Publications by David Smith
Revolution Newsletter: October 2011
The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full October edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Applications of R Contest: Deadline October 31. Revolution Analytics is o...
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The R-Files: Paul Teetor
“The R-Files” is an occasional series from Revolution Analytics, where we profile prominent members of the R Community. Name: Paul Teetor Profession: Quantitative developer (freelance) Nationality: American Years Using R: 7 Known for: Author of R Cookbook (O’Reilly Media, 2011) An active member of the R community, Paul Teetor is a quan...
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Slides for Revolution R Enterprise: 100% R and more
If you haven't yet taken a look at Revolution R Enterprise but wanted to know what is adds to open-source R, the slides below from yesterday's webinar will give you a quick overview: A recorded replay with audio of the me giving the presentation is also available at the link below. Revolution Analytics Webinars: Revolution R Enterprise: 100% R a...
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ggplot2 for big data
(Hadley Wickham, author of ggplot2 and several other R packages, guest blogs today about forthcoming big-data improvements to his R graphics package — ed.) Hi! I'm Hadley Wickham and I'm guest posting on the Revolutions blog to give you a taste of some of the visualisation work that my research team and I worked on this summer. This work has ...
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High-schoolers celebrate World Statistics Day
Rose Hoffmann, AP Statistics teacher at Catholic Memorial High School in Waukesha, WI sent the following note to the Revolution Analytics team: In August 2010, my husband who is a statistician attended the American Statistical convention. Your company gave out the flying monkey with a black cape … He gave me the monkey since it was my fi...
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NYT on Big Data and R
In the New York Times' “Bits” blog today, Quentin Hardy offers recollections on Big Data talks at the recent Web 2.0 Summit. He begins with a definition of Big Data: Big Data is really about … the benefits we will gain by cleverly sifting through it to find and exploit new patterns and relationships. You see it now in things like Facebook ...
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One week left to enter the $20,000 "Applications of R" contest
The deadline to enter the “Applications of R in Business” contest is just a week away. To qualify for $20,000 in prizes from Revolution Analytics, your entry must be submitted to inside-r.org by midnight PST on October 31. Note that this doesn't have to be your final submission: as long as you've entered a draft version, you can still mod...
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"Anyone planning to work with Big Data ought to learn Hadoop and R"
Dan Woods at Forbes interviewed LinkedIn's Daniel Tunkelang about the rise of data science and on building data science teams. When asked how students today should prepare themselves to be data scientists, Tunkelang gives some good advice: When we built the data science team at LinkedIn a few years ago, we looked for raw talent, assuming that sm...
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Mixed-Effects Models in R with Quantum Forest
For anyone who wants to estimate linear or nonlinear mixed-effects models (aka random-effects models, hierarchical models or multilevel models) using the R language, the Quantum Forest blog has several recent posts that will be of interest. Written by Luis Apiolaza from the School of Forestry at the University of Canterbury in New Zealand, t...
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Building diversified portfolios with R
A common approach to reducing risk associated with financial portfolios is diversification. A portfolio made of components that are all highly correlated with each other — a portfolio composed solely of financial stocks, for example — is risky, because if there's a wide-spread crisis that affects the banking sector, all components of the port...
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