DIMACS Workshop: Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications

DIMACS 研讨会：数据深度：稳健的多元分析、计算几何和应用

• 批准号: 0205136
• 负责人: Fred Roberts
• 金额: $ 1.8万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205136&HistoricalAwards=false
• 关键词: DIMACS; Workshop; Data; Depth; Robust

Support is provided for the DIMACS workshop "Data depth: Robust multivariate analysis, computational geometry and applications" at Rutgers University. The workshop brings together theoretical and applied statisticians and computer scientists to promote and further the use and development of depth functions in nonparametric multivariate analysis. Data depth has applications in and connections with a number of different research areas, such as aviation safety, data compression, image analysis, data mining and analysis of genetic data.The workshop addresses significant open conceptual issues and establishes perspective on applications. It also sets primary directions for further research, emphasizing the role of computational geometry in understanding concepts of and developing algorithms for data depth.

为罗格斯大学的DIMACS讲习班“数据深度：稳健的多变量分析、计算几何学和应用”提供支助。该研讨会汇集了理论和应用统计学家和计算机科学家，以促进和进一步使用和非参数多变量分析中的深度函数的发展。数据深度在许多不同的研究领域都有应用和联系，例如航空安全、数据压缩、图像分析、数据挖掘和遗传数据分析。研讨会讨论了重要的开放性概念问题，并建立了应用前景。它还为进一步的研究设定了主要方向，强调了计算几何在理解数据深度概念和开发数据深度算法中的作用。