useR! 2011 roundup

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As I stand[*] here at Heathrow waiting for my flight back to the States, I thought I'd dash off a few quick reflections of the userR! 2011 conference at University Warwick. It was an outstanding event. There's something about a conference of just a few hundred attendees (there were about 450) that creates a sense of camaraderie and common purpose you just don't get at larger conferences. It was wonderful to re-connect with colleagues, meet long-standing collaborators previously only known via email, and meet many new friends. The event was tremendously well-run, and as a community-run conference proceeded much more smoothly than many professionally-managed conferences I've been to. A big thank-you to the useR 2011 organizing committee (John Aston, Julia Brettschneider, David Firth, Ashley Ford, Ioannis Kosmidis, Tom Nichols, Elke Thönnes and Heather Turner) for such a fantastic conference, and we at Revolution Analytics were proud to have been a sponsor. (Photo courtesy useR! 2011.)

User 2011 conference

There was some great information shared in the tutorials and invited and contributed sessions, too. Here are a few quick nuggets compiled from my notes:

From Max Kuhn's tutorial:

  • The caret package is a powerful yet easy-to-use front end to more than 122 different kinds of predictive models in R. It provides a consident user interface to all models, and makes it easy to tune and compare models to select the one with the best predictive power for your data.
  • The partykit package provides some beautiful visualizations of tree models.

From Ulrike Gromping's talk

From Jonty Rougier's talk

From Pairach Piboonrungroj's talk:

  • Structural Equation Modeling is just a combination of factor modelling and regression
  • R packages for SEM include semOpenMx and lavaan

From Fabrizio Ortolani's talk:

  • The forecast function is a simple yet powerful time series forecasting tool, and out-performs similar functionality in SAS and SAP.

From Patrick Burns' talk:

  • Modern portfolio optimization is computationally intensive, and is basically a knapsack problem with many constraints
  • The packages testthat and RUnit, and the functions and tryCatch, are useful for testing R code
  • Generating random inputs to functions is a good way of testing, especially of error-detecting code which often goes untested.

From Ian Cook's talk:

  • R has been validated R for use in the pharmaceutical industry many times
  • FDA officers have spoken about the use of R for clinical research: Sue Bell in 2006 (although this link now seems to be broken — anyone have a copy?) and Matt Soukup in 2007.

From Alexander Kowarik's talk:

  • The sparkTable package combines official statistics tables with sparklines
  • A cool application of sparklines is win-loss records for football teams

From Olaf Mersmann's talk:

From Paul Murrell's keynote:

  • You can use R to read a PDF file, and extract the vector representation of the images and the text for analysis.
  • The R graphics engine now has support for complex shapes (e.g. polygons with holes), which can be drawn with the grid.path and polypath functions
  • The gridSVG package will soon make it possible to create interative SVG graphics (e.g. high-quality clickable maps) with R.

From Simon Urbanek's keynote:

  • The forthcoming ix package will soon allow for interactive, cross-linked exploratory graphics in R that supports millions of points with high performance.

Anyway, I have to board my plane now. You can see more commentary from useR 2011 at the #user2011 hashtag on Twitter.

[*] Literally, stand. The only power outlets are conveniently placed out of cable reach of chairs. Thanks, BAA!

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