Computing Environments for Statistics

统计计算环境

• 批准号: 0604593
• 负责人: Luke-jon Tierney
• 金额: $ 29.96万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0604593&HistoricalAwards=false
• 关键词: Computing; Environments; Statistics

The investigator explores and develops new principles for the design of statistical software to take advantage of modern computing power. Particular emphasis is placed on exploring the effective use of compilation, code analysis, and exception handling for statistical languages, and on developing effective tools and frameworks for parallel computing in statistics. Pilot implementations are incorporated in open source statistical software systems.Effective statistical methodology made available through statistical software is critical to the ability of researchers to make maximal use of experimental and observational data, and for the ability of instructors to teach good research practices. The design principles developed by this research lead to software that improves the ability of researchers, instructors, and other users of statistical methodology to apply this methodology more effectively in scientific research and teaching and to take full advantage of modern high-performance computational resources. These principles also lead to software frameworks that can be used to more rapidly deliver new statistical methodology to end users. Applications in brain imaging analysis serve as a testbed for methods and principles developed in this research.

研究人员探索和开发统计软件设计的新原则，以利用现代计算能力。特别强调的是，探索有效地使用编译，代码分析和异常处理的统计语言，并在统计并行计算开发有效的工具和框架。 开放源码统计软件系统中纳入了试点实施，通过统计软件提供的有效统计方法对于研究人员最大限度地利用实验和观测数据的能力以及教员传授良好研究做法的能力至关重要。 本研究开发的设计原则导致软件，提高了研究人员，教师和其他用户的统计方法，更有效地应用这种方法在科学研究和教学的能力，并充分利用现代高性能的计算资源。 这些原则还导致软件框架，可用于更快地向最终用户提供新的统计方法。 在脑成像分析中的应用可以作为本研究中开发的方法和原理的测试平台。