Advanced Topics in R

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Date

2014-12-05

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Indiana University Workshop in Methods

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https://hdl.handle.net/2022/21959

Abstract

In this follow up workshop to “Introduction to R” researchers will have the opportunity for a deeper dive into R. Available on all IU's supercomputers, R is a flexible open source statistical programming language that can work with large and complex data sets. This workshop will address several advanced topics in R as well as giving participants the opportunity to use R on IU’s supercomputers. The topics to be covered include: R scripting on IU supercomputers; debugging, profiling, and performance analysis of R code; parallel programming in R, including the Rmpi and snowfall packages; and advanced plotting in R. Participants will have access to the supercomputer Big Red II during the session and will be able to see hands-on examples of running R code and submitting batch jobs in R.

Description

Hui Zhang is principal research software engineer with IU Research Technology. Hui has a broad background in visualization and analytics, with specific training and expertise in areas including scientific visualization and data-intensive computing. Hui recently participated in the NSF-funded Stampede project where he investigated data-intensive scientific workflows with applications across science and health domains. Jefferson Davis is a software consultant with Research Analytics. He has worked on several projects that have used R and R libraries. Sample projects include visualizing economic simulations, simplifying demographic data, and running semantic analyses on large text files. Scott Michael is the manager of the Research Analytics group within UITS. His areas of expertise include high performance computational systems, workflow development for supercomputers, and application parallelization. His domain expertise lies in computational simulations of astrophysical disks.

Keywords

Workshop in Methods, R (software), research methods, statistical methods

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Workshop in Methods