Computing Environments for Statistics

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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.