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Symposium on Case Studies in Bayesian Statistics

Symposium on Case Studies in Bayesian Statistics
贝叶斯统计案例研究研讨会
批准号:
9972601
负责人:
Robert Kass
金额:
$1.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-08-15 至 2000-07-31

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中文摘要
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英文摘要
The symposium ``Case Studies in Bayesian Statistics 4'' will be held at Carnegie Mellon University on Friday September 24 and Saturday September 25, 1999. The symposium will include three extended presentations of applications of Bayesian methods. In these applications the statistician has been an integral member of the research team. Two contributed poster sessions will also be held. The objectives of the symposium are to:(i) identify and focus attention on specific implementation and theoretical problems that hinder applications of Bayesian methods, and to identify candidate solutions;(ii) provide a forum in which the interplay between statistical theory and practice will be explored in the context of concrete research projects; (iii) provide a small-meeting atmosphere within which junior investigators and graduate students can explore substantial Bayesian applications with experienced researchers; and(iv) produce a volume containing well-documented case studies and data sets suitable for use by researchers, practitioners, educators and students of applied statistics and other quantitative fields.As increasingly much background information becomes available to scientists undertaking an investigation, it is important to utilize previous knowledge effectively in designing studies and analyzing data. Bayesian statistical methods are tailored to this purpose. There have been many recent advances in Bayesian statistical theory and computation, but scientific meetings rarely spend substantial time discussing applications. The purpose of this symposium is to concentrate attention solely on applications of Bayesian statistics. The goal is to elucidate the interplay between theory and practice and thereby identify successful methods and indicate important directions for future research.
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