagues; expose young researchers to important challenges and opportunities in collaborative research; and include as participants women, under-represented minorities and persons with disabilities who might benefit from the small workshop environment. In addition to our traditional poster session, our workshops include a session devoted to presentations by younger researchers. The conference will also run a short course at the beginning of the workshop. The topic chosen for this year is sequential Markov Chain Monte Carlo methods.Case Studies in Bayesian Statistics IX is the ninth workshop in the series that was begun in 1991. The workshops are held in odd years at Carnegie Mellon University in early fall. The ninth workshop is planned for October 19-20, 2007. The highest level goal of the workshop series is to advance statistical practice by examining Bayesian methods in specific applied contexts. The objectives of the workshop are to explore the interplay of statistical theory and practice in the context of substantive scientific research; promote the continued development of Bayesian statistics by highlighting problems in the sciences that require non-standard approaches; provide an opportunity for scientists and statisticians to present their work in depth, highlighting both the scientific background and the analytical approaches; and encourage dissemination of the findings presented at the workshop via well documented and peer reviewed case studies. Most statistics meetings allow a very limited time (like 20 minutes) for the presentation of a paper. While this is OK for studies that depart only slightly from what is already known and understood, it is a major expositional problem for more ambitious studies. Bayesian statistics, a recent movement in statistics, requires exploration of the scientific background of a study, the statistical modeling and computation, and the conclusions, with all the necessary caveats. Accordingly, the Case Studies in Bayesian Statistics workshops are organized to give researchers and discussants ample time (3 hours) to present and discuss each of two serious Bayesian empirical papers. There is also a special session for young researchers to present their work, a poster session, and a short course (which this year is on sequential Markov Chain Monte Carlo methods, an important new Bayesian computing technique). The conference supports younger researchers, women and under-served minorities to attend the meeting.