Monthly Archives: June 2013

Put some cushions on the sofa

June 21, 2013
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I posted earlier this week about sofa (here), introducing a package I started recently that interacts with CouchDB from R. There's been a fair amount of response at least in terms of page views, so I'll take that as a sign to keep going. One thing that would be nice while you are CouchDB-ing is to interact with local...

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The PISA2009lite package is released

June 20, 2013
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The PISA2009lite package is released

This post introduces a new R package named PISA2009lite. I will show how to install this package, what is inside and how to use it. Introduction PISA (Programme for International Student Assessment) is a worldwide study focused on measuring performance of 15-year-old school pupils. More precisely, scholastic performance on mathematics, science and reading is measured

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Measuring Associations

June 20, 2013
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Measuring Associations

In Chapter 18, we discuss a relatively new method for measuring predictor importance called the maximal information coefficient (MIC). The original paper is by Reshef at al (2011). A summary of the initial reactions to the MIC are Speed and Tibshirani (and others can be found here). My (minor) beef with it is the lack...

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Upcoming Rcpp talk in Sydney

June 20, 2013
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The Sydney Users of R Forum (SURF) will be hosting me for a talk on July 10. The focus will be Rcpp for R and C++ integration, and the intent is to have this be really applied with lots of motivating examples. Organizers Louise and Eugene were able...

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Quickly read Excel (xlsx) worksheets into R on any platform

June 20, 2013
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I wrote a couple days about about importing Excel files into R. There are lots of ways to do this, but all the ways that use only R have drawbacks (as I outlined in my last post), and all the other ways require installation of programs other than R. I’m not opposed to using programs

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Huge interest in next LondonR user group meeting

June 20, 2013
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The next LondonR meeting takes place on the 16 July and registrations have already exceeded 200. Presentations at the meeting will be made by Rich Pugh of Mango Solutions, Andrie de Vries of Revolution Analytics and Hadley Wickham of RStudio. All places for a  pre-meeting workshop with Hadley Wickham were snapped up within 2 days of announcing the details. More information...

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How American Century revolutionized their investment platform with R

June 20, 2013
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How American Century revolutionized their investment platform with R

American Century Investments is a top-20 mutual fund company with more than 125 billion dollars of assets under management. The quantitative investment group manages 22 funds, and takes an objective, systematic and disciplined approach to determine which stocks to buy and sell. Real-time data and carefully calibrated statistical models are the foundation of this quantitative approach. This group formerly...

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Datagrabbing Commonly Formatted Sheets from a Google Spreadsheet – Guardian 2014 University Guide Data

June 20, 2013
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Datagrabbing Commonly Formatted Sheets from a Google Spreadsheet – Guardian 2014 University Guide Data

So it seems like it’s that time of year when the Guardian publish their university rankings data (Datablog: University guide 2014), which means another opportunity to have a tinker and see what I’ve learned since last year… (Last year’s hack was a Filtering Guardian University Data Every Which Way You Can…, where I had a

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Bayesian Modeling of Anscombe’s Quartet

June 20, 2013
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Bayesian Modeling of Anscombe’s Quartet

Anscombe’s quartet is a collection of four datasets that look radically different yet result in the same regression line when using ordinary least square regression. The graph below shows Anscombe’s quartet with imposed regression lines (taken from the Wikipedia article). While least square regression is a good choice for dataset 1 (upper left plot) it...

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Data Science Labs: Predictive Models to Improve Vaccine Quality and Production

June 20, 2013
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Data Science Labs: Predictive Models to Improve Vaccine Quality and Production

The age of "blockbuster drugs" is coming to an end, as personalized medicine becomes a reality. Data science will be a major driver of innovation in these and other areas of the pharmaceutical industry. This was demonstrated during a project the Data Science Labs team executed on with a major pharmaceuticals company.

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