Symposium on Case Studies in Bayesian Statistics

贝叶斯统计案例研究第九期是1991年开始的系列讲习班的第九期。研讨会在奇数年的初秋在卡内基梅隆大学举行。第九期研讨会计划于2007年10月19日至20日举行。讲习班系列的最高目标是通过审查特定应用背景下的贝叶斯方法来推动统计实践。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；通过突出需要采用非标准方法的科学问题，促进贝叶斯统计学的继续发展；为科学家和统计学家提供机会，深入介绍他们的工作，突出科学背景和分析方法；鼓励通过有充分文件和同行评议的案例研究，传播在讲习班上提出的研究结果。随着它的发展，这个系列研讨会已经成为贝叶斯统计领域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；提供一个小型会议氛围，促进青年研究人员与资深同事的互动；使青年研究人员在合作研究中面临重要的挑战和机会；并让妇女、任职人数不足的少数群体和可能从小讲习班环境中受益的残疾人作为参与者。除了我们传统的海报会议外，我们的研讨会还包括一个专门由年轻研究人员进行演讲的会议。会议还将在研讨会开始时开设一个短期课程。今年选择的主题是序贯马尔科夫链蒙特卡罗方法。贝叶斯统计案例研究第九期是1991年开始的系列研讨会的第九期。研讨会在奇数年的初秋在卡内基梅隆大学举行。第九期研讨会计划于2007年10月19日至20日举行。讲习班系列的最高目标是通过审查特定应用背景下的贝叶斯方法来推动统计实践。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；通过突出需要采用非标准方法的科学问题，促进贝叶斯统计学的继续发展；为科学家和统计学家提供机会，深入介绍他们的工作，突出科学背景和分析方法；鼓励通过有充分文件和同行评议的案例研究，传播在讲习班上提出的研究结果。大多数统计会议的发表论文的时间都非常有限(比如20分钟)。虽然这对于只与已知和理解稍有不同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最近的一项运动，它需要探索研究的科学背景、统计建模和计算以及结论，并提供所有必要的警告。因此，组织了贝叶斯统计中的案例研究研讨会，为研究人员和讨论者提供充足的时间(3小时)来介绍和讨论两篇严肃的贝叶斯经验论文。还有为年轻研究人员举办的展示他们工作的特别会议、海报会议和短期课程(今年的课程是关于一种重要的新贝叶斯计算技术--序贯马尔科夫链蒙特卡罗方法)。会议支持年轻的研究人员、妇女和服务不足的少数族裔参加会议。

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.