Computing Environments for Statistics

统计的计算环境摘要研究者探索和发展了统计软件设计的新原则，以利用现代计算能力。特别强调的是探索统计语言的编译、名称空间管理和异常处理的有效使用，以及为统计中的并行计算开发有效的工具和框架。试点实现被纳入开源统计软件系统。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师教授良好研究实践的能力至关重要。本研究开发的设计原则导致软件提高了研究人员、教师和其他统计方法用户在科学研究和教学中更有效地应用该方法的能力。这些原则还导致了软件框架，可以用来更快地向最终用户交付新的统计方法。

Proposal ID DMS-0305226PI Luke-jon TierneyTitle Computing environments for statisticsAbstractThe 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, name space management, 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. These principles also lead to software frameworks that can be used to more rapidly deliver new statistical methodology to end users.