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Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics, Bangalore, India, December 19-23, 1988 Award In Indian Currency

Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics, Bangalore, India, December 19-23, 1988 Award In Indian Currency
印度-美国
批准号:
8814731
负责人:
Prem Goel
金额:
$5.06万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1988
资助国家:
美国
项目状态:
已结题
起止时间:
1988-08-01 至 1990-01-31

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英文摘要
Description: This project provides for participation by 20 U.S. scientists in an Indo-U.S. workshop on Bayesian analysis in statistics and econometrics to be held at the Indian Statistical Institute (ISI), Bangalore, India between December 19 and 23, 1988. The U.S. organizer is Dr. Prem Goel of Ohio State University, and the Indian co-organizer is Dr. N.S. Iyengar, head of the economic analysis unit at ISI, and president of the Indian Econometric Society. Topics to be covered are: Econometric modeling and forecasting; Bayesian computing; Reliability and process control; Foundation and decision theory; Hierarchical models and robust Bayes analysis; and Bayes and empirical Bayes inferences. The proceedings are expected to be published. Scope: Indian statisticians have been very active in India, and many Indians who work in the U.S. have contributed greatly to the field. The proposed workshop is to impart the relatively new Bayesian approach to statistics and decision analysis, to the Indian Community of young statisticians who mostly emphasize the classic approach to the same problems. This interaction is likely to make a large impact on the future research in statistics in general and in its applications to India, by stimulating interest in this modern aspect of statistics research and in modernization of statistical education.
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IGMS: Research and Studies in Digital Signal and Image Processing
U.S.-Australia Cooperative Research: Mathematically Optimal Solutions to Decision-Making
Mathematical Sciences: Bayesian Analysis, Chaos, Stochastic Optimization, and File-Merging Methodology
Mathematical Sciences: Bayesian Design and Analysis, Stochastic Optimization, and File-Merging Methodology
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